FPFTS: A joint fuzzy particle swarm optimization mobility‐aware approach to fog task scheduling algorithm for Internet of Things devices. (18th August 2020)

• Record Type: Journal Article
• Authors: Javanmardi, Saeed; Shojafar, Mohammad; Persico, Valerio; Pescapè, Antonio
• Other Names: Kumar Neeraj guestEditor.; Jindal Anish guestEditor.; Villari Massimo guestEditor.; Srirama Satish Narayana guestEditor.
• Is Part Of: Software, practice & experience. Volume 51:Number 12(2021)
• Page Start: 2519
• Page End: 2539
• Publication Date: 2020-08-18
• Subjects: fog computing -- Internet of Things -- Mamdani fuzzy inference system -- particle swarm optimization algorithm -- resource management -- task scheduling; Computer software -- Periodicals; Computer programming -- Periodicals; Computer programs -- Periodicals; 005.3
• DOI: 10.1002/spe.2867
• Languages: English
• ISSNs: 0038-0644

Abstract

Summary: In the Internet of Things (IoT) scenario, the integration with cloud‐based solutions is of the utmost importance to address the shortcomings resulting from resource‐constrained things that may fall short in terms of processing, storing, and networking capabilities. Fog computing represents a more recent paradigm that leverages the wide‐spread geographical distribution of the computing resources and extends the cloud computing paradigm to the edge of the network, thus mitigating the issues affecting latency‐sensitive applications and enabling a new breed of applications and services. In this context, efficient and effective resource management is critical, also considering the resource limitations of local fog nodes with respect to centralized clouds. In this article, we present FPFTS, fog task scheduler that takes advantage of particle swarm optimization and fuzzy theory, which leverages observations related to application loop delay and network utilization. We evaluate FPFTS using an IoT‐based scenario simulated within iFogSim, by varying number of moving users, fog‐device link bandwidth, and latency. Experimental results report that FPFTS compared with first‐come first‐served (respectively, delay‐priority) allows to decrease delay‐tolerant application loop delay by 85.79% (respectively, 86.36%), delay sensitive application loop delay by 87.11% (respectively, 86.61%), and network utilization by 80.37% (respectively, 82.09%), on average.