Performance Evaluation and Implementation of Tasks in Virtual Machines
Suman Sourav Prasad1, Jyoti Prakash Mishra2, Sambit Kumar Mishra3

1Suman Sourav Prasad*, Department of MCA, Ajay Binay Institute of Technology, Cuttack, India.
2Jyoti Prakash Mishra, Computer Sc.&Engg. Department, Gandhi Institute for Education and Technology, Baniatangi, Bhubaneswar, India.
Sambit Kumar Mishra, Computer Sc. &Engg. Department, Gandhi Institute for Education and Technology, Baniatangi, Bhubaneswar, India. 
Manuscript received on October 16, 2019. | Revised Manuscript received on 25 October, 2019. | Manuscript published on November 10, 2019. | PP: 1524-1527 | Volume-9 Issue-1, November 2019. | Retrieval Number: A4371119119/2019©BEIESP | DOI: 10.35940/ijitee.A4371.119119
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Abstract: In the present situation, it may be essential to build a simple data sharing environment to monitor and protect the unauthorized modification of data. In such case, mechanisms may be required to develop to focus on significant weakened networking with proper solutions. In some situations, block chain data management may be used considering the cloud environment. It is well understood that in virtual environment, allocating resources may have significant role towards evaluating the performance including utilization of resources linked to the data center. Accuracy towards allocation of virtual machines in cloud data centers may be more essential considering the optimization problems in cloud computing. In such cases, it may also be desirable to prioritize on virtual machines linked to cloud data centers. Consolidating the dynamic virtual machines may also permit the virtual server providers to optimize utilization of resources and to focus on energy consumption. In fact, tremendous rise in acquiring computational power driven by modern service applications may be linked towards establishment of large-scale virtualized data centers. Accordingly, the joint collaboration of smart connected devices with data analytics may also enable enormous applications towards different predictive maintenance systems. To obtain the near optimal as well as feasible results in this case, it may be desirable to simulate implementing the algorithms and focusing on application codes. Also, different approaches may also be needed to minimize development time and cost. In many cases, the experimental result proves that the simulation techniques may minimize the cache miss and improve the execution time. In this paper, it has been intended towards distribution of tasks along with implementation mechanisms linked to virtual machines.
Keywords: Data Center, Virtual Machine, Blockchain, Data Analytics, Metaheuristic
Scope of the Article: Data Analytics