Cloud service reliability modelling and optimal task scheduling
Document Type
Article
Publication Date
1-26-2017
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.
Identifier
85009966243 (Scopus)
Publication Title
Iet Communications
External Full Text Location
https://doi.org/10.1049/iet-com.2016.0417
ISSN
17518628
First Page
161
Last Page
167
Issue
2
Volume
11
Grant
2012CB315805
Fund Ref
National Natural Science Foundation of China
Recommended Citation
Cui, Hongyan; Li, Yang; Liu, Xiaofei; Ansari, Nirwan; and Liu, Yunjie, "Cloud service reliability modelling and optimal task scheduling" (2017). Faculty Publications. 9792.
https://digitalcommons.njit.edu/fac_pubs/9792
