Optimized Job Scheduling Algorithm in Cloud Computing Environment
Shyam Sunder Pabboju1, G.Nagi Reddy2, P.Satya Shekar Varma3, K.Nikhil Kumar4

1Shyam Sunder Pabboju*, Assistant Professor, CSE, JNTUH, MGIT, Hyderabad,
2G.Nagi Reddy, Assistant Professor, CSE, JNTUH, MGIT, Hyderabad, India.
3P.Satya Shekar Varma, Assistant Professor CSE, JNTUH, MGIT, Hyderabad, India.
4K.Nikhil Kumar, student, CSE, JNTUH, MGIT, Hyderabad.
Manuscript received on March 15, 2020. | Revised Manuscript received on April 01, 2020. | Manuscript published on April 10, 2020. | PP: 2236-2239 | Volume-9 Issue-6, April 2020. | Retrieval Number: F3901049620/2020©BEIESP | DOI: 10.35940/ijitee.F3901.049620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: There is a strong trend towards cloud technologies in the SME(Small and Medium Enterprises) sector, largely due to cost reduction, capex availability, and sometimes by collaboration features. Now a days so many startup companies are getting emerged and for them buying the resources for one time usage it becomes more expensive so they are preferring to using the cloud services(SLA) to overcome all this problems. In Cloud computing it essential to check weather a resource is available for allocating or not and allocating the jobs for the clients request is the big task. There are many job scheduling algorithm already proposed by the researchers to implement in cloud environment. After studying there algorithm we have came up with the most effective job scheduling algorithm. It is totally depending on Size and Arrival time of the job. By implementing our proposed algorithm we can obtain the better optimal solution to improve the overall performance of the system and gives more effective results compared to other job scheduling algorithms. 
Keywords: Cloud Computing, Job Scheduling, Performance, Quality of Service, Virtualization
Scope of the Article: Cloud Computing and Networking