Cloud service reliability modelling and optimal task scheduling. Issue 2 (1st January 2017) - Cui, Hongyan; Li, Yang; Liu, Xiaofei; Ansari, Nirwan; Liu, Yunjie
Abstract : Cloud computing enables service sharing in a massive scale via network access to a pool of configurable computing resources. It has to allocate resources adaptively for tasks and applications to be executed effectively and reliably in a large scale, highly heterogeneous environment. Resource allocation in cloud computing is an NP‐hard problem. In this study, the authors conduct a reliability analysis of cloud services by applying a Markov‐based method. They formulate the cloud scheduling problem as a multi‐objective optimisation problem with constraints in terms of reliability, makespan, and flowtime. Furthermore, they propose a genetic algorithm‐based chaotic ant swarm (GA‐CAS) algorithm, in which four operators and natural selection are applied, to solve this constrained multi‐objective optimisation problem. Simulation results have demonstrated that GA‐CAS generally speeds up convergence and outperforms other meta‐heuristic approaches.