An online fair resource allocation solution for fog computing. Issue 4 (4th July 2022)

• Record Type: Journal Article
• Authors: Sun, Jia He; Choudhury, Salimur; Salomaa, Kai
• Is Part Of: International journal of parallel, emergent and distributed systems. Volume 37:Issue 4(2022)
• Page Start: 456
• Page End: 477
• Publication Date: 2022-07-04
• Subjects: Fog computing -- fair resource allocation -- heuristic -- online scheduling; Parallel computers -- Periodicals; Electronic data processing -- Distributed processing -- Periodicals; Computer algorithms -- Periodicals; 004.35
• DOI: 10.1080/17445760.2022.2061484
• Languages: English
• ISSNs: 1744-5760

Abstract

Abstract : Fog computing is a complementary computing paradigm to the existing cloud computing. A fundamental problem of fog computing is how to allocate the computing resources of fog nodes when scheduling tasks that arrive in an online manner. Other than task completion speed metrics, fairness of resource allocation between competing users is also an important metric to consider. One such metric is Dominant Resource Fairness (DRF), a fairness scheme that guarantees four key qualities: incentivised sharing, strategy-proof, Pareto-efficiency, and envy free. This paper examines the multi-resource, multi-server, and heterogeneous task resource allocation problem from a DRF perspective. Four different types of tasks are considered: ordered/unordered and splittable/unsplittable. Three low complexity heuristics are proposed to maximise fairness between users. Results show that the proposed heuristics are at least comparable to three baseline scheduling algorithms in terms of task completion speed while achieving higher fairness between users.