Function-Aware Resource Management Framework for Serverless Edge Computing

作     者：Ko, Haneul Pack, Sangheon 

作者机构：Kyung Hee Univ Dept Elect Engn Yongin 17104 Gyeonggi South Korea Korea Univ Sch Elect Engn Seoul 02841 South Korea 

出 版 物：《IEEE INTERNET OF THINGS JOURNAL》 (IEEE Internet Things J.)

年 卷 期：2023年第10卷第2期

页      面：1310-1319页

核心收录：

学科分类：0810[工学-信息与通信工程] 0808[工学-电气工程] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Research Foundation (NRF) of South Korea [2020R1A2C3006786] Institute for Information & Communications Technology Planning & Evaluation (IITP) [2021-0-00739] 

主　　题：Function-aware resource management (FARM) joint optimization serverless edge computing warm start 

摘      要：Serverless edge computing is an emerging concept where only required functions are defined and executed as container instances at the edge cloud. The edge cloud has finite resources;therefore, sophisticated resource management is indispensable to accommodate more requests. In this article, we propose a function-aware resource management (FARM) framework for serverless edge computing that defines per-function queues to maximally utilize edge cloud resources. The FARM framework optimally determines: 1) which container instances should be maintained as warm status and 2) the amount of computing resources assigned to them. The FARM framework specifically formulates a constrained Markov decision process problem to minimize the memory resource consumption for the warm status maintenance while guaranteeing on-time task completion and converts it to a linear programming model to derive the optimal solution. The evaluation results show that the FARM framework can reduce the memory resource consumption of the edge cloud while meeting the on-time task completion.