A Novel Cross Entropy Approach for Offloading Learning in Mobile Edge Computing

Zhu, Shuhan, Xu, Wei, Fan, Lisheng, Wang, Kezhi and Karagiannidis, George K. (2020) A Novel Cross Entropy Approach for Offloading Learning in Mobile Edge Computing. IEEE Wireless Communications Letters, 9 (3). pp. 402-405. ISSN 2162-2337

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Official URL: https://doi.org/10.1109/lwc.2019.2957743

Abstract

In this letter, we propose a novel offloading learning approach to compromise energy consumption and latency in a multi-tier network with mobile edge computing. In order to solve this integer programming problem, instead of using conventional optimization tools, we apply a cross entropy approach with iterative learning of the probability of elite solution samples. Compared to existing methods, the proposed one in this network permits a parallel computing architecture and is verified to be computationally very efficient. Specifically, it achieves performance close to the optimal and performs well with different choices of the values of hyperparameters in the proposed learning approach.

Item Type: Article
Uncontrolled Keywords: Mobile edge computing (MEC), cross entropy (CE), computation offloading, probability learning.
Subjects: G400 Computer Science
G500 Information Systems
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Elena Carlaw
Date Deposited: 17 Jan 2020 09:28
Last Modified: 12 Mar 2020 11:30
URI: http://nrl.northumbria.ac.uk/id/eprint/41921

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