Nature-inspired cost optimisation for enterprise cloud systems using joint allocation of resources. Issue 2 (7th February 2021)

• Record Type: Journal Article
• Authors: Mishra, Suchintan; Sahoo, Manmath Narayan; Kumar Sangaiah, Arun; Bakshi, Sambit
• Is Part Of: Enterprise information systems. Volume 15:Issue 2(2021)
• Page Start: 174
• Page End: 196
• Publication Date: 2021-02-07
• Subjects: VM placement -- cloud computing -- joint allocation -- multiobjective optimisation -- ACO -- resource allocation -- fuzzy AHP; Information storage and retrieval systems -- Periodicals; Management information systems -- Periodicals; Electronic commerce -- Periodicals; 658.4038011
• DOI: 10.1080/17517575.2019.1605001
• Languages: English
• ISSNs: 1751-7575

Abstract

ABSTRACT: Resource allocation in cloud being NP-complete lacks a generalised optimal solution. In this work, we propose a nature-inspired ACO-Fuzzy framework based joint resource allocation algorithm for cloud datacenters. The algorithm assigns compute and network resources efficiently to minimize end-user cost. An ACO-based local search heuristic is used to discover the current status of resources and then a Fuzzy-based decision maker finds the most optimal set of compute and network resources minimising the end-user cost. Analytical and experimental evaluations validate the efficiency of joint allocation. Abbreviations: CSP: cloud service provider; VM: virtual machine; VMP: virtual machine placement; NIJA: nature-inspired joint allocation; DM: decision maker; WAN: wireless area network; ACO: ant colony optimisation; SDFF: server defined first-fit; GA: genetic algorithm; PSO: particle swarm optimisation; SA: simulated annealing