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Utilization and Energy Consumption Optimization for Cloud Computing Environment - 2021

Research Area:  Cloud Computing

Abstract:

In a cloud environment, the workload that has to be maintained using visualization is limited by the available hardware resources of virtual machines (VMs). So utilization of VMs becomes significant to do more work with lesser infrastructure. Thus, in recent times, major thrust was shown by researchers in the field of task allocation algorithms on VMs. There are many techniques discussed in the literature, which uses different allocation methods, which can improve the performance by changing the working of cloud environment. In this research work, analysis, implementation and performance comparison of the existing allocation techniques have been performed using CloudSim. So performance tuning is being done analytically and practically for the task allocation algorithm. VMs and cloudlets are configured for experimental purposes and parameter results are obtained. Parameters recorded are execution time, makespan, utilization ratio and power consumption. A new algorithm is proposed for task allocation algorithm (Tiwari et al in Int J Adv Intell Syst Comput, 2016 (Tiwari and Kumar in Telecommun. Syst. 62:149–165, 2016)). These parameters are calculated for FCFS, SJF, Hungarian and the proposed algorithm. Then, result analysis is done and majorly got a speedup in utilization ratio of the proposed algorithm w.r.t. to FCFS as 53.20%, 18.08% w.r.t. to SJF and 10.52% w.r.t. to Hungarian. For power consumption, the algorithm has shown a significant decrease in power consumption from 37.21, 16.52 and 10.52% w.r.t. to FCFS, SJF and Hungarian algorithms.

Author(s) Name:  Rajeev Tiwari,Roohi Sille,Nilima Salankar,Pardeep Singh

Journal name:  

Conferrence name:  Cyber Security and Digital Forensics

Publisher name:  Springer

DOI:  10.1007/978-981-16-3961-6_50

Volume Information:  pp 609-619