Imperial College London
Alternate

ProfessorKinLeung

Faculty of Engineering, Department of Electrical and Electronic Engineering

Tanaka Chair in Internet Technology
 
 
 
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Contact

 

+44 (0)20 7594 6238kin.leung Website

 
 
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Assistant

 

Miss Vanessa Rodriguez-Gonzalez +44 (0)20 7594 6267

 
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Location

 

810aElectrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Zafari:2023:10.1109/TNSM.2023.3265813,
author = {Zafari, F and Basu, P and Leung, KK and Li, J and Towsley, D and Swami, A},
doi = {10.1109/TNSM.2023.3265813},
journal = {IEEE Transactions on Network and Service Management},
pages = {4369--4382},
title = {Resource Sharing in the Edge: A Distributed Bargaining-Theoretic Approach},
url = {http://dx.doi.org/10.1109/TNSM.2023.3265813},
volume = {20},
year = {2023}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - The growing demand for edge computing resources, particularly due to increasing popularity of Internet of Things (IoT), and distributed machine/deep learning applications poses a significant challenge. On the one hand, certain edge service providers (ESPs) may not have sufficient resources to satisfy their applications according to the associated service-level agreements. On the other hand, some ESPs may have additional unused resources. In this paper, we propose a resource-sharing framework that allows different ESPs to optimally utilize their resources and improve the satisfaction level of applications subject to constraints such as communication cost for sharing resources across ESPs. Our framework considers that different ESPs have their own objectives for utilizing their resources, thus resulting in a multi-objective optimization problem. We present an N-person Nash Bargaining Solution (NBS) for resource allocation and sharing among ESPs with Pareto optimality guarantee. Furthermore, we propose a distributed, primal-dual algorithm to obtain the NBS by proving that the strong-duality property holds for the resultant resource sharing optimization problem. Using synthetic and real-world data traces, we show numerically that the proposed NBS based framework not only enhances the ability to satisfy applications' resource demands, but also improves utilities of different ESPs.
AU  - Zafari,F
AU  - Basu,P
AU  - Leung,KK
AU  - Li,J
AU  - Towsley,D
AU  - Swami,A
DO  - 10.1109/TNSM.2023.3265813
EP  - 4382
PY  - 2023///
SP  - 4369
TI  - Resource Sharing in the Edge: A Distributed Bargaining-Theoretic Approach
T2  - IEEE Transactions on Network and Service Management
UR  - http://dx.doi.org/10.1109/TNSM.2023.3265813
VL  - 20
ER  -
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