Paper Info
Title
Joint Optimization Of Service Chain Caching And Task Offloading In Mobile Edge Computing
Abstract
Caching and offloading in Mobile Edge Computing (MEC) are hot topics recently. Existing caching strategies at the edge ignore the programming ability of edge network and design strategies independently thus network resource is under utilization and the quality of experience (QOE) for end users is far from satisfactory. In this paper, we design intelligently joint caching and offloading strategies under the assumption that applications can be in the form of divisible service chain. Different from common approaches that target on reducing response latency only for users, our system take the leasing cost into consideration thus is more efficient for Application Service Providers (ASP). To fulfill our design, we novelly utilize open Jackson queuing network to formulate this joint optimization problem under long term cost restrictions and design a pipeline of algorithm to search for the optimal solution. More specifically, we design a cost adaptive algorithm derived from Lyapunov drift-plus-penalty function so that the long-term problem can be optimized in the slot-by-slot basis. Moreover, we propose to exploit resource-based utility function and device-number-based relative distance to jointly find optimal caching and offloading scheme. Extensive simulation results demonstrate that our approach can effectively reduce the average service latency of the MEC system and keep a low average leasing cost. (C) 2021 Elsevier B.V. All rights reserved.
Year
DOI
Venue
2021
10.1016/j.asoc.2021.107142
APPLIED SOFT COMPUTING
Keywords
DocType
Volume
Mobile edge computing, Service chain caching, Task offloading, Lyapunov Optimization
Journal
103
ISSN
Citations 
PageRank 
1568-4946
6
0.38
References 
Authors
24
7
Name
Order
Citations
PageRank
Kai Peng160.38
Jiangtian Nie29710.96
Neeraj Kumar32889236.13
Chao Cai460.38
Jiawen Kang554331.46
Zehui Xiong658654.94
Yang Zhang760.38