Task consolidation based power consumption minimization in cloud computing environment

• Published in: Multimedia tools and applications Vol. 82; no. 14; pp. 21385 - 21413
• Main Authors: Badr, Shaimaa, El Mahalawy, Ahmed, Attiya, Gamal, Nasr, Aida A.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.06.2023; Springer Nature B.V
• Subjects: Algorithms; Cloud computing; Computer centers; Computer Communication Networks; Computer Science; Consolidation; Data centers; Data Structures and Information Theory; Multimedia Information Systems; Optimization; Power consumption; Resource utilization; Special Purpose and Application-Based Systems; Task scheduling; Cloud computing; Task consolidation; Data centers; Scheduling; Power consumption; And CloudSim
• ISSN: 1380-7501; 1573-7721
• DOI: 10.1007/s11042-022-14009-1

Cloud Computing is playing a huge role in future technology. Further, with the explosive growth of the Internet and cloud computing, several service providers, such as Amazon, Microsoft, IBM, and Google, have expanded their data centers and rapidly deployed data centers in different places around the world to deliver various cloud computing services. However, several challenges are raised with the wide spread use of cloud environment such as power consumption, load balance, reliability, scalability, and security. This paper tackles the power consumption problem and presents an efficient algorithm, called Task Consolidation based Power Minimization (TCPM), to efficiently schedule tasks onto available resources of the cloud environment so as to minimize power consumption. In proposed TCPM algorithm, several benefits of the existing algorithms are enhanced and incorporated into the TCPM algorithm, where the best-fit procedure is used to achieve the best possible resource utilization and avoid wasting energy. The results of the proposed TCPM algorithm are compared with other recent algorithms such as FCFS, WWO, and MCT algorithms using the CloudSim toolkit.