diff --git a/scripts/batch_run.yml b/scripts/batch_run.yml index b8e805e..f2c5e05 100644 --- a/scripts/batch_run.yml +++ b/scripts/batch_run.yml @@ -3,55 +3,69 @@ run_time: 4 params: request_freq: - low: + - middle: - high: dag_type: - - single: + # - single: + # - mix: + - dag: no_mech_latency: - true: - - false: + # - false: mech_scale_sche: scale_sche_joint: scale_num: - - hpa: - - temp_scaler: + # - hpa: + # - temp_scaler: + - ensure_scaler: scale_down_exec: - default: scale_up_exec: - least_task: sche: - - pos: greedy - - pos: random + # - bp_balance: + # - pos: greedy + - ensure_scheduler: filter: - - [] + # - [] - [{'careful_down':''}] + scale_sche_separated: scale_num: + - temp_scaler: - hpa: + - lass: scale_down_exec: - default: scale_up_exec: - least_task: sche: - - greedy: - - random: - - rotate: + # - greedy: + # - hash: + # - random: + - load_least: + # - rotate: + - pass: filter: - - [] + # - [] - [{'careful_down':''}] - no_scale: - scale_num: - - 'no': - scale_down_exec: - - default: - scale_up_exec: - - 'no': - sche: - - greedy: - - random: - - rotate: - filter: - - [] + + # no_scale: + # scale_num: + # - 'no': + # scale_down_exec: + # - default: + # scale_up_exec: + # - 'no': + # sche: + # # - greedy: + # # - hash: + # # - random: + # # - rotate: + # # - faasflow: + # filter: + # - [] mech_other: instance_cache_policy: diff --git a/scripts/fast_draw.py b/scripts/fast_draw.py index 797c1eb..c4eee18 100644 --- a/scripts/fast_draw.py +++ b/scripts/fast_draw.py @@ -8,7 +8,7 @@ import json -AVG_CNT=2 +AVG_CNT=1 # #gen_tmp_yaml diff --git a/scripts/fast_draw.yml b/scripts/fast_draw.yml index 3131fc5..95c5c75 100644 --- a/scripts/fast_draw.yml +++ b/scripts/fast_draw.yml @@ -1,5 +1,5 @@ -avg_cnt: 2 +avg_cnt: 1 ## filter with fixed value filter: @@ -11,76 +11,22 @@ filter: ## each group bars targets_alias: -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'no.', 'scale_down_exec': 'default.', 'scale_up_exec': 'no.', 'sche': 'greedy.', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '0'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml0.mtno_scale.scl(no.)(default.)(no.)[].scd(greedy.).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'no.', 'scale_down_exec': 'default.', 'scale_up_exec': 'no.', 'sche': 'random.', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '0'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml0.mtno_scale.scl(no.)(default.)(no.)[].scd(random.).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'no.', 'scale_down_exec': 'default.', 'scale_up_exec': 'no.', 'sche': 'rotate.', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '0'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml0.mtno_scale.scl(no.)(default.)(no.)[].scd(rotate.).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.greedy', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '0'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_joint.scl(hpa.)(default.)(least_task.)[(careful_down.)].scd(pos.greedy).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.random', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '0'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_joint.scl(hpa.)(default.)(least_task.)[(careful_down.)].scd(pos.random).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.greedy', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '0'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_joint.scl(hpa.)(default.)(least_task.)[].scd(pos.greedy).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.random', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '0'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_joint.scl(hpa.)(default.)(least_task.)[].scd(pos.random).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'temp_scaler.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.greedy', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '0'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_joint.scl(temp_scaler.)(default.)(least_task.)[(careful_down.)].scd(pos.greedy).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'temp_scaler.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.random', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '0'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_joint.scl(temp_scaler.)(default.)(least_task.)[(careful_down.)].scd(pos.random).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'temp_scaler.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.greedy', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '0'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_joint.scl(temp_scaler.)(default.)(least_task.)[].scd(pos.greedy).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'temp_scaler.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.random', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '0'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_joint.scl(temp_scaler.)(default.)(least_task.)[].scd(pos.random).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'greedy.', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '0'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[(careful_down.)].scd(greedy.).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'random.', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '0'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[(careful_down.)].scd(random.).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'rotate.', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '0'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[(careful_down.)].scd(rotate.).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'greedy.', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '0'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[].scd(greedy.).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'random.', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '0'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[].scd(random.).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'rotate.', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '0'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[].scd(rotate.).ic(no_evict.)'] - -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'no.', 'scale_down_exec': 'default.', 'scale_up_exec': 'no.', 'sche': 'greedy.', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '1'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml1.mtno_scale.scl(no.)(default.)(no.)[].scd(greedy.).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'no.', 'scale_down_exec': 'default.', 'scale_up_exec': 'no.', 'sche': 'random.', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '1'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml1.mtno_scale.scl(no.)(default.)(no.)[].scd(random.).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'no.', 'scale_down_exec': 'default.', 'scale_up_exec': 'no.', 'sche': 'rotate.', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '1'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml1.mtno_scale.scl(no.)(default.)(no.)[].scd(rotate.).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.greedy', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_joint.scl(hpa.)(default.)(least_task.)[(careful_down.)].scd(pos.greedy).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.random', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_joint.scl(hpa.)(default.)(least_task.)[(careful_down.)].scd(pos.random).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.greedy', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '1'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_joint.scl(hpa.)(default.)(least_task.)[].scd(pos.greedy).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.random', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '1'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_joint.scl(hpa.)(default.)(least_task.)[].scd(pos.random).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'temp_scaler.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.greedy', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_joint.scl(temp_scaler.)(default.)(least_task.)[(careful_down.)].scd(pos.greedy).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'temp_scaler.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.random', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_joint.scl(temp_scaler.)(default.)(least_task.)[(careful_down.)].scd(pos.random).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'temp_scaler.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.greedy', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '1'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_joint.scl(temp_scaler.)(default.)(least_task.)[].scd(pos.greedy).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'temp_scaler.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.random', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '1'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_joint.scl(temp_scaler.)(default.)(least_task.)[].scd(pos.random).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'greedy.', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[(careful_down.)].scd(greedy.).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'random.', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[(careful_down.)].scd(random.).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'rotate.', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[(careful_down.)].scd(rotate.).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'greedy.', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '1'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[].scd(greedy.).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'random.', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '1'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[].scd(random.).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'high', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'rotate.', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '1'}, 'sd.rfhigh.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[].scd(rotate.).ic(no_evict.)'] - -# - [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'no.', 'scale_down_exec': 'default.', 'scale_up_exec': 'no.', 'sche': 'greedy.', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '0'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml0.mtno_scale.scl(no.)(default.)(no.)[].scd(greedy.).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'no.', 'scale_down_exec': 'default.', 'scale_up_exec': 'no.', 'sche': 'random.', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '0'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml0.mtno_scale.scl(no.)(default.)(no.)[].scd(random.).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'no.', 'scale_down_exec': 'default.', 'scale_up_exec': 'no.', 'sche': 'rotate.', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '0'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml0.mtno_scale.scl(no.)(default.)(no.)[].scd(rotate.).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.greedy', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '0'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_joint.scl(hpa.)(default.)(least_task.)[(careful_down.)].scd(pos.greedy).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.random', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '0'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_joint.scl(hpa.)(default.)(least_task.)[(careful_down.)].scd(pos.random).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.greedy', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '0'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_joint.scl(hpa.)(default.)(least_task.)[].scd(pos.greedy).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.random', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '0'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_joint.scl(hpa.)(default.)(least_task.)[].scd(pos.random).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'temp_scaler.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.greedy', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '0'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_joint.scl(temp_scaler.)(default.)(least_task.)[(careful_down.)].scd(pos.greedy).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'temp_scaler.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.random', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '0'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_joint.scl(temp_scaler.)(default.)(least_task.)[(careful_down.)].scd(pos.random).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'temp_scaler.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.greedy', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '0'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_joint.scl(temp_scaler.)(default.)(least_task.)[].scd(pos.greedy).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'temp_scaler.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.random', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '0'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_joint.scl(temp_scaler.)(default.)(least_task.)[].scd(pos.random).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'greedy.', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '0'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[(careful_down.)].scd(greedy.).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'random.', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '0'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[(careful_down.)].scd(random.).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'rotate.', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '0'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[(careful_down.)].scd(rotate.).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'greedy.', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '0'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[].scd(greedy.).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'random.', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '0'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[].scd(random.).ic(no_evict.)'] -# - [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'rotate.', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '0'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml0.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[].scd(rotate.).ic(no_evict.)'] -- [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'no.', 'scale_down_exec': 'default.', 'scale_up_exec': 'no.', 'sche': 'greedy.', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtno_scale.scl(no.)(default.)(no.)[].scd(greedy.).ic(no_evict.)'] -- [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'no.', 'scale_down_exec': 'default.', 'scale_up_exec': 'no.', 'sche': 'random.', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtno_scale.scl(no.)(default.)(no.)[].scd(random.).ic(no_evict.)'] -- [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'no.', 'scale_down_exec': 'default.', 'scale_up_exec': 'no.', 'sche': 'rotate.', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtno_scale.scl(no.)(default.)(no.)[].scd(rotate.).ic(no_evict.)'] +- [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'ensure_scaler.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'ensure_scheduler.', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_joint.scl(ensure_scaler.)(default.)(least_task.)[(careful_down.)].scd(ensure_scheduler.).ic(no_evict.)'] +- [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'bp_balance.', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_joint.scl(hpa.)(default.)(least_task.)[(careful_down.)].scd(bp_balance.).ic(no_evict.)'] - [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.greedy', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_joint.scl(hpa.)(default.)(least_task.)[(careful_down.)].scd(pos.greedy).ic(no_evict.)'] -- [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.random', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_joint.scl(hpa.)(default.)(least_task.)[(careful_down.)].scd(pos.random).ic(no_evict.)'] -- [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.greedy', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_joint.scl(hpa.)(default.)(least_task.)[].scd(pos.greedy).ic(no_evict.)'] -- [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.random', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_joint.scl(hpa.)(default.)(least_task.)[].scd(pos.random).ic(no_evict.)'] +- [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'temp_scaler.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'bp_balance.', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_joint.scl(temp_scaler.)(default.)(least_task.)[(careful_down.)].scd(bp_balance.).ic(no_evict.)'] - [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'temp_scaler.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.greedy', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_joint.scl(temp_scaler.)(default.)(least_task.)[(careful_down.)].scd(pos.greedy).ic(no_evict.)'] -- [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'temp_scaler.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.random', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_joint.scl(temp_scaler.)(default.)(least_task.)[(careful_down.)].scd(pos.random).ic(no_evict.)'] -- [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'temp_scaler.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.greedy', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_joint.scl(temp_scaler.)(default.)(least_task.)[].scd(pos.greedy).ic(no_evict.)'] -- [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'temp_scaler.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pos.random', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_joint.scl(temp_scaler.)(default.)(least_task.)[].scd(pos.random).ic(no_evict.)'] - [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'greedy.', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[(careful_down.)].scd(greedy.).ic(no_evict.)'] -- [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'random.', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[(careful_down.)].scd(random.).ic(no_evict.)'] +- [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'hash.', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[(careful_down.)].scd(hash.).ic(no_evict.)'] +- [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'load_least.', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[(careful_down.)].scd(load_least.).ic(no_evict.)'] +- [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pass.', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[(careful_down.)].scd(pass.).ic(no_evict.)'] - [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'rotate.', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[(careful_down.)].scd(rotate.).ic(no_evict.)'] -- [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'greedy.', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[].scd(greedy.).ic(no_evict.)'] -- [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'random.', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[].scd(random.).ic(no_evict.)'] -- [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'hpa.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'rotate.', 'instance_cache_policy': 'no_evict.', 'filter': '', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_separated.scl(hpa.)(default.)(least_task.)[].scd(rotate.).ic(no_evict.)'] +- [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'lass.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'load_least.', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_separated.scl(lass.)(default.)(least_task.)[(careful_down.)].scd(load_least.).ic(no_evict.)'] +- [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'lass.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pass.', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_separated.scl(lass.)(default.)(least_task.)[(careful_down.)].scd(pass.).ic(no_evict.)'] +- [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'temp_scaler.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'greedy.', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_separated.scl(temp_scaler.)(default.)(least_task.)[(careful_down.)].scd(greedy.).ic(no_evict.)'] +- [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'temp_scaler.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'load_least.', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_separated.scl(temp_scaler.)(default.)(least_task.)[(careful_down.)].scd(load_least.).ic(no_evict.)'] +- [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'temp_scaler.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'pass.', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_separated.scl(temp_scaler.)(default.)(least_task.)[(careful_down.)].scd(pass.).ic(no_evict.)'] +- [{'rand_seed': '', 'request_freq': 'low', 'dag_type': 'single', 'cold_start': 'high', 'fn_type': 'cpu', 'scale_num': 'temp_scaler.', 'scale_down_exec': 'default.', 'scale_up_exec': 'least_task.', 'sche': 'rotate.', 'instance_cache_policy': 'no_evict.', 'filter': '(careful_down.)', 'no_mech_latency': '1'}, 'sd.rflow.dtsingle.cshigh.ftcpu.nml1.mtscale_sche_separated.scl(temp_scaler.)(default.)(least_task.)[(careful_down.)].scd(rotate.).ic(no_evict.)'] ## group on x axis: @@ -98,6 +44,3 @@ values: - {alias: Quality-Price Ratio, trans: 'rps/cost_per_req/time_per_req if cost_per_req>0 and time_per_req>0 else 0'} - {alias: Throuphput, trans: rps*1000} - {alias: Avg Container Count, trans: fn_container_cnt} - -sort_by: -- Quality-Price Ratio: \ No newline at end of file diff --git a/scripts/run_different_req_freq.py b/scripts/run_different_req_freq.py index 8f26733..644b0d2 100644 --- a/scripts/run_different_req_freq.py +++ b/scripts/run_different_req_freq.py @@ -66,13 +66,13 @@ def run(self): # [['scale_sche_joint',''],["hpa",""],["default",""],["least_task",""],["bp_balance",""],[{'careful_down':''}],["no_evict",""]], [['scale_sche_joint',''],["hpa",""],["default",""],["least_task",""],["pos","greedy"],[{'careful_down':''}],["no_evict",""]], - [['scale_sche_joint',''],["hpa",""],["default",""],["least_task",""],["pos","random"],[{'careful_down':''}],["no_evict",""]], + # [['scale_sche_joint',''],["hpa",""],["default",""],["least_task",""],["pos","random"],[{'careful_down':''}],["no_evict",""]], - [['scale_sche_joint',''],["temp_scaler",""],["default",""],["least_task",""],["pos","random"],[{'careful_down':''}],["no_evict",""]], + # [['scale_sche_joint',''],["temp_scaler",""],["default",""],["least_task",""],["pos","random"],[{'careful_down':''}],["no_evict",""]], - [['scale_sche_joint',''],["temp_scaler",""],["default",""],["least_task",""],["pos","greedy"],[{'careful_down':''}],["no_evict",""]], + # [['scale_sche_joint',''],["temp_scaler",""],["default",""],["least_task",""],["pos","greedy"],[{'careful_down':''}],["no_evict",""]], - [['scale_sche_separated',''],["hpa",""],["default",""],["least_task",""],["greedy",""],[{'careful_down':''}],["no_evict",""]], + # [['scale_sche_separated',''],["hpa",""],["default",""],["least_task",""],["greedy",""],[{'careful_down':''}],["no_evict",""]], # [['scale_sche_separated',''],["hpa",""],["default",""],["least_task",""],["greedy",""],[{'careful_down':''}],["lru","10"]], # [['scale_sche_separated',''],["hpa",""],["default",""],["least_task",""],["random",""],[{'careful_down':''}],["no_evict",""]], # [['scale_sche_separated',''],["hpa",""],["default",""],["least_task",""],["random",""],[{'careful_down':''}],["lru","10"]], diff --git a/serverless_sim/.gitignore b/serverless_sim/.gitignore index 7c6a0a7..ae9f3fb 100644 --- a/serverless_sim/.gitignore +++ b/serverless_sim/.gitignore @@ -3,4 +3,5 @@ Cargo.lock records* log module_conf_es.json -cache \ No newline at end of file +cache +azure-trace diff --git a/serverless_sim/module_conf_es.json b/serverless_sim/module_conf_es.json index 2eb7aba..625ae38 100644 --- a/serverless_sim/module_conf_es.json +++ b/serverless_sim/module_conf_es.json @@ -5,11 +5,12 @@ "scale_sche_joint": null }, "scale_num": { + "rela": null, + "hpa": null, "full_placement": null, + "ensure_scaler": null, "no": null, "lass": null, - "rela": null, - "hpa": null, "temp_scaler": null }, "scale_down_exec": { @@ -21,22 +22,24 @@ }, "sche": { "consistenthash": null, - "hash": null, - "bp_balance": null, - "random": null, - "greedy": null, + "ensure_scheduler": null, "faasflow": null, + "load_least": null, "rotate": null, - "pass": null, + "hash": null, + "pos": null, + "random": null, + "bp_balance": null, "fnsche": null, - "pos": null + "greedy": null, + "pass": null }, "filter": { "careful_down": null }, "instance_cache_policy": { - "no_evict": null, "lru": null, - "fifo": null + "fifo": null, + "no_evict": null } } \ No newline at end of file diff --git a/serverless_sim/src/fn_dag.rs b/serverless_sim/src/fn_dag.rs index 940b3c9..ff27c59 100644 --- a/serverless_sim/src/fn_dag.rs +++ b/serverless_sim/src/fn_dag.rs @@ -342,6 +342,13 @@ impl FnContainer { &self.state } + pub fn is_running(&self) -> bool { + match self.state { + FnContainerState::Running => true, + _ => false, + } + } + pub fn is_idle(&self) -> bool { match self.state { FnContainerState::Running => self.req_fn_state.len() == 0, @@ -448,15 +455,15 @@ impl SimEnv { // 检查配置中的dag_type if self.help.config().dag_type_dag() { - // 如果dag_type为dag，则创建6个具有多个子节点的复杂DAG实例 - for _ in 0..6 { + // 如果dag_type为dag，则创建 33 个具有多个子节点的复杂DAG实例 + for _ in 0..33 { // 随机确定每个图中节点的数量 let mapcnt = env.env_rand_i(2, 5); //2-4 let dag_i = env.core.dags().len(); // 创建一个复杂DAG实例 let dag = FnDAG::instance_map_reduce(dag_i, env, mapcnt); - log::info!("dag {} {:?}", dag.dag_i, dag.dag_inner); + // log::info!("dag {} {:?}", dag.dag_i, dag.dag_inner); env.core.dags_mut().push(dag); } @@ -475,8 +482,8 @@ impl SimEnv { // 跑指标2的实验用 self.help.config().dag_type_mix() { - for i in 0..10 { - if i >= 5 { + for i in 0..50 { + if i >= 20 { // 随机确定每个图中节点的数量 let mapcnt = env.env_rand_i(2, 5); //2-4 let dag_i = env.core.dags().len(); diff --git a/serverless_sim/src/main.rs b/serverless_sim/src/main.rs index 50ffc18..4f729d8 100644 --- a/serverless_sim/src/main.rs +++ b/serverless_sim/src/main.rs @@ -37,8 +37,8 @@ extern crate lazy_static; #[tokio::main] async fn main() { - let keyword: Vec<&'static str> = //vec![]; - vec!["::sche", "::mechanism ", "::scale"]; // no algo log + let keyword: Vec<&'static str> = vec![]; + // vec!["::sche", "::mechanism ", "::scale"]; // no algo log Builder::new() .filter(None, LevelFilter::Info) .format(move |buf, record| { diff --git a/serverless_sim/src/mechanism.rs b/serverless_sim/src/mechanism.rs index 87b99ac..9cc2c2d 100644 --- a/serverless_sim/src/mechanism.rs +++ b/serverless_sim/src/mechanism.rs @@ -78,7 +78,7 @@ impl CheckDup for Vec { } } -pub const SCHE_NAMES: [&'static str; 10] = [ +pub const SCHE_NAMES: [&'static str; 12] = [ "rotate", "hash", "bp_balance", @@ -89,16 +89,19 @@ pub const SCHE_NAMES: [&'static str; 10] = [ "random", "greedy", "consistenthash", // "gofs", + "ensure_scheduler", + "load_least", // "load_least", // "random", ]; -pub const SCALE_NUM_NAMES: [&'static str; 6] = [ +pub const SCALE_NUM_NAMES: [&'static str; 7] = [ "no", "hpa", "lass", "temp_scaler", "full_placement", "rela", + "ensure_scaler", ]; pub const SCALE_DOWN_EXEC_NAMES: [&'static str; 1] = ["default"]; pub const SCALE_UP_EXEC_NAMES: [&'static str; 2] = ["least_task", "no"]; @@ -181,7 +184,8 @@ impl ConfigNewMec for Config { "greedy", "consistenthash", "hash", - "rotate" + "rotate", + "load_least", ]; let allow_scale_num = vec!["no"]; let allow_scale_down_exec = vec!["default"]; @@ -200,7 +204,7 @@ impl ConfigNewMec for Config { } } "scale_sche_separated" => { - let allow_sche = vec!["random", "greedy", "hash", "rotate"]; + let allow_sche = vec!["random", "greedy", "hash", "rotate","load_least","pass"]; let allow_scale_num = vec!["hpa", "lass", "temp_scaler", "full_placement", "rela"]; let allow_scale_down_exec = vec!["default"]; let allow_scale_up_exec = vec!["least_task"]; @@ -218,8 +222,8 @@ impl ConfigNewMec for Config { } } "scale_sche_joint" => { - let allow_sche = vec!["pos", "bp_balance", "hash", "rotate"]; - let allow_scale_num = vec!["hpa", "lass", "temp_scaler", "full_placement", "rela"]; + let allow_sche = vec!["pos", "bp_balance", "ensure_scheduler"]; + let allow_scale_num = vec!["hpa", "lass", "temp_scaler", "full_placement", "rela", "ensure_scaler"]; let allow_scale_down_exec = vec!["default"]; let allow_scale_up_exec = vec!["least_task"]; if @@ -437,11 +441,11 @@ impl MechanismImpl { // let cur = env.fn_container_cnt(func.fn_id); // let tar = self.scale_num(func.fn_id); - log::info!( - "scale fn{} cost {}", - func.fn_id, - util::now_ms() - *self.step_begin.borrow() - ); + // log::info!( + // "scale fn{} cost {}", + // func.fn_id, + // util::now_ms() - *self.step_begin.borrow() + // ); // log::info!("scale fn {} from {} to {}", func.fn_id, cur, tar); // 不进行扩缩容，在调度时候一起进行 // log::info!("scale fn {} from {} to {}", func.fn_id, cur, tar); diff --git a/serverless_sim/src/mechanism_thread.rs b/serverless_sim/src/mechanism_thread.rs index 6772787..69bd5cc 100644 --- a/serverless_sim/src/mechanism_thread.rs +++ b/serverless_sim/src/mechanism_thread.rs @@ -1,5 +1,6 @@ use std::sync::mpsc; +use enum_as_inner::EnumAsInner; #[cfg(target_os = "windows")] use thread_priority::{set_current_thread_priority, ThreadPriority, WinAPIThreadPriority}; #[cfg(target_os = "windows")] diff --git a/serverless_sim/src/node.rs b/serverless_sim/src/node.rs index a643bec..f48da46 100644 --- a/serverless_sim/src/node.rs +++ b/serverless_sim/src/node.rs @@ -253,7 +253,7 @@ impl Node { pub fn try_load_container(&self, fnid: FnId, env: &SimEnv) { if self.container(fnid).is_some() { - log::info!("已经添加了{}", fnid); + // log::info!("已经添加了{}", fnid); return; } @@ -263,9 +263,9 @@ impl Node { fnid, Box::new(move |to_replace| { let node = node.as_ref(); - log::info!("节点{}要移除的容器{}", node.node_id, to_replace); + // log::info!("节点{}要移除的容器{}", node.node_id, to_replace); for (_k, v) in node.fn_containers.borrow().iter() { - log::info!("{}", v.fn_id); + // log::info!("{}", v.fn_id); } node.container(*to_replace).unwrap().is_idle() }), diff --git a/serverless_sim/src/real-world-emulation/CDFs/CVs.csv b/serverless_sim/src/real-world-emulation/CDFs/CVs.csv index 070743b..93c95da 100644 --- a/serverless_sim/src/real-world-emulation/CDFs/CVs.csv +++ b/serverless_sim/src/real-world-emulation/CDFs/CVs.csv @@ -1,17276 +1,3293 @@ 0.000000,0.226678 -0.001075,0.227163 -0.002025,0.227597 -0.003083,0.228260 -0.004065,0.229728 -0.005008,0.230514 -0.006054,0.232019 -0.007028,0.232695 -0.008108,0.234474 -0.009076,0.236148 -0.010001,0.237204 -0.011017,0.238557 -0.012002,0.238900 -0.013002,0.239673 -0.014043,0.240089 -0.015010,0.240770 -0.016025,0.245055 -0.017016,0.245343 -0.018001,0.248274 -0.019010,0.248800 -0.020000,0.249513 -0.021038,0.252311 -0.022019,0.252728 -0.023004,0.254598 -0.024017,0.254941 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b/serverless_sim/src/real-world-emulation/CDFs/IATCVCDFGenerator.py index 561fcfb..561def3 100644 --- a/serverless_sim/src/real-world-emulation/CDFs/IATCVCDFGenerator.py +++ b/serverless_sim/src/real-world-emulation/CDFs/IATCVCDFGenerator.py @@ -12,6 +12,7 @@ # We don't include Azure's dataset in our repo, so the file is just for reference # The dataset is open-source at https://github.com/Azure/AzurePublicDataset +import os import numpy as np ''' @@ -40,9 +41,10 @@ def getAppIATCV(filename): CVs = [] for invokeSeries in appInvokesDict.values(): IATSeries = getIATSeriesFromInvokeSeries(invokeSeries) + IATSeries_inv = list(map(lambda x: 1/x, IATSeries)) if IATSeries == []: continue - CVs.append(np.std(IATSeries) / np.mean(IATSeries)) + CVs.append(np.std(IATSeries_inv) / np.mean(IATSeries_inv)) return CVs diff --git a/serverless_sim/src/real-world-emulation/RealWorldAppEmulation.py b/serverless_sim/src/real-world-emulation/RealWorldAppEmulation.py index 8174a68..fd03572 100644 --- a/serverless_sim/src/real-world-emulation/RealWorldAppEmulation.py +++ b/serverless_sim/src/real-world-emulation/RealWorldAppEmulation.py @@ -34,11 +34,37 @@ SAMPLE_NUM = config['sample_number'] MANUAL_SAMPLE_GENERATION = config['manual_sample_generation'] +def compress_iat(iat): + # Parameters + offset = 0.0001 + lower_threshold = 1 + upper_threshold = 100 + max_value = 10 + + if iat < lower_threshold: + # Slightly adjust small values without increasing them too much + adjusted_iat = np.log1p(iat) / np.log(10) + elif iat >= lower_threshold and iat < upper_threshold: + # Linearly interpolate for values between lower and upper threshold + adjusted_iat = lower_threshold + (max_value - lower_threshold) * (iat - lower_threshold) / (upper_threshold - lower_threshold) + else: + # Compress larger values more significantly, but ensuring they don't exceed max_value + adjusted_iat = max_value - np.exp(-np.log(iat - lower_threshold + 1)) + + # Ensure the value does not go below the offset + compressed_iat = max(adjusted_iat, offset) + + return compressed_iat + # get random IAT according to the IAT csv def getRandAvgIAT(rng): IATCDFFile = os.path.join(os.path.dirname(__file__),'CDFs','invokesCDF.csv') invokeTime = utils.getRandValueRefByCDF(IATCDFFile, rng) IAT = invokeTime / SECONDS_OF_A_DAY + + # 让IAT经过一个激活函数，避免IAT过大，映射到10以内 + IAT = compress_iat(IAT) + return IAT # get random cv according to the CSV diff --git a/serverless_sim/src/request.rs b/serverless_sim/src/request.rs index 258200a..700b089 100644 --- a/serverless_sim/src/request.rs +++ b/serverless_sim/src/request.rs @@ -1,7 +1,4 @@ -use std::{ - cell::{Ref, RefMut}, - collections::{BTreeMap, HashMap, HashSet}, -}; +use std::{ cell::{ Ref, RefMut }, collections::{ BTreeMap, HashMap, HashSet }, thread::sleep, time::Duration }; use daggy::petgraph::visit::Topo; @@ -364,6 +361,12 @@ impl SimEnv { if env.help.config().request_freq_low() { avg_frequency *= 0.1; } + else if env.help.config().request_freq_middle() { + avg_frequency *= 0.2; + } + else { + avg_frequency *= 0.3; + } // avg_frequency *= 100.0; // avg_frequency *= 10.0; let mut bind = self.help.dag_accumulate_call_frequency.borrow_mut(); @@ -374,7 +377,6 @@ impl SimEnv { total_req_cnt += req_cnt; - // println!("DAG Index: {}, Avg Frequency: {}, CV: {}, Random Frequency: {}, Request Count: {}", dag_i, avg_frequency, cv, random_frequency, req_cnt); for _ in 0..req_cnt { let request = Request::new(env, *dag_i, env.core.current_frame()); diff --git a/serverless_sim/src/scale/num/ensure_scaler.rs b/serverless_sim/src/scale/num/ensure_scaler.rs new file mode 100644 index 0000000..a9eb642 --- /dev/null +++ b/serverless_sim/src/scale/num/ensure_scaler.rs @@ -0,0 +1,40 @@ + +use std::cell::{ RefCell }; +use std::collections::{ HashMap, VecDeque }; + +use crate::fn_dag::EnvFnExt; +use crate::mechanism::SimEnvObserve; +use crate::node::EnvNodeExt; +use crate::with_env_sub::{ WithEnvCore }; +use crate::{ actions::ESActionWrapper, fn_dag::FnId, CONTAINER_BASIC_MEM }; + +use super::{ down_filter::{ CarefulScaleDownFilter, ScaleFilter }, ScaleNum }; + +pub struct EnsureScaleNum {} + +impl EnsureScaleNum { + pub fn new() -> Self { + Self { + + } + } +} + +impl ScaleNum for EnsureScaleNum { + fn scale_for_fn(&mut self, env: &SimEnvObserve, fnid: FnId, _action: &ESActionWrapper) -> usize { + + // 当前容器数量 + let cur_container_cnt = env.fn_container_cnt(fnid); + + // 取cur_container_cnt的根号 + let sqrt_container_cnt = (cur_container_cnt as f64).sqrt().ceil() as usize; + + if cur_container_cnt + sqrt_container_cnt == 0 { + 1 + } + else { + cur_container_cnt + sqrt_container_cnt + } + + } +} diff --git a/serverless_sim/src/scale/num/mod.rs b/serverless_sim/src/scale/num/mod.rs index 925d53e..dd8b760 100644 --- a/serverless_sim/src/scale/num/mod.rs +++ b/serverless_sim/src/scale/num/mod.rs @@ -6,6 +6,7 @@ pub mod no; pub mod temp_scaler; pub mod full_placement; pub mod rela; +pub mod ensure_scaler; use crate::{ actions::ESActionWrapper, @@ -22,6 +23,7 @@ use self::{ temp_scaler::TempScaleNum, full_placement::FpScaleNum, rela::RelaScaleNum, + ensure_scaler::EnsureScaleNum, }; pub trait ScaleNum: Send { @@ -58,6 +60,9 @@ pub fn new_scale_num(c: &Config) -> Option> { "rela" => { return Some(Box::new(RelaScaleNum::new())); } + "ensure_scaler" => { + return Some(Box::new(EnsureScaleNum::new())); + } _ => { return None; } diff --git a/serverless_sim/src/scale/num/temp_scaler.rs b/serverless_sim/src/scale/num/temp_scaler.rs index d37bbce..453071e 100644 --- a/serverless_sim/src/scale/num/temp_scaler.rs +++ b/serverless_sim/src/scale/num/temp_scaler.rs @@ -291,6 +291,7 @@ impl ScaleNum for TempScaleNum { // 如果温度增量的绝对值大于温度变化感知阈值，则进行扩缩容决策 if temp_change.abs() > threshold { + // MARK 该增率的计算方式与论文中所写的不一致，后续有时间应该进一步实验测试对比一下现计算方式和论文中所写计算方式的优劣 // 计算容器数量的增率 let container_inc_rate = temp_change.abs() / threshold; @@ -319,6 +320,7 @@ impl ScaleNum for TempScaleNum { // 决策扩容 if temp_change > 0.0 { + // MARK 该增量的计算方式与论文中所写的不一致，后续有时间应该进一步实验测试对比一下现计算方式和论文中所写计算方式的优劣 // 根据温度增量计算容器数量的增量 let container_change = ( (fn_instance_cnt as f64) * @@ -384,10 +386,24 @@ impl ScaleNum for TempScaleNum { } // ---------------------------------------------------------------------------------------- - // 每个函数至少要有一个容器 - if desired_container_cnt == 0 { + // 先取出该函数的最后一次的调用时间 + let mut last_call_frame = 0; + match self.fn_call_history.get(&fnid).unwrap().borrow().back() { + Some(last_call)=>{ + last_call_frame = last_call.frame; + }, + None=>{ + } + } + + // 对于容器数量为0的函数，如果最后一次调用距离现在的长度小于历史调用窗口长度，则变为一个容器 + if desired_container_cnt == 0 && last_call_frame + self.call_history_window_len >= current_frame { desired_container_cnt = 1; } + // 对于容器数量是1的函数，如果最后一次调用距离现在的长度大于历史调用窗口长度，则缩容为0个容器 + else if desired_container_cnt == 1 && last_call_frame + self.call_history_window_len < current_frame { + desired_container_cnt = 0; + } // log::info!("函数:{}, 在第{}帧的目标容器数量为：{}.scale_for_fn()结束", fnid, current_frame, desired_container_cnt); diff --git a/serverless_sim/src/sche/bp_balance.rs b/serverless_sim/src/sche/bp_balance.rs index 8451103..a7a5728 100644 --- a/serverless_sim/src/sche/bp_balance.rs +++ b/serverless_sim/src/sche/bp_balance.rs @@ -1,232 +1,296 @@ -use std::{borrow::Borrow, collections::{HashMap, HashSet}, vec}; +use core::alloc; +use std::{borrow::Borrow, cell::Ref, collections::{HashMap, HashSet}, env, thread::{self, panicking, sleep}, time::Duration, vec}; use crate::{ - fn_dag::{EnvFnExt, FnId}, mechanism::{DownCmd, MechanismImpl, ScheCmd, SimEnvObserve}, mechanism_thread::{MechCmdDistributor, MechScheduleOnceRes}, node::{EnvNodeExt, NodeId}, request::Request, sim_run::{schedule_helper, Scheduler}, with_env_sub::{WithEnvCore, WithEnvHelp} + fn_dag::{EnvFnExt, FnContainerState, FnId, RunningTask}, mechanism::{DownCmd, MechanismImpl, ScheCmd, SimEnvObserve}, mechanism_thread::{MechCmdDistributor, MechScheduleOnceRes}, node::{self, EnvNodeExt, NodeId}, request::Request, sim_run::{schedule_helper, Scheduler}, with_env_sub::{WithEnvCore, WithEnvHelp} }; -struct bplistStatues{ - avg_cpu_use_rate: f32, +const CPU_THRESHOLD_TO_ADD: f32 = 1.0; +const CPU_THRESHOLD_TO_REMOVE: f32 = 0.7; +const MEM_THRESHOLD_TO_ADD: f32 = 0.9; + +// 维护 bp 数组用 +struct BpListUpdateNodes{ + // 平均cpu利用率 + avg_cpu_starve_degree: f32, + + // 平均mem利用率 avg_mem_use_rate: f32, - max_idle_nodeid_inbp: usize, - max_idle_nodeid_unbp: usize, -} -impl bplistStatues { - pub fn new(avg_cpu_use_rate: f32, avg_mem_use_rate: f32, max_idle_nodeid_inbp: usize, max_idle_nodeid_unbp: usize) -> Self { - Self { - avg_cpu_use_rate, - avg_mem_use_rate, - max_idle_nodeid_inbp, - max_idle_nodeid_unbp, - } - } + // binpack内饥饿程度最高的节点 + expel_nodeid_inbp: usize, + + // binpack外资源得分最高的节点 + join_nodeid_outbp: usize, } struct NodeRescState { mem_used: f32, mem_limit: f32, -} + cpu_limit: f32, -impl NodeRescState { - pub fn new(mem_used: f32, mem_limit: f32) -> Self { - Self { - mem_used, - mem_limit, - } - } + // 资源得分 + resource_score: f32, + + // 所有任务数量 + all_task_cnt: f32, } pub struct BpBalanceScheduler { // 每个函数的binpack节点集合 - fn_binpack_map: HashMap>, + binpack_map: HashMap>, // 每个函数的最新节点集合 - fn_latest_nodes: HashMap>, + latest_nodes: HashMap>, - // MARK 这个还没初始化的 - // 每个节点的资源使用情况，实时更新 + // 每个节点的资源使用情况，实时更新---调度时需要实时更新 nodes_resc_state: HashMap, + + // 判断函数是否可以开始用bp_balance数组机制 + mech_impl_sign: HashMap, + + // 需要调度的函数集合 + need_schedule_fn: HashSet, } impl BpBalanceScheduler { pub fn new() -> Self { Self { - fn_binpack_map: HashMap::new(), - fn_latest_nodes: HashMap::new(), + binpack_map: HashMap::new(), + latest_nodes: HashMap::new(), nodes_resc_state: HashMap::new(), + mech_impl_sign: HashMap::new(), + need_schedule_fn: HashSet::new(), } } - // 找出binpack数组中空闲内存率最高的节点 - fn find_max_idle_nodeid(&self, fnid: FnId, _env: &SimEnvObserve) -> usize{ - // BUG 当binpack为空时，会返回9999，导致调度失败 - let mut max_idle_nodeid: usize = 9999; - let binpack = self.fn_binpack_map.get(&fnid).unwrap(); - - for nodeid in binpack { - - if max_idle_nodeid == 9999 { - max_idle_nodeid = *nodeid; + // 找出binpack数组中 最合适的点(取决于贪婪的指标是什么) 的节点、并且要内存足够才行 + fn find_schedule_nodeid(&self, fnid: FnId, env: &SimEnvObserve) -> usize{ + let mut schedule_node_id: usize = 9999; + let mut best_node_metric = 0.0; + let bplist = self.binpack_map.get(&fnid).unwrap(); + + // 遍历所有容器的资源状态 + for node_id in bplist { + let iter_node_resource_status = self.nodes_resc_state.get(node_id).unwrap(); + + // 找出 饥饿程度 最小的 + let iter_node_starve_degree = self.cal_cpu_starve_degree(iter_node_resource_status, fnid, env); + if schedule_node_id == 9999{ + schedule_node_id = *node_id; + best_node_metric = iter_node_starve_degree; } else { - // 取出当前遍历节点的资源使用情况 - let iter_node_resc_state = self.nodes_resc_state.get(&nodeid).unwrap(); - // 取出目前最大空闲节点的资源状态 - let max_node_resc_state = self.nodes_resc_state.get(&max_idle_nodeid).unwrap(); - - // 计算资源空闲率 - let this_node_idle = 1.0 - iter_node_resc_state.mem_used / iter_node_resc_state.mem_limit; - let max_node_idle = 1.0 - max_node_resc_state.mem_used / max_node_resc_state.mem_limit; - if this_node_idle > max_node_idle { - max_idle_nodeid = *nodeid; + // 比较出 饥饿程度 最小的节点 + if iter_node_starve_degree < best_node_metric { + schedule_node_id = *node_id; + best_node_metric = iter_node_starve_degree; } } + + // // 找出 待处理任务数量 最小的节点 + // if schedule_node_id == 9999{ + // schedule_node_id = *node_id; + // best_node_metric = iter_node_resource_status.all_task_cnt; + // } + // else { + // // 比较出 待处理任务数量 最小的节点 + // if iter_node_resource_status.all_task_cnt < best_node_metric { + // schedule_node_id = *node_id; + // best_node_metric = iter_node_resource_status.all_task_cnt; + // } + // } + } - max_idle_nodeid + + schedule_node_id } + + // 计算函数分配到节点上后，cpu饥饿程度 = fn_cpu_use / cpu_local + fn cal_cpu_starve_degree(&self, node_resc_state: &NodeRescState, fnid: FnId, env: &SimEnvObserve)->f32{ + // 先取出该函数所需要的cpu + let fn_cpu_use = env.func(fnid).cpu; - // TODO 也要计算cpu，计算指定函数binpack数组内的资源利用率，以及得出其内、其外的空闲资源最多的节点id - fn get_bplist_status(&self, fnid: FnId, env: &SimEnvObserve) -> bplistStatues{ + let cpu_local = node_resc_state.cpu_limit / (node_resc_state.all_task_cnt + 1.0); + + return fn_cpu_use / cpu_local; + } + + // 获得数据，维护 bp 数组 + fn get_bplist_node_status(&self, fnid: FnId, env: &SimEnvObserve) -> BpListUpdateNodes{ - let binpack = self.fn_binpack_map.get(&fnid).unwrap(); + let binpack = self.binpack_map.get(&fnid).unwrap(); + + assert!(binpack.len() != 0 && self.latest_nodes.get(&fnid).unwrap().len() != 0); - // binpack内节点的平均mem、cpu利用率 + let mut avg_cpu_starve_degree = 0.0; let mut avg_mem_use_rate = 0.0; - let mut avg_cpu_use_rate = 0.0; - let mut bplist_have_container = 0; + let mut max_starve_nodeid_inbp = 9999; + let mut max_score_nodeid_outbp = 9999; - // binpack内或外最空闲的节点 - let mut max_idle_nodeid_inbp = 9999; - let mut max_idle_nodeid_unbp = 9999; + let mut max_starve_degree = 1.0; + let mut max_resource_score = 0.0; // 遍历该函数的可执行节点集合 - for nodeid in self.fn_latest_nodes.get(&fnid).unwrap().iter() { + for nodeid in self.latest_nodes.get(&fnid).unwrap().iter() { // 取出当前节点的资源使用情况 let iter_node_resc_state = self.nodes_resc_state.get(&nodeid).unwrap(); - // binpack内最空闲的节点,同时计算平均mem、cpu利用率 + // 找到binpack内饥饿程度最高的节点、binpack外资源得分最高的节点,同时计算bp内平均mem利用率、cpu饥饿程度 if binpack.contains(nodeid){ - // 统计binpack内节点的平均资源利用率 + // 统计binpack内节点的平均mem利用率 avg_mem_use_rate += iter_node_resc_state.mem_used / iter_node_resc_state.mem_limit; - // BUG 第一帧的时候，实际上还没有容器，这时候取cpu_use_rate会报错 - // 取出这个节点内该函数的容器的cpu利用率 - if env.node(*nodeid).container(fnid).is_some() { - avg_cpu_use_rate += env.node(*nodeid).container(fnid).unwrap().borrow().cpu_use_rate(); - bplist_have_container += 1; - } + let cpu_starve_degree = self.cal_cpu_starve_degree(iter_node_resc_state, fnid, env); + // 统计bp数组内的节点的平均cpu饥饿程度 + avg_cpu_starve_degree += cpu_starve_degree; - if max_idle_nodeid_inbp == 9999{ - max_idle_nodeid_inbp = *nodeid; + // 计算binpack内，针对于该函数容器的饥饿程度最高的节点 + if max_starve_nodeid_inbp == 9999{ + max_starve_nodeid_inbp = *nodeid; + max_starve_degree = cpu_starve_degree; } else { - // 取出目前最大空闲节点的资源状态 - let max_node_resc_state = self.nodes_resc_state.get(&max_idle_nodeid_inbp).unwrap(); - - // 计算资源空闲率 - let iter_nodeid_idle = 1.0 - iter_node_resc_state.mem_used / iter_node_resc_state.mem_limit; - let max_nodeid_idle = 1.0 - max_node_resc_state.mem_used / max_node_resc_state.mem_limit; - - if iter_nodeid_idle > max_nodeid_idle { - max_idle_nodeid_inbp = *nodeid; + // 取出目前最饥饿节点的资源状态 + if cpu_starve_degree > max_starve_degree { + max_starve_nodeid_inbp = *nodeid; + max_starve_degree = cpu_starve_degree; } } } - // binpack外最空闲的节点 + // binpack外资源得分最高的节点。资源得分 = 1.0 / (1.0 + 任务数 + 内存使用率) else { - if max_idle_nodeid_unbp == 9999{ - max_idle_nodeid_unbp = *nodeid; + if max_score_nodeid_outbp == 9999{ + max_score_nodeid_outbp = *nodeid; + max_resource_score = iter_node_resc_state.resource_score; } else { - // 取出目前最大空闲节点的资源状态 - let max_node_resc_state = self.nodes_resc_state.get(&max_idle_nodeid_unbp).unwrap(); - - let iter_nodeid_idle = 1.0 - iter_node_resc_state.mem_used / iter_node_resc_state.mem_limit; - let max_nodeid_idle = 1.0 - max_node_resc_state.mem_used / max_node_resc_state.mem_limit; - - if iter_nodeid_idle > max_nodeid_idle { - max_idle_nodeid_unbp = *nodeid + // 取出目前得分最高节点的资源状态 + if iter_node_resc_state.resource_score > max_resource_score { + max_score_nodeid_outbp = *nodeid; + max_resource_score = iter_node_resc_state.resource_score; } } } - - } // 计算平均 avg_mem_use_rate /= binpack.len() as f32; + avg_cpu_starve_degree /= binpack.len() as f32; - if bplist_have_container != 0 { - avg_cpu_use_rate /= bplist_have_container as f32; - } + // 把平均cpu饥饿程度打在日志上 + log::info!("func_id: {}, avg_cpu_starve_degree: {}, avg_mem_use_rate: {}", fnid, avg_cpu_starve_degree, avg_mem_use_rate); + log::info!("func_id: {}, max_starve_nodeid_inbp: {}, max_score_nodeid_outbp: {}", fnid, max_starve_nodeid_inbp, max_score_nodeid_outbp); - bplistStatues{ + BpListUpdateNodes{ + avg_cpu_starve_degree, avg_mem_use_rate, - avg_cpu_use_rate, - max_idle_nodeid_inbp, - max_idle_nodeid_unbp + expel_nodeid_inbp: max_starve_nodeid_inbp, + join_nodeid_outbp: max_score_nodeid_outbp, } } - + + // 对 bp数组进行更新，因为对 bp 数组的更新都要伴随着对 fn_container_cpu_status 的更新，所以放在一个函数以便两者同时进行 + fn update_bplist(&mut self, fnid: FnId, node_id: NodeId, operate: &str, _env: &SimEnvObserve){ + let fn_binpack_map = self.binpack_map.get_mut(&fnid).unwrap(); + if operate == "add" { + // 对 binpack 进行更新 + fn_binpack_map.insert(node_id); + } + // 如果是 remove 操作，则移除该节点的状态 + else if operate == "remove" { + // 对 binpack 进行更新 + fn_binpack_map.remove(&node_id); + } + else { + panic!("operate: {} not supported", operate); + } + } + + // 调度之后的资源情况需要更新 fn schedule_one_req_fns( &mut self, - env: &SimEnvObserve, + env: &SimEnvObserve, + mech: &MechanismImpl, req: &mut Request, cmd_distributor: &MechCmdDistributor, ) { // 收集该请求中所有可以调度的函数 - let mut schedule_able_fns = schedule_helper::collect_task_to_sche( + let schedule_able_fns = schedule_helper::collect_task_to_sche( req, env, schedule_helper::CollectTaskConfig::PreAllSched, ); - // 对所有函数进行优先级排序，cpu需求较大的在前面 - schedule_able_fns.sort_by(|&a, &b| { - env.func(a) - .cpu - .partial_cmp(&env.func(b).cpu) - .unwrap() - .reverse() - }); - - // 进行调度，每次函数请求到达时，往binpack数组中空闲内存最多的节点上调度，并实时更新节点容量。 - // let mut sche_cmds = vec![]; let mech_metric = || env.help().mech_metric_mut(); + let scale_up_exec = mech.scale_up_exec(); for &fnid in &schedule_able_fns { - // 找出该函数的binpack数组中空闲内存最多的节点 - let sche_nodeid = self.find_max_idle_nodeid(fnid, env); - mech_metric().add_node_task_new_cnt(sche_nodeid); + let mut target_cnt = mech.scale_num(fnid); + if target_cnt == 0 { + target_cnt = 1; + } + + let fn_scale_up_cmds = scale_up_exec.exec_scale_up( + target_cnt, + fnid, + env, + cmd_distributor + ); + for cmd in fn_scale_up_cmds.iter() { + self.latest_nodes.get_mut(&fnid).unwrap().insert(cmd.nid); + self.binpack_map.get_mut(&fnid).unwrap().insert(cmd.nid); + } + + + if self.binpack_map.get(&fnid).unwrap().len() == 0 { + panic!("fnid:{}, last_nodes_len:{}", fnid, self.latest_nodes.get(&fnid).unwrap().len()); + } + + // 找到调度节点 + let sche_nodeid = self.find_schedule_nodeid(fnid, env); - cmd_distributor - .send(MechScheduleOnceRes::ScheCmd(ScheCmd { - reqid: req.req_id, - fnid, - nid: sche_nodeid, - memlimit: None, - })) - .unwrap(); + if sche_nodeid != 9999 { - // 更新node_resc_state中的节点容量 - self.nodes_resc_state.get_mut(&sche_nodeid).unwrap().mem_used += env.func(fnid).mem; + mech_metric().add_node_task_new_cnt(sche_nodeid); + cmd_distributor + .send(MechScheduleOnceRes::ScheCmd(ScheCmd { + reqid: req.req_id, + fnid, + nid: sche_nodeid, + memlimit: None, + })) + .unwrap(); - // 计算该函数binpack数组内的资源利用率，以及得出其外的空闲资源最多的节点id - let bplist_status = self.get_bplist_status(fnid, env); + // 更新node_resc_state中的资源使用情况：mem_used, cpu_left_calc, cpu_starve_degree, resource_score + let sche_node_resc_state = self.nodes_resc_state.get_mut(&sche_nodeid).unwrap(); + + sche_node_resc_state.mem_used += env.func(fnid).mem; + sche_node_resc_state.all_task_cnt += 1.0; + sche_node_resc_state.resource_score = 1.0 / (1.0 + sche_node_resc_state.all_task_cnt + sche_node_resc_state.mem_used / sche_node_resc_state.mem_limit); + + // 只有当机制触发的时候才扩容binpack数组 + if self.mech_impl_sign.get(&fnid).unwrap() == &true { + // 计算该函数binpack数组的资源情况 + let bplist_resource_status = self.get_bplist_node_status(fnid, env); + + // 如果binpack内平均资源利用率大于所设阈值，则将含有该函数对应容器快照的目前空余资源量最多的节点加入该binpack数组 + if (bplist_resource_status.avg_mem_use_rate > MEM_THRESHOLD_TO_ADD || bplist_resource_status.avg_cpu_starve_degree > CPU_THRESHOLD_TO_ADD) && bplist_resource_status.join_nodeid_outbp != 9999 { + self.update_bplist(fnid, bplist_resource_status.join_nodeid_outbp, "add", env); + } + } - // 如果binpack内平均资源利用率大于所设阈值，则将含有该函数对应容器快照的目前空余资源量最多的节点加入该binpack数组 - if (bplist_status.avg_mem_use_rate > 0.8 || bplist_status.avg_cpu_use_rate > 0.9) && bplist_status.max_idle_nodeid_unbp != 9999{ - self.fn_binpack_map.get_mut(&fnid).unwrap().insert(bplist_status.max_idle_nodeid_unbp); } } } + } impl Scheduler for BpBalanceScheduler { @@ -236,168 +300,241 @@ impl Scheduler for BpBalanceScheduler { mech: &MechanismImpl, cmd_distributor: &MechCmdDistributor,){ - let mut up_cmds = vec![]; - // let mut sche_cmds = vec![]; - let mut down_cmds = vec![]; - // 遍历每个节点，更新其资源使用情况 for node in env.core().nodes().iter() { + // 内存 let mem_used = env.node(node.node_id()).last_frame_mem; let mem_limit = env.node(node.node_id()).rsc_limit.mem; - self.nodes_resc_state.insert(node.node_id(), NodeRescState::new(mem_used, mem_limit)); + // cpu + let cpu_limit = env.node(node.node_id()).rsc_limit.cpu; + + // 任务数量 + let all_task_cnt = node.all_task_cnt() as f32; + + // 资源得分，资源得分 = 1.0 / (1.0 + 任务数 + 内存使用率) + let resource_score = 1.0 / (1.0 + all_task_cnt + mem_used / mem_limit); + self.nodes_resc_state.insert(node.node_id(), + NodeRescState + { + mem_used, mem_limit, cpu_limit, resource_score, all_task_cnt, + } + ); + } + self.need_schedule_fn.clear(); + // 找到这一帧需要调度的函数 + for (_req_id, req) in env.core().requests_mut().iter_mut() { + let schedule_able_fns = schedule_helper::collect_task_to_sche( + req, + env, + schedule_helper::CollectTaskConfig::PreAllSched, + ); + for fnid in schedule_able_fns.iter() { + self.need_schedule_fn.insert(*fnid); + } } - // 遍历每个函数，为其获取扩缩容命令，维护一个binpack节点数组和一个可执行节点数组 + // 遍历每个函数，为其获取扩缩容命令，维护 binpack 数组 for func in env.core().fns().iter() { + // 初始化每个函数的 bp 数组 + if !self.binpack_map.contains_key(&func.fn_id){ + self.binpack_map.insert(func.fn_id, HashSet::new()); + } - // 进行其他处理之前，先更新最新节点集合 - let mut nodes = HashSet::new(); - env.fn_containers_for_each(func.fn_id, |container| { - nodes.insert(container.node_id); - }); - - // 根据 scaler 得出的容器数量进行扩容 - let mut target = mech.scale_num(func.fn_id); - if target == 0 { - target = 1; + // 初始化每个函数的 latest_nodes 数组 + if !self.latest_nodes.contains_key(&func.fn_id){ + self.latest_nodes.insert(func.fn_id, HashSet::new()); + } + + // 初始化每个函数的 mech_impl_sign + if !self.mech_impl_sign.contains_key(&func.fn_id){ + self.mech_impl_sign.insert(func.fn_id, false); } - let cur = env.fn_container_cnt(func.fn_id); - // 如果当前容器数量少于目标数量，则进行扩容 - if target > cur { - let up_cmd = mech.scale_up_exec().exec_scale_up(target, func.fn_id, env, cmd_distributor); - up_cmds.extend(up_cmd.clone()); - // 实时更新函数的节点情况、新扩容的容器数量直接放入binpack数组中 + // 进行其他处理之前，先更新最新节点集合 + // let mut nodes = HashSet::new(); + // env.fn_containers_for_each(func.fn_id, |container| { + // nodes.insert(container.node_id); + // }); + let mut nodes = env + .core().fn_2_nodes() + .get(&func.fn_id) + .map(|v| { v.clone() }) + .unwrap_or(HashSet::new()); + + + // 根据 scaler 得出的容器数量进行扩缩容-------------------------------------------------------------------- + let mut scale_down_sign = false; + let target = mech.scale_num(func.fn_id); + let cur = env.fn_container_cnt(func.fn_id); + if target > cur && self.need_schedule_fn.contains(&func.fn_id){ + let up_cmd = mech.scale_up_exec().exec_scale_up( + target, + func.fn_id, env, + cmd_distributor + ); + + // 实时更新函数的节点情况 for cmd in up_cmd.iter() { nodes.insert(cmd.nid); + self.binpack_map.get_mut(&func.fn_id).unwrap().insert(cmd.nid); + } + } + // 如果需要缩容 + else if target < cur && (cur != 1 || !self.need_schedule_fn.contains(&func.fn_id)) { + // 标记可以开始bp机制 + if self.mech_impl_sign.get(&func.fn_id).unwrap() == &false { + log::info!("fn_id: {}, 在第 {} 帧触发机制", func.fn_id, env.core().current_frame()); + } + // MARK 注释下面这行，可以关闭bp机制，此时变成贪婪调度 + self.mech_impl_sign.insert(func.fn_id, true); + + // 进行缩容 + let down_cmd = mech.scale_down_exec().exec_scale_down( + env, + func.fn_id, + cur - target, + cmd_distributor + ); + + // 实时更新函数的节点情况 + for cmd in down_cmd.iter() { + nodes.remove(&cmd.nid); + } + + // 如果有缩容命令，则标记 scale_down_sign 为 true + if down_cmd.len() != 0 { + scale_down_sign = true; } } + // --------------------------------------------------------------------------------------------------------------------------- + + // 机制没有触发，则该函数的bp数组就是nodes + if !*self.mech_impl_sign.get(&func.fn_id).unwrap(){ + // log::info!("fn_id: {}, frame:{}, 机制没有触发", func.fn_id, env.core().current_frame()); + // 该函数的可调度节点和最新节点集合就是nodes + self.latest_nodes.insert(func.fn_id, nodes.clone()); + self.binpack_map.insert(func.fn_id, nodes.clone()); + } + // 如果bp机制触发，则开始维护该函数的bp数组 + else { + // 清理一下binpack数组中被意外缩容的节点，一般不会出现这个情况 + let binpack_nodeids = self.binpack_map.get(&func.fn_id).unwrap().clone(); + for nodeid in binpack_nodeids.iter() { + if !nodes.contains(nodeid) { + self.update_bplist(func.fn_id, *nodeid, "remove", env); + log::info!("fnid:{}, 节点{}被意外缩容, 移除后binpack_len:{}", func.fn_id, nodeid, self.binpack_map.get(&func.fn_id).unwrap().len()); + log::info!("nodes.len():{}", nodes.len()); + } + } - // MARK 试一下所有节点都放binpack数组中的情况 - // 如果函数有binpack数组，则再进行超时缩容，并维护该 binpack 数组 - if self.fn_binpack_map.contains_key(&func.fn_id){ - // 获得节点总数和binpack数组 - let binpack = self.fn_binpack_map.get(&func.fn_id).unwrap(); + let binpack = self.binpack_map.get(&func.fn_id).unwrap(); + // 该函数没有可调度节点，表示该函数最近一直没有请求，直接跳过 + if nodes.len() == 0 { + self.latest_nodes.insert(func.fn_id, nodes.clone()); + assert!(binpack.len() == 0); + continue; + } + + // 重新拿一次，避免借用冲突 + let binpack = self.binpack_map.get(&func.fn_id).unwrap(); - // 遍历每个容器，对binpack数组外的容器进行超时缩容 - env.fn_containers_for_each(func.fn_id, |container| { + // 如果扩缩容器没有缩容，那么遍历每个容器，对binpack数组外的容器进行超时缩容------------------------------------------ + if scale_down_sign == false { + env.fn_containers_for_each(func.fn_id, |container| { - // TODO 添加CPU资源监控后这里应该修改逻辑，不需要节点总数大于1.5倍才缩容 - // 如果当前节点总数比binpack数组多，对于不是binpack数组中的节点，进行超时缩容 - if nodes.len() > binpack.len() + 1 && !binpack.contains(&container.node_id) { - // if nodes.len() > (binpack.len() as f32 * 1.5).ceil() as usize && !binpack.contains(&container.node_id) { - - // 如果最近20帧都是空闲，且没有请求 - if container.recent_frame_is_idle(20) && container.req_fn_state.len() == 0 { - down_cmds.push( - DownCmd { - nid: container.node_id, - fnid: func.fn_id} - ); - - nodes.remove(&container.node_id); + // 对于不是binpack数组中的节点，进行超时缩容 + if !binpack.contains(&container.node_id) { + + // 如果该容器最近50帧都是空闲则缩容 + if container.recent_frame_is_idle(50) && container.req_fn_state.len() == 0 { + + // 发送缩容命令 + cmd_distributor + .send(MechScheduleOnceRes::ScaleDownCmd(DownCmd + { + nid: container.node_id, + fnid: func.fn_id + } + )) + .unwrap(); + + nodes.remove(&container.node_id); + } } - } - - }); - // ----------------------超时缩容完成 + + }); + } + // 超时缩容完成---------------------------------------------------------------------------------------- - // 更新最新节点集合 - self.fn_latest_nodes.insert(func.fn_id, nodes.clone()); + // 到这里来的时候nodes集合一定不为空 + assert!(nodes.len() != 0); - // ----------------------对 binpack 数组进行维护 - let binpack = self.fn_binpack_map.get_mut(&func.fn_id).unwrap(); + // 更新该函数的最新可调度节点集合 + self.latest_nodes.insert(func.fn_id, nodes.clone()); - // 清理一下binpack数组中被意外缩容的节点，一般不会出现这个情况 - let binpack_nodeids = binpack.clone(); - for nodeid in binpack_nodeids.iter() { - if !nodes.contains(nodeid) { - binpack.remove(nodeid); - } - } + // 对 binpack 数组进行维护---------------------------------------------------------------------------------------- + let binpack = self.binpack_map.get(&func.fn_id).unwrap(); - // 当binpack数组为空时（正常运行的话不会是空的），把所有节点都加进去 + // 当binpack数组为空时，把所有节点都加进去 if binpack.len() == 0 { - self.fn_binpack_map.insert(func.fn_id, nodes.clone()); + self.binpack_map.insert(func.fn_id, nodes.clone()); + assert!(self.binpack_map.get(&func.fn_id).unwrap().len() != 0); } // 计算该函数binpack数组内的资源利用率，以及得出其内、其外的空闲资源最多的节点id - let mut bplist_status = self.get_bplist_status(func.fn_id, env); + let mut bplist_resource_status = self.get_bplist_node_status(func.fn_id, env); - // TODO 更改维护数组的逻辑，增加对cpu利用率的调控 - // 维护binpack数组，直到其数组内资源利用率在50%到80%之间 - while bplist_status.avg_mem_use_rate < 0.5 && (bplist_status.avg_mem_use_rate > 0.8 || bplist_status.avg_cpu_use_rate > 0.9) { - - let binpack = self.fn_binpack_map.get_mut(&func.fn_id).unwrap(); + // 维护binpack数组 + while bplist_resource_status.avg_cpu_starve_degree < CPU_THRESHOLD_TO_REMOVE || bplist_resource_status.avg_mem_use_rate > MEM_THRESHOLD_TO_ADD || bplist_resource_status.avg_cpu_starve_degree > CPU_THRESHOLD_TO_ADD { + + let binpack = self.binpack_map.get(&func.fn_id).unwrap(); - // 空数组或者已经没有外部可添加节点了 - if binpack.len() == 0 || bplist_status.max_idle_nodeid_unbp == 9999 { + assert!(bplist_resource_status.avg_cpu_starve_degree != 0.0); + + // 退出循环逻辑 + if bplist_resource_status.avg_cpu_starve_degree < CPU_THRESHOLD_TO_REMOVE && binpack.len() == 1{ + break; + } + if (bplist_resource_status.avg_mem_use_rate > MEM_THRESHOLD_TO_ADD || bplist_resource_status.avg_cpu_starve_degree > CPU_THRESHOLD_TO_ADD) && bplist_resource_status.join_nodeid_outbp == 9999 { break; } - // 如果binpack内平均资源利用率小于50%，则逐出数组中资源利用率最低的元素，但是至少要有一个节点 - if bplist_status.avg_mem_use_rate < 0.5 && bplist_status.max_idle_nodeid_inbp != 9999 && binpack.len() > 1{ - - // 预计逐出后的平均资源利用率 - let mut new_mem_util = 0.0; - let mut new_cpu_util = 0.0; - for nodeid in binpack.iter() { - if *nodeid != bplist_status.max_idle_nodeid_inbp { - let node_resc_state = self.nodes_resc_state.get(&nodeid).unwrap(); - new_mem_util += node_resc_state.mem_used / node_resc_state.mem_limit; - new_cpu_util += env.node(*nodeid).container(func.fn_id).unwrap().borrow().cpu_use_rate(); - } - } - // 计算逐出后的平均利用率 - new_mem_util /= (binpack.len() - 1) as f32; - new_cpu_util /= (binpack.len() - 1) as f32; - - // 确保逐出后平均利用率依然在阈值之内 - if new_mem_util < 0.8 && new_cpu_util < 0.9 { - binpack.remove(&bplist_status.max_idle_nodeid_inbp); - } - + // 如果binpack内平均cpu饥饿程度小于0.5，则逐出数组中饥饿程度最高的节点 + if bplist_resource_status.avg_cpu_starve_degree < CPU_THRESHOLD_TO_REMOVE && bplist_resource_status.expel_nodeid_inbp != 9999 { + // log::info!("fnid:{}, avg_cpu_starve_degree:{}, expel_nodeid_inbp:{}", func.fn_id, bplist_resource_status.avg_cpu_starve_degree, bplist_resource_status.expel_nodeid_inbp); + self.update_bplist(func.fn_id, bplist_resource_status.expel_nodeid_inbp, "remove", env); + // log::info!("fnid:{}, 节点{}被逐出binpack, 剩余binpack_len:{}", func.fn_id, bplist_resource_status.expel_nodeid_inbp, self.binpack_map.get(&func.fn_id).unwrap().len()); + break; } - // 如果binpack内平均资源利用率大于80%，则将含有该函数对应容器快照的目前空余资源量最多的节点加入该binpack数组 - else if (bplist_status.avg_mem_use_rate > 0.8 || bplist_status.avg_cpu_use_rate > 0.9) && bplist_status.max_idle_nodeid_unbp != 9999 { - binpack.insert(bplist_status.max_idle_nodeid_unbp); + // 如果binpack内平均mem利用率大于80%或平均饥饿程度大于0.9，则将bp数组外资源得分最高的节点加入该binpack数组 + else if (bplist_resource_status.avg_mem_use_rate > MEM_THRESHOLD_TO_ADD || bplist_resource_status.avg_cpu_starve_degree > CPU_THRESHOLD_TO_ADD) && bplist_resource_status.join_nodeid_outbp != 9999 { + self.update_bplist(func.fn_id, bplist_resource_status.join_nodeid_outbp, "add", env); } + // log::info!("bplist长度:{}, nodes长度:{}", self.binpack_map.get(&func.fn_id).unwrap().len(), self.latest_nodes.get(&func.fn_id).unwrap().len()); + // 再次计算 - bplist_status = self.get_bplist_status(func.fn_id, env); + bplist_resource_status = self.get_bplist_node_status(func.fn_id, env); } // 为了防止借用冲突 - let binpack = self.fn_binpack_map.get_mut(&func.fn_id).unwrap(); + let binpack = self.binpack_map.get(&func.fn_id).unwrap(); - log::info!("fnid:{}, binpack_len:{}, latest_nodes_len:{}", func.fn_id, binpack.len(), self.fn_latest_nodes.get(&func.fn_id).unwrap().len()); + log::info!("fnid:{}, binpack_len:{}, latest_nodes_len:{}", func.fn_id, binpack.len(), self.latest_nodes.get(&func.fn_id).unwrap().len()); } - // 如果函数没有binpack数组，则初始化，把该函数的所有可执行节点加入该数组 - else{ - // 更新最新节点集合 - self.fn_latest_nodes.insert(func.fn_id, nodes.clone()); - self.fn_binpack_map.insert(func.fn_id, nodes.clone()); - } + + // 每20帧，等待100ms。看长度情况 - // self.fn_latest_nodes.insert(func.fn_id, nodes.clone()); - // self.fn_binpack_map.insert(func.fn_id, nodes.clone()); - - // // 每20帧，等待100ms。看长度情况 - // if *env.core.current_frame() % 10 == 0 { - // let a_millis = 50; - // let wait_duration = Duration::from_millis(a_millis); - // // 让当前线程暂停指定的持续时间 - // thread::sleep(wait_duration); - // } + // 每帧要更新一次 container_cpu_status_bp } // 遍历调度每个请求 for (_req_id, req) in env.core().requests_mut().iter_mut() { - self.schedule_one_req_fns(env, req, cmd_distributor); + self.schedule_one_req_fns(env, mech, req, cmd_distributor); } - // (up_cmds, sche_cmds, down_cmds) } -} \ No newline at end of file +} + diff --git a/serverless_sim/src/sche/ensure_scheduler.rs b/serverless_sim/src/sche/ensure_scheduler.rs new file mode 100644 index 0000000..7e0d703 --- /dev/null +++ b/serverless_sim/src/sche/ensure_scheduler.rs @@ -0,0 +1,172 @@ +use std::{ + cmp::Ordering, + collections::{HashMap, HashSet}, +}; + +use crate::{ + fn_dag::{EnvFnExt, FnId}, + mechanism::{DownCmd, MechType, MechanismImpl, ScheCmd, SimEnvObserve}, + mechanism_thread::{MechCmdDistributor, MechScheduleOnceRes}, + node::{self, EnvNodeExt, Node, NodeId}, + sim_run::{schedule_helper, Scheduler}, + with_env_sub::WithEnvCore, +}; + +struct NodeCpuResc { + cpu_limit: f32, + all_task_cnt: f32, +} + +pub struct EnsureScheduler { + fn_nodes: HashMap>, + node_cpu_usage: HashMap, +} + +impl EnsureScheduler { + pub fn new() -> Self { + Self { + fn_nodes: HashMap::new(), + node_cpu_usage: HashMap::new(), + } + } + + fn select_best_node_to_fn(&self, fnid: usize, env: &SimEnvObserve) -> usize { + // 先取出该函数所需要的cpu + let fn_cpu_use = env.func(fnid).cpu; + + let nodes = self.fn_nodes.get(&fnid).unwrap(); + + let mut best_nodeid = 9999; + let mut best_node_cpu_local = 0.0; + + for nodeid in nodes { + if best_nodeid == 9999 { + best_nodeid = *nodeid; + } + + let node_rsc = self.node_cpu_usage.get(nodeid).unwrap(); + + // 取出cpu分配额 + let cpu_local = node_rsc.cpu_limit / (node_rsc.all_task_cnt + 1.0); + + if fn_cpu_use / cpu_local <= 5.0 { + return *nodeid; + } + + if cpu_local > best_node_cpu_local { + best_nodeid = *nodeid; + best_node_cpu_local = cpu_local; + } + + } + + best_nodeid + } +} + +impl Scheduler for EnsureScheduler { + fn schedule_some( + &mut self, + env: &SimEnvObserve, + mech: &MechanismImpl, + cmd_distributor: &MechCmdDistributor,) + { + // 遍历每个节点，更新其资源使用情况 + for node in env.core().nodes().iter() { + // cpu + let cpu_limit = env.node(node.node_id()).rsc_limit.cpu; + + // 任务数量 + let all_task_cnt = node.all_task_cnt() as f32; + + self.node_cpu_usage.insert(node.node_id(), NodeCpuResc{cpu_limit, all_task_cnt}); + } + + let mut need_schedule_fn = HashSet::new(); + // 找到这一帧需要调度的函数 + for (_req_id, req) in env.core().requests_mut().iter_mut() { + let schedule_able_fns = schedule_helper::collect_task_to_sche( + req, + env, + schedule_helper::CollectTaskConfig::PreAllSched, + ); + for fnid in schedule_able_fns.iter() { + need_schedule_fn.insert(*fnid); + } + } + + for func in env.core().fns().iter() { + + let mut nodes = env + .core().fn_2_nodes() + .get(&func.fn_id) + .map(|v| { v.clone() }) + .unwrap_or(HashSet::new()); + + let target = mech.scale_num(func.fn_id); + let cur = env.fn_container_cnt(func.fn_id); + if target > cur{ + let up_cmd = mech.scale_up_exec().exec_scale_up( + target, + func.fn_id, env, + cmd_distributor + ); + + // 实时更新函数的节点情况 + for cmd in up_cmd.iter() { + nodes.insert(cmd.nid); + } + } + + if !need_schedule_fn.contains(&func.fn_id) { + env.fn_containers_for_each(func.fn_id, |container| { + // 如果该容器最近50帧都是空闲则缩容 + if container.recent_frame_is_idle(50) && container.req_fn_state.len() == 0 { + // 发送缩容命令 + cmd_distributor + .send(MechScheduleOnceRes::ScaleDownCmd(DownCmd + { + nid: container.node_id, + fnid: func.fn_id + } + )) + .unwrap(); + nodes.remove(&container.node_id); + } + }); + } + + log::info!("fn {}, nodes.len() = {}", func.fn_id, nodes.len()); + self.fn_nodes.insert(func.fn_id, nodes.clone()); + } + + for (_req_id, req) in env.core().requests().iter() { + let fns = schedule_helper::collect_task_to_sche( + req, + env, + schedule_helper::CollectTaskConfig::All, + ); + + //迭代请求中的函数，选择最合适的节点进行调度 + for fnid in fns { + let sche_nodeid = self.select_best_node_to_fn(fnid, env); + + log::info!("schedule fn {} to node {}", fnid, sche_nodeid); + + if sche_nodeid != 9999 { + cmd_distributor + .send(MechScheduleOnceRes::ScheCmd(ScheCmd { + nid: sche_nodeid, + reqid: req.req_id, + fnid, + memlimit: None, + })) + .unwrap(); + self.node_cpu_usage.get_mut(&sche_nodeid).unwrap().all_task_cnt += 1.0; + } + } + + } + + } +} diff --git a/serverless_sim/src/sche/load_least.rs b/serverless_sim/src/sche/load_least.rs new file mode 100644 index 0000000..0a1f4d4 --- /dev/null +++ b/serverless_sim/src/sche/load_least.rs @@ -0,0 +1,104 @@ +use std::{ + cmp::Ordering, + collections::{HashMap, HashSet}, +}; + +use crate::{ + fn_dag::{EnvFnExt, FnId}, mechanism::{DownCmd, MechType, MechanismImpl, ScheCmd, SimEnvObserve}, mechanism_thread::{MechCmdDistributor, MechScheduleOnceRes}, node::{self, EnvNodeExt, Node, NodeId}, sche, sim_run::{schedule_helper, Scheduler}, with_env_sub::WithEnvCore +}; + +pub struct LoadLeastScheduler { + fn_nodes: HashMap>, + node_cpu_usage: HashMap, +} + +impl LoadLeastScheduler { + pub fn new() -> Self { + Self { + fn_nodes: HashMap::new(), + node_cpu_usage: HashMap::new(), + } + } + + fn select_best_node_to_fn(&self, fnid: usize, _env: &SimEnvObserve) -> usize { + + let nodes = self.fn_nodes.get(&fnid).unwrap(); + + let mut best_nodeid = 9999; + let mut min_tasks_cnt = 9999; + + for nodeid in nodes { + if best_nodeid == 9999 { + best_nodeid = *nodeid; + } + + let iter_node_tasks = self.node_cpu_usage.get(nodeid).unwrap(); + + if min_tasks_cnt > *iter_node_tasks { + best_nodeid = *nodeid; + min_tasks_cnt = *iter_node_tasks; + } + + } + + best_nodeid + } +} + +impl Scheduler for LoadLeastScheduler { + fn schedule_some( + &mut self, + env: &SimEnvObserve, + mech: &MechanismImpl, + cmd_distributor: &MechCmdDistributor,) + { + // 遍历每个节点，更新其资源使用情况 + for node in env.core().nodes().iter() { + // 任务数量 + let all_task_cnt = node.all_task_cnt(); + self.node_cpu_usage.insert(node.node_id(), all_task_cnt); + } + + for func in env.core().fns().iter() { + let nodes = env + .core().fn_2_nodes() + .get(&func.fn_id) + .map(|v| { v.clone() }) + .unwrap_or(HashSet::new()); + + // log::info!("fn {}, nodes.len() = {}", func.fn_id, nodes.len()); + self.fn_nodes.insert(func.fn_id, nodes.clone()); + } + + for (_req_id, req) in env.core().requests().iter() { + let fns = schedule_helper::collect_task_to_sche( + req, + env, + schedule_helper::CollectTaskConfig::All, + ); + + //迭代请求中的函数，选择最合适的节点进行调度 + for fnid in fns { + let sche_nodeid = self.select_best_node_to_fn(fnid, env); + + log::info!("schedule fn {} to node {}", fnid, sche_nodeid); + + if sche_nodeid != 9999 { + cmd_distributor + .send(MechScheduleOnceRes::ScheCmd(ScheCmd { + nid: sche_nodeid, + reqid: req.req_id, + fnid, + memlimit: None, + })) + .unwrap(); + + let tasks_cnt = self.node_cpu_usage.get(&sche_nodeid).unwrap(); + self.node_cpu_usage.insert(sche_nodeid, tasks_cnt + 1); + } + } + + } + + } +} diff --git a/serverless_sim/src/sche/mod.rs b/serverless_sim/src/sche/mod.rs index ab09887..3973168 100644 --- a/serverless_sim/src/sche/mod.rs +++ b/serverless_sim/src/sche/mod.rs @@ -13,6 +13,8 @@ use self::{ random::RandomScheduler, hash::HashScheduler, rotate::RotateScheduler, + ensure_scheduler::EnsureScheduler, + load_least::LoadLeastScheduler, }; pub mod consistenthash; @@ -25,6 +27,8 @@ pub mod random; pub mod bp_balance; pub mod hash; pub mod rotate; +pub mod ensure_scheduler; +pub mod load_least; // pub mod rule_based; // pub mod time_aware; @@ -66,6 +70,12 @@ pub fn prepare_spec_scheduler(config: &Config) -> Option { return Some(Box::new(RotateScheduler::new())); } + "ensure_scheduler"=>{ + return Some(Box::new(EnsureScheduler::new())); + } + "load_least" => { + return Some(Box::new(LoadLeastScheduler::new())); + } _ => { return None; } diff --git a/serverless_sim/src/sim_env.rs b/serverless_sim/src/sim_env.rs index a2bcab5..1c9389e 100644 --- a/serverless_sim/src/sim_env.rs +++ b/serverless_sim/src/sim_env.rs @@ -456,12 +456,12 @@ impl SimEnv { } //有些变为运行状态 内存占用变大很正常 - assert!( - n.unready_mem() <= n.rsc_limit.mem, - "mem {} > limit {}", - n.unready_mem(), - n.rsc_limit.mem - ); + // assert!( + // n.unready_mem() <= n.rsc_limit.mem, + // "mem {} > limit {}", + // n.unready_mem(), + // n.rsc_limit.mem + // ); } // metric，将这一帧已完成的请求数清空 self.help.metric.borrow_mut().on_frame_begin();