Load balancing aware scheduling algorithms for fog networks. (18th June 2019)

• Record Type: Journal Article
• Authors: Singh, Anil; Auluck, Nitin
• Other Names: Wu Hao guestEditor.; Bie Rongfang guestEditor.; Pereira Charith guestEditor.; Rana Omer guestEditor.
• Is Part Of: Software, practice & experience. Volume 50:Number 11(2020)
• Page Start: 2012
• Page End: 2030
• Publication Date: 2019-06-18
• Subjects: cloud data center -- fog computing -- load balancing -- mobile data center -- security; Computer software -- Periodicals; Computer programming -- Periodicals; Computer programs -- Periodicals; 005.3
• DOI: 10.1002/spe.2722
• Languages: English
• ISSNs: 0038-0644

Abstract

Summary: Fog networks have attracted the attention of researchers recently. The idea is that a part of the computation of a job/application can be performed by fog devices that are located at the network edge, close to the users. Executing latency sensitive applications on the cloud may not be feasible, owing to the significant communication delay involved between the user and the cloud data center ( cdc ). By the time the application traverses the network and reaches the cloud data center, it might already be too late. However, fog devices, also known as mobile data centers ( mdcs ), are capable of executing such latency sensitive applications. In this paper, we study the problem of balancing the application load while taking account of security constraints of jobs, across various mdcs in a fog network. In case a particular mdc does not have sufficient capacity to execute a job, the job needs to be migrated to some other mdc . To this end, we propose three heuristic algorithms: minimum distance, minimum load, and minimum hop distance and load (MHDL) . In addition, we also propose an ILP ‐based algorithm called load balancing aware scheduling ILP ( LASILP ) for solving the task mapping and scheduling problem. The performance of the proposed algorithms have been compared with the cloud only algorithm and another heuristic algorithm called fog‐cloud‐placement ( FCP ). Simulation results performed on real‐life workload traces reveal that the MHDL heuristic performs better as compared to other scheduling policies in the fog computing environment while meeting application privacy requirements.