Formulating Interference-aware Data Delivery Strategies in Edge Storage Systems

Paper

Xia, Xiaoyu, Chen, Feifei, He, Qiang, Cui, Guangming, Grundy, John, Abdelrazek, Mohamed and Dong, Fang. 2023. "Formulating Interference-aware Data Delivery Strategies in Edge Storage Systems." 51st International Conference on Parallel Processing (ICPP '22). Bordeaux, France 29 Aug - 01 Sep 2022 United States. Association for Computing Machinery (ACM). https://doi.org/10.1145/3545008.3545078

Paper/Presentation Title	Formulating Interference-aware Data Delivery Strategies in Edge Storage Systems
Presentation Type	Paper
Authors	Xia, Xiaoyu, Chen, Feifei, He, Qiang, Cui, Guangming, Grundy, John, Abdelrazek, Mohamed and Dong, Fang
Journal or Proceedings Title	Proceedings of the 51st International Conference on Parallel Processing (ICPP '22)
Journal Citation	pp. 1-11
Article Number	68
Number of Pages	11
Year	2023
Publisher	Association for Computing Machinery (ACM)
Place of Publication	United States
ISBN	9781450397339
Digital Object Identifier (DOI)	https://doi.org/10.1145/3545008.3545078
Web Address (URL) of Paper	https://dl.acm.org/doi/10.1145/3545008.3545078
Conference/Event	51st International Conference on Parallel Processing (ICPP '22)
Event Details	51st International Conference on Parallel Processing (ICPP '22) Parent International Conference on Parallel Processing (ICPP) Delivery In person Event Date 29 Aug 2022 to end of 01 Sep 2022 Event Location Bordeaux, France
Abstract	Networked edge servers constitute an edge storage system in edge computing (EC). Upon users’ requests, data must be delivered from edge servers in the system or from the cloud to users. Existing studies of edge storage systems have unfortunately neglected the fact that an excessive number of users accessing the same edge server for data may impact users’ data rates seriously due to the wireless interference. Thus, users must first be allocated to edge servers properly for ensuring their data rates. After that, requested data can be delivered to users to minimize their average data delivery latency. In this paper, we formulate this Interference-aware Data Delivery at the network Edge (IDDE) problem, and demonstrate its NP-hardness. To tackle it effectively and efficiently, we propose IDDE-G, a novel approach that first finds a Nash equilibrium as the strategy for allocating users. Then, it finds an approximate strategy for delivering requested data to allocated users. We analyze the performance of IDDE-G theoretically and evaluate its performance experimentally to demonstrate the effectiveness and efficiency of IDDE-G on solving the IDDE problem.
Keywords	edge computing; data delivery; edge storage system; interferenceaware; user allocation
ANZSRC Field of Research 2020	4699. Other information and computing sciences
Public Notes	Files associated with this item cannot be displayed due to copyright restrictions.
Byline Affiliations	Deakin University
	University of Southern Queensland
	Swinburne University of Technology
	Monash University
	Southeast University, China

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