An upgraded fruit fly optimisation algorithm for solving task scheduling and resource management problem in cloud infrastructure. Issue 1 (13th December 2020)

• Record Type: Journal Article
• Authors: Loheswaran, K.
• Is Part Of: IET networks. Volume 10:Issue 1(2021)
• Page Start: 24
• Page End: 33
• Publication Date: 2020-12-13
• Subjects: Computer network architectures -- Periodicals; Computer network protocols -- Periodicals; Information networks -- Periodicals; Telecommunication systems -- Periodicals; 004.605
• DOI: 10.1049/ntw2.12001
• Languages: English
• ISSNs: 2047-4954

Abstract

Abstract: In this manuscript, an upgraded Fruit Fly Optimization Algorithm (FFOA) is proposed for optimising task scheduling and resource management processes. The proposed FOA algorithm is utilized to address the issues. In the proposed algorithm, every solution is represented by fruit fly. Every fruit fly upgrades their status through well‐organized smell search process. First, a basic approach is put forward to allocate every task for numerous resources and execution time is measured for every task. Second, the overloaded virtual machines (VMs) are identified and the load is balanced to obtain optimal system resource utilisation. The ability of Fly Task Scheduling Algorithm is to schedule the VMs execution time of tasks is minimal. The results of the Fruit Fly‐based algorithms such as Fruit Fly Task Scheduling Algorithm, Modified Fruit Fly Task Scheduling Algorithm, Improved Fruit Fly Task Scheduling Algorithm and Multi‐Swarm Fruit Fly Task Scheduling Algorithm (MSFFTSA) are proposed and analysed. The upgraded Fruit Fly Optimization algorithm of MSFFTSA is compared with different Fruit Fly algorithms. Finally, the proposed algorithm is compared with other algorithms and the experimental results shows that the proposed MSFFTSA technique is better than the other algorithms of the fruit fly algorithms.