Spatial-Temporal Edge User Allocation: An Expectation Confirmation Perspective Approach

Article


Zou, Guobing, Xu, Zhiwei, Xia, Xiaoyu, Liu, Ya, Gan, Yanglan, Zhang, Bofeng, Zhou, Min and He, Qiang. 2022. "Spatial-Temporal Edge User Allocation: An Expectation Confirmation Perspective Approach." IEEE Transactions on Network and Service Management. 19 (4), pp. 4918-4931. https://doi.org/10.1109/TNSM.2022.3193088
Article Title

Spatial-Temporal Edge User Allocation: An Expectation Confirmation Perspective Approach

ERA Journal ID5064
Article CategoryArticle
AuthorsZou, Guobing (Author), Xu, Zhiwei (Author), Xia, Xiaoyu (Author), Liu, Ya (Author), Gan, Yanglan (Author), Zhang, Bofeng (Author), Zhou, Min (Author) and He, Qiang (Author)
Journal TitleIEEE Transactions on Network and Service Management
Journal Citation19 (4), pp. 4918-4931
Number of Pages14
Year2022
PublisherIEEE (Institute of Electrical and Electronics Engineers)
Place of PublicationUnited States
ISSN1932-4537
Digital Object Identifier (DOI)https://doi.org/10.1109/TNSM.2022.3193088
Web Address (URL)https://ieeexplore.ieee.org/document/9837317
Abstract

As the 5th generation (5G) network develops and rolls out rapidly, user requests can be offloaded to nearby edge servers for processing. This alleviates the pressure on the network backhaul and the remote cloud. Nevertheless, the edge user allocation (EUA) problem, as one of the main research challenges in the 5G era, has become a major obstacle to ensuring users’ Quality of Experience (QoE) in the edge computing environment. Conventional EUA approaches, ranging from static global allocation model to online decision-making model, have ignored the long-term impact of the changes in users’ expectations on user-perceived Quality of Service (QoS). Additionally, most existing approaches have not taken into account the distance between an edge user and an edge server, which impacts the user’s data rate profoundly. In this paper, we tackle these challenges by formulating EUA problem as a spatial-temporal one (ST-EUA), which models distance-aware QoS based on the wireless transmission attenuation and models users’ QoE based on the Expectation Confirmation Theory (ECT). To find an appropriate solution for ST-EUA problem, we develop two fuzzy control-based approaches, namely FC and BFC, for on demand scenarios and batch processing scenarios, respectively. They can balance effectively the user consolidation and server load. We conduct extensive experiments based on two widely-used real-world datasets. The results demonstrate the superiority of our FC and BFC in effectiveness and efficiency over the baselines and state-of-the-art.

KeywordsEdge User Allocation, Expectation Confirmation Theory, Fuzzy Control, Quality of Experience, Quality of Service
ANZSRC Field of Research 2020460612. Service oriented computing
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Byline AffiliationsShanghai University, China
Beijing National Research Center for Information Science and Technology, China
School of Mathematics, Physics and Computing
Donghua University, China
Shanghai Polytechnic University, China
Swinburne University of Technology
Institution of OriginUniversity of Southern Queensland
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