A NOVEL APPROACH OF TASK CLASSIFICATION AND VM SKEWNESS IN CLOUD ENVIRONMENT

  • Sukhbhinder Kaur Research Scholar, Department of Computer Science & Engineering, SBSSTC, Ferozepur, Punjab.
  • Mr. Navtej Singh Ghumman Assistant Professor, Department of Computer Science & Engineering, SBSSTC, Ferozepur, Punjab.

Abstract

Cloud Computing is a technology that provides a platform for sharing of resources such as software, infrastructure, application and other information. Cloud Computing is being used widely all over the world, as it provides benefits to the users like cost saving and ease of use. The research work focuses on the study of task scheduling mechanism in cloud. The main goal is to reduce the power consumption by datacenters. Energy efficient scheduling of workload help to reduce the consumption of energy in datacenters thus helps in better usage of resources. An improved power saving algorithm is proposed by combining the task classification along with VM skewness algorithm with different scaling options. Skewness is used to quantify the unevenness in utilization of multiple resources on the server. Our purposed algorithm calculate the skewness factor of all Virtual Machines and based upon its value. The proposed approach is performing and shows a decrease in response time, waiting time, processing cost and overall electrical power consumed. The study can be further extended by applying the proposed algorithm on actual Cloud Computing environment and we can also integrate various energy saving technologies into data centers to reduce energy consumption.

References

[1] A. Agustí-Torra, F. Raspall, D. Remondo, D. Rincón and G. Giuliani, "On the feasibility of collaborative green data center ecosystems," Elsevier, pp. 566-580, 2014.
[2] A. Gunasekaran, N. Subramanian and Shams Rahman “Green supply chain collaboration and incentives: Current trends and future directions,” ELSEVIER, pp.1-10, 2015.
[3] A. v and S. S. Manakattu, "Neighbour Aware Random Sampling (NARS) algorithm for load balancing in Cloud computing," IEEE, 2015.
[4] B. Wadhwa and A. Verma, "Carbon Efficient VM Placement and Migration Technique for Green Federated Cloud Datacenters," IEEE, pp. 2297-2302, 2014.
[5] C. Qiu, H. Shen and L. Chen, "Towards Green Cloud Computing: Demand Allocation and Pricing Policies for Cloud Service Brokerage," IEEE, pp. 203-2012, 2015.
[6] Chakradhara Rao and Mogasala Leelarani,”Cloud: Computing Services and Deployment Models,”IJECS, pp.1-4, 2013.
[7] D.C. Ketan kumar, G.Verma and K. Chandrasekaran” A Green Mechanism Design Approach to Automate Resource Procurement in Cloud,” ELSEVIER, pp.108-117, 2015.
[8] Eduard Oró VictorDepoorter, AlbertGarcia and JaumeSalom,”Energy efficiency and renewable energy integrationin data centres. Strategies and modeling review, “ELSEVIER, pp.1-17, 2015.
[9] F. Farahnakian, T. Pahikkala, P. Liljeberg, J. Plosila and H. Tenhunen, "Utilization Prediction Aware VM Consolidation Approach for Green Cloud Computing," IEEE, pp. 381-388, 2015.
[10] H. Leia, T. Zhanga, Y. Liub, Yabing Zhaa and X .Zhub “Smart green energy efficient scheduling strategy with dynamic electricity price for data center, “ELSEVIER, pp.23-38, 2015.
[11] Harmanpreet Kaur, Jasmeet Singh Gurm,” A Survey on the Power and Energy Consumption of Cloud,” IJCST,
[12] H. Rong ,H. Zhang , S. Xiao, Canbing Li and Chunhua Hu “Optimizing energy consumption for data centers ,”ELSEVIER ,pp.1-18 , 2015.
[13] Í. Goiri , Md E. Haque , Kien Le , R. Beauchea , T.D. Nguyen , J.Guitart , J.Torres , R. Bianchini ,” Matching renewable energy supply and demand in green datacenters ,” ELSEVIER , pp. 520-534 ,2015 .
[14] J.Srinvas and K.Venkatasubba,”Cloud Computing Basics,” IJARCCE, pp.1-5, July-2012.
[15] Kenneth Ganfield and Alyona Stashkova,”Developing Application with NetBeans IDE,”November, 2013.
[16] L. A. Rocha and E. Cardozo, "A Hybrid Optimization Model for Green Cloud Computing," IEEE, pp. 11-20, 2014.
[17] Lars Vogel and Simon Scholz(c),”Introduction to java-Programming Tutorial,” 2008, 2016 vogella Gmbh.
[18] M. B. Nagpure, P. Dahiwale and P. Marbate, "An Efficient Dynamic Resource Allocation Strategy for VM Environment in Cloud," IEEE, 2015.
[19]M. Giacobbe, A. Celesti, M. Fazio, M. Villari and A. Puliafito, "An Approach to Reduce Carbon Dioxide Emissions Through Virtual Machine Migrations in a Sustainable Cloud Federation," IFIP, 2015.
[20] M. S. Hasan, Y. Kouki, T. Ledoux and J. L. Pazat, "Exploiting Renewable sources: when Green SLA becomes a possible reality in Cloud computing," IEEE, pp. 1-14, 2015.
[21] Ms.S.Gowri#1 Mr.V.Harikrishnan#2 “Analyzing Power Consumption using Local Cooling,”IJETT, pp.1-5, 2014.
[22] Mohammad Oquil Ahmad and Dr. Rafiqual Zaman Khan,” The Cloud Computing: A Systematic Review,” IJIRCCE, pp.1-10, May, 2015.
[23] M. Yakhchi, S. M. Ghafari, S. Yakhchi, M. Fazeli and A. Patooghi, "Proposing a Load Balancing Method Based on Cuckoo Optimization Algorithm for Energy Management in Cloud Computing Infrastructures," IEEE, 2015.
[24] N. Dehouche, "A Bi-criteria Algorithm for Low-Carbon and QoS-Aware Routing in Cloud Computing Infrastructures," IEEE, 2015.
[25] Oracle CEO Larry Ellison, “Cloud Computing Basics," pp.1-20
[26] Rahul Bhoyar and Nitin Chopde,”Cloud Computing Service, Models, Types, Database and issue,” IJARCSSE, pp.1-7, 2013.
[27] Rohini Sharma,”Approaches of Green Computing,” IJICSE, pp.52-55, July-August-2015.
[28] S.Chen, S.Irving, and Lu Peng” Operational Cost Optimization for Cloud Computing
Data Centers Using Renewable Energy,”IEEE, pp.1-12, 2015.
[29] S.Kumar and R.H.Goudar,”Cloud Computing – Research issue, Challenges, Architecture, Platforms, IJFCC, pp.1-5, 2012.
[30] Saurabh Kumar Garg and Rajkumar Buyya, "Green Cloud computing and Environmental Sustainability,"pp.1-27.
[31] S. P. Reddy and C. H K S, "Energy Aware Scheduling of Real-Time and Non Real-Time Tasks on Cloud Processors," ICICES2014 - S.A.Engineering College, Chennai, Tamil Nadu, India, 2014.
[32] S. Roy and S. Gupta, "The Green Cloud Effective Framework: An Environment Friendly Approach Reducing CO2 Level," Proceedings of 2014 1st International Conference on Non-Conventional Energy (ICONCE 2014), pp. 233-236, 2014.
[33] S.R. Sivarasu, E.Chandira Sekaran and P. Karthik “Development of renewable energy based micro grid project implementations for residential consumers in India: Scope, challenges and possibilities,” ELSEVIER, pp.256-269, 2015.
[34] S. Yakhchi, S. Ghafari, M. Yakhchi, M. Fazeli and A. Patooghy, "ICA-MMT: A Load Balancing Method in Cloud Computing Environment," IEEE, 2015.
[35] Torry harris,” CLOUD COMPUTING – An Overview,” pp. 1-6.
[36] Wanqing You, Kai Qian and Ying Qian,”Hierarchical Queue –Based Task Scheduling,” JACN, vol.2, pp.1-4.
[37] Yibin Li, Min Chen,” Energy Optimization with Dynamic Task Scheduling Mobile Cloud Computing,” IEEE, pp.1-10, 2015.
[38] Y. E. Fernandas and M. Vasanthi, "Energy Efficient Mechanism for Green Computing n Wireless Storage Area Networks," IEEE, pp. 1311-1314, 2015.
[39] Y Edwin Fernandas and M.S. Vasanthi,” Energy Efficient Mechanism for Green Computing in Wireless Storage Area Networks,” IEEE, pp.1-4, 2015.
[40] Y.-J. Chiang, Y.-C. Ouyang and h.-H. Hsu, "An Efficient Green Control Algorithm in Cloud Computing for Cost Optimization," IEEE, pp. 1-14, 2013.
Published
2017-10-22
How to Cite
KAUR, Sukhbhinder; GHUMMAN, Mr. Navtej Singh. A NOVEL APPROACH OF TASK CLASSIFICATION AND VM SKEWNESS IN CLOUD ENVIRONMENT. INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY, [S.l.], v. 16, n. 7, p. 6994-7001, oct. 2017. ISSN 2277-3061. Available at: <http://cirworld.com/index.php/ijct/article/view/6416>. Date accessed: 21 nov. 2017. doi: https://doi.org/10.24297/ijct.v16i7.6416.
Section
Articles

Most read articles by the same author(s)

1 2 > >>