Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/6730
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dc.contributor.authorTewari, Prateek-
dc.contributor.authorGupta, Punit [Guided by]-
dc.date.accessioned2022-09-26T06:39:47Z-
dc.date.available2022-09-26T06:39:47Z-
dc.date.issued2017-
dc.identifier.urihttp://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/6730-
dc.description.abstractMonkey search algorithm is a task scheduling algorithm in which we schedule tasks by allocating them to resources.In this project resources are designated as virtual machines(or mountains) and tasks are designated as cloudlets(or monkeys).Earlier many task scheduling algorithms are proposed to improve the performance but are not cost efficient at the same time.PSO and ACO are efficient solutions but not cost efficient.So to overcome the issues I have proposed learning based cost efficient algorithm for cloud infrastructure. In early proven task scheduling algorithms network cost is not included but in my proposed MSA network overhead or cost is taken into consideration which thus improves the efficiency of the algorithm as compared to previous algotithms.I have made comparison of my proposed MSA with FCFS algorithm as well as with ACO. Also I have used cloud simulation which is a framework of modeling and simulation of cloud computing infrastructures and sevices and real time as well as local cloud environment. The poposed MSA works well and is much improved in terms of efficiency and execution cost.en_US
dc.language.isoenen_US
dc.publisherJaypee University of Information Technology, Solan, H.P.en_US
dc.subjectCloud iaasen_US
dc.subjectMonkey searchen_US
dc.titleMonkey Search Algorithm Based Task Scheduling in Cloud Iaasen_US
dc.typeProject Reporten_US
Appears in Collections:B.Tech. Project Reports

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