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IJSTR >> Volume 8 - Issue 11, November 2019 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Energy-Efficient And Improved Qos -Driven Task Scheduling Algorithm In Mcc Environment Using Cloudsim Simulator

[Full Text]



Dr.G.Anandharaj, K.Suganthi



Mobile Cloud Computing, QoS, Genetic Algorithm, Differential Evolution, Energy-efficient, Task Scheduling.



As an evolving and prospective computing paradigm, mobile cloud computing (MCC) can significantly improve computing capacity and save energy from intelligent mobile devices. Because of some intrinsic mobile device defects, such as restricted battery power, inadequate storage space, and mobile apps, many mobility management problems, quality of service (QoS), energy management, and safety problems are faced. A mobile device implementation is known as Task. The main focus of the task scheduling is to improve the effective use of resources and thus reduce the completion time of the task. This research explores relative analysis of energy-efficient and improved QoS-driven tasks Scheduling (E2IQDTS) algorithms for optimizing multi-objective problem in a Mobile Cloud Computing Environment scheduling parameters such as Makespam, Dynamic Offloading, Deadline-satisfied, Task Length, Priority, Delay-Sensitive, etc. Evolutionary algorithms such as Genetic Algorithm (GA), Genetic Programming (GP) and Differential Evolution (DF) are used.



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