Fair Multi-Resource Allocation in Heterogeneous Servers With an External Resource Type

This paper considers the problem of fair allocation of multiple types of resources in heterogeneous servers, along with a resource type external to those servers. Our work is motivated by the need for fair multi-resource allocation in mobile edge computing (MEC), where the users must upload their ta...

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Bibliographic Details
Published in:IEEE/ACM transactions on networking 2023-06, Vol.31 (3), p.1-19
Main Authors: Meskar, Erfan, Liang, Ben
Format: Article
Language:English
Subjects:
Cloud computing
Computational modeling
Edge computing
external resource
Fair resource allocation
heterogeneous computing servers
Minimax techniques
Mobile computing
multiple resource types
Resource allocation
Resource management
Resource utilization
Servers
Task analysis
Wireless communication
Wireless communications
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Summary:This paper considers the problem of fair allocation of multiple types of resources in heterogeneous servers, along with a resource type external to those servers. Our work is motivated by the need for fair multi-resource allocation in mobile edge computing (MEC), where the users must upload their tasks over a single dedicated wireless communication link that exists outside the computing servers. We propose a fair multi-resource allocation mechanism for this environment, termed Task Share Fairness with External Resource (TSF-ER), which finds the Kalai-Smorodinsky bargaining solution satisfying important fairness properties. We show that TSF-ER is envy-free, Pareto optimal, and strategy-proof, and it satisfies the property of sharing incentive. Large-scale simulation driven by Google and Alibaba cluster trace further shows that TSF-ER significantly outperforms the existing utilitarian, Nash social welfare maximizer, and egalitarian solutions, leading to fairer resource allocation while maintaining a high level of resource utilization.
ISSN:1063-6692
1558-2566
DOI:10.1109/TNET.2022.3213426