文献类型：期刊文献

英文题名：Time-cost efficient memory configuration for serverless workflow applications

作者：Li, Zengpeng[1];Yu, Huiqun[1,2];Fan, Guisheng[1]

机构：[1]East China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai 200237, Peoples R China;[2]Shanghai Key Lab Comp Software Evaluating & Testi, Shanghai, Peoples R China

年份：2022

卷号：34

期号：27

外文期刊名：CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE

收录：;EI(收录号：20223912786013);WOS:【SCI-EXPANDED(收录号:WOS:000858434700001)】；

基金：National Natural Science Foundation of China, Grant/Award Number: 61772200; Natural Science Foundation of Shanghai, Grant/Award Number: 21ZR1416300

语种：英文

外文关键词：constrained optimization; performance modeling; serverless computing; workflow memory configuration

摘要：Recently, workflow applications are increasingly migrated to Function-as-a-Service platforms which are easy to manage, highly-scalable, and pay-as-you-go. Meanwhile, users face challenges in migration of serverless applications because of the lack of efficient algorithm for workflow memory configuration to optimize the performance. To this end, this article proposes a heuristic urgency-based algorithm UWC and a meta-heuristic hybrid algorithm BPSO to tackle the time-cost tradeoff. UWC sorts functions and allocates each function an appropriate memory size by greedy strategy. BPSO hybridizes particle swarm optimization as well as beetle antennae search algorithm to guide particles to search directionally and utilizes nonlinear inertia weight to avoid local premature convergence. Extensive experiments with classical serverless application demonstrate that UWC and BPSO are very competitive in comparison with existing algorithms as they can find the optimal workflow memory configuration.