Research Area:  Cloud Computing

Abstract:

Cloud computing provides effective mechanisms for distributing the computing tasks to the virtual resources. To provide cost-effective executions and achieve objectives such as load balancing, availability and reliability in the cloud environment, appropriate task and workflow scheduling solutions are needed. Various metaheuristic algorithms are applied to deal with the problem of scheduling, which is an NP-hard problem. This paper presents an in-depth analysis of the Particle Swarm Optimization (PSO)-based task and workflow scheduling schemes proposed for the cloud environment in the literature. Moreover, it provides a classification of the proposed scheduling schemes based on the type of the PSO algorithms which have been applied in these schemes and illuminates their objectives, properties and limitations. Finally, the critical future research directions are outlined.

Keywords:  

Author(s) Name:  Mohammad Masdari, Farbod Salehi, Marzie Jalali & Moazam Bidaki

Publisher name:  Springer

DOI:  10.1007/s10922-016-9385-9

Volume Information:  volume 25, pages 122–158 (2017)

Paper Link:   https://link.springer.com/article/10.1007/s10922-016-9385-9