Dynamic Weighted Fog Computing Device Placement Using a Bat-Inspired Algorithm with Dynamic Local Search Selection
- PDF / 1,678,518 Bytes
- 11 Pages / 595.276 x 790.866 pts Page_size
- 37 Downloads / 262 Views
Dynamic Weighted Fog Computing Device Placement Using a Bat-Inspired Algorithm with Dynamic Local Search Selection Chun-Cheng Lin 1,2,3 & Der-Jiunn Deng 4
&
Sirirat Suwatcharachaitiwong 1 & Yan-Sing Li 1
# Springer Science+Business Media, LLC, part of Springer Nature 2020
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. Keywords Fog computing . Mobile edge . Nature-inspired algorithm . Deployment . Dynamics . Node-weighted graph
1 Introduction Cloud/fog/edge computing and the Internet of Things (IoT) play a crucial role in Industry 4.0 [1]. Generally, in a smart factory (or other industrial applications defined within a limited geographical region), the cloud server is maintained in a centralized location, causing a too long latency time to respond to the requests from a huge number of IoT sensors distributed in a large working area. Fog computing extends * Der-Jiunn Deng [email protected] Chun-Cheng Lin [email protected] Sirirat Suwatcharachaitiwong [email protected] Yan-Sing Li [email protected] 1
Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu 300, Taiwan
2
Department of Business Administration, Asia Univesity, Taichung 413, Taiwan
3
Department of Medical Research, China Medical University Hospital, China Medical University, Taichung 404, Taiwan
4
Department of Computer Science and Information Engineering, National Changhua University of Education, Changhua 500, Taiwan
cloud computing with distributing computing, storage, and networking resources to the network edge to support IoT applications with requirements of real-time and low-latency response, location awareness, end-device mobility, scalability, heterogeneity, transient storage, high-speed data dissemination, decentralized computation, and security [2, 3]. This work focuses on the optimization problem of deploying fog computing devices to support the requests from mobile edge devices in a geographical area. Deployment of fog systems has appeared in several applications, e.g., intelligent logistic center [4], local area networks [5], medical cyber-physical system [
Data Loading...
