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

Shuhan Zhu, Wei Xu, Lisheng Fan, Kezhi Wang, George K. Karagiannidis

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)
7 Downloads (Pure)

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.
Original languageEnglish
Pages (from-to)402-405
Number of pages4
JournalIEEE Wireless Communications Letters
Volume9
Issue number3
Early online date5 Dec 2019
DOIs
Publication statusPublished - 9 Mar 2020

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