A novel approach using modified filtering algorithm (MFA) for effective completion of cloud tasks

Issue title: Special section: Recent trends, Challenges and Applications in Cognitive Computing for Intelligent Systems

Guest editors: Vijayakumar Varadarajan, Piet Kommers, Vincenzo Piuri and V. Subramaniyaswamy

Article type: Research Article

Authors: Jha, Sudan^a | Prashar, Deepak^a | Elngar, Ahmed A.^{b; *}

Affiliations: [a] School of Computer Science and Engineering, Lovely Professional University, Phagwara, Punjab, India | [b] Faculty of Computers and Artificial Intelligence, Beni-Suef University, Beni-Suef City, Egypt

Correspondence: [*] Corresponding author. Ahmed A. Elngar, Faculty of Computers and Artificial Intelligence, Beni-Suef University, Beni-Suef, 62511, Egypt. E-mail: elngar_7@yahoo.co.uk.

Abstract: In today’s era, cloud computing has played a major role in providing various services and capabilities to a number of researchers around the globe. One of the major problems we face in cloud is to identify the various constraints related with the delay in the Task accomplishment as well as the enhanced approach to execute the task with high throughput. Many studies have shown that it is almost difficult to create an ideal solution but it seems feasible to provide a sub-optimal solution utilizing heuristic algorithms. In this paper, compared to previously used particle swarm optimization (PSO), heuristic approaches, and improved PSO algorithm for efficient task scheduling, we propose “Modified Filtering Algorithm” for task scheduling on cloud setting. Comparing all these three algorithms, we strive to build an optimum schedule to reduce the completion period of execution of activities.

Keywords: Cloud environment, modified filtering algorithm (MFA), heuristic algorithms, PSO, task scheduling, quantum time

DOI: 10.3233/JIFS-189159

Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 6, pp. 8409-8417, 2020