Dynamic Weighted Fog Computing Device Placement Using a Bat-Inspired Algorithm with Dynamic Local Search Selection

Chun Cheng Lin, Der Jiunn Deng, Sirirat Suwatcharachaitiwong, Yan Sing Li

Research output: Contribution to journalArticle

Abstract

This work investigates the dynamical weighted deployment of mobile fog computing devices to support a mobile edge computing environment, in which each edge device is associated with a weight to reflect its importance based on the application. Since edge devices are mobile and could be switched off, it is challenging to dynamically optimize the deployment to adapt to dynamic change. This work further models the problem mathematically and solves it by a bat-inspired algorithm (BA), which searches the optimal solutions by simulating the food-searching behavior of bats via echolocation. Furthermore, three local search methods designed specifically for this problem are integrated into the BA, and a dynamic local search selection mechanism is proposed to adjust the probabilities of choosing the three local search methods iteratively in the BA main loop. Simulation results show outperformance of the proposed BA over the BA without local search and the previous approach.

Original languageEnglish
Pages (from-to)1805-1815
Number of pages11
JournalMobile Networks and Applications
Volume25
Issue number5
DOIs
Publication statusPublished - 2020 Oct 1

All Science Journal Classification (ASJC) codes

  • Software
  • Information Systems
  • Hardware and Architecture
  • Computer Networks and Communications

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