Abstract
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.
Original language | English |
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Pages (from-to) | 1310-1319 |
Number of pages | 10 |
Journal | IEEE Internet of Things Journal |
Volume | 10 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2023 Jan 15 |
Externally published | Yes |
Keywords
- Function-aware resource management (FARM)
- joint optimization
- serverless edge computing
- warm start
ASJC Scopus subject areas
- Signal Processing
- Information Systems
- Hardware and Architecture
- Computer Science Applications
- Computer Networks and Communications