CGSA scheduler: A multi-objective-based hybrid approach for task scheduling in cloud environment

• Published in: Information security journal. Vol. 27; no. 2; pp. 77 - 91
• Main Authors: Pradeep, K., Jacob, T. Prem
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis Ltd 04.03.2018
• Subjects: Algorithms; Cloud computing; Energy consumption; Genetic algorithms; Gravitation; Multiple objective analysis; Particle swarm optimization; Scheduling; Search algorithms; Task scheduling
• ISSN: 1939-3555; 1939-3547
• DOI: 10.1080/19393555.2017.1407848

In cloud computing task scheduling is one of the important processes. The key problem of scheduling is how to allocate the entire task to a corresponding virtual machine while maximizing profit. The main objective of this paper is to execute the entire task with low cost, less resource use, and less energy consumption. To obtain the multi-objective function for scheduling, in this paper we propose a hybridization of cuckoo search and gravitational search algorithm (CGSA). The vital design of our approach is to exploit the merits of both cuckoo search (CS) and gravitational search algorithms (GSA) while avoiding their drawbacks. The performance of the algorithm is analyzed based on the different evaluation measures. The algorithms like GSA, CS, Particle swarm optimization (PSO), and genetic algorithm (GA) are used as a comparative analysis. The experimental results show that our proposed algorithm achieves the better result compare to the existing approaches.