Energy Efficient Load Balancing Strategy for Better Cost Of Multisite Offloading
DOI:
https://doi.org/10.26438/ijcse/v6i8.882889Keywords:
Mobile offloading, ACO, greedy algorithm, cost optimizationAbstract
Cloud computing is the latest paradigm for providing many types of facilities that are suitable to transfer the data or any other information from the resource constraint devices. It is the delivery of computing services. Various services are servers, storage, database, software, networking and analytics over the network.. A lot of frameworks have stated the features of mobile cloud computing and challenges faced during its operational activities along with the concept of load balancing and offloading. Computation offloading can reduce the load during mobile computing. Load balancing is a concept that is used in the well allocation of resources to provide complete satisfaction of user during the remote processing of the mobile application. They are saving a lot of energy and enhance the performance of mobile devices. A lot of research work has been carried out on a single site offloading, but there is a need to carry out work on cost minimization in multisite offloading.. This proposed work provides better cost in case of various information centres using Ant Colony Optimization (ACO).We used ACO algorithm to minimize the cost of virtual machines of different sites. Matlab Simulation Tool has been used to perform cost optimization using ACO and greedy algorithms considering the deadline. Both ACO and Greedy algorithm have been compared by simulation in MATLAB in order to optimize the costs. The proposed methodology has been evaluated on two cloud services namely Amazon and Microsoft Azure for cost minimization and the results shows that the ACO is better as compared to compare to greedy approach for minimization of cost.
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