Nature-inspired cost optimisation for enterprise cloud systems using joint allocation of resources. Issue 2 (7th February 2021) - Mishra, Suchintan; Sahoo, Manmath Narayan; Kumar Sangaiah, Arun; Bakshi, Sambit
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