P. Balakrishnan ¹, A. Umamakeswari ¹, R. Kaviya ¹

Affiliations
1 School of Computing, SASTRA University, Thanjavur - 613401, Tamil Nadu, IN

Abstract

Objectives: This research work proposes a methodology for estimating the energy consumption of tasks by considering processor and memory usage. Methods: To facilitate energy efficiency in CPU, the mobile devices may be operated at different frequencies during the execution of tasks. This research work applies CPU frequency scaling as its base to achieve energy efficiency. Besides, it also considers energy consumption during memory access while making the offloading decision. Findings: The proposed approach uses energy consumption during computation as well as memory access as its metric to conceive the offloading decision. Additionally, the proposed energy model is simulated and the results are concluded that there is a considerable amount of energy saving in mobile devices due to computation offloading to nearby mobile devices or cloud resources. Applications: To save energy decide which application in mobile as energy consume considered as model. The models work as code offloading in MATLAB and determine by two level genetic algorithms. The efficiency of proposed model is evaluated by a simulation and average energy result can be concluded for a mobile device.

Keywords

Frequency Scaling, Mobile Cloud Computing, Offloading, Task Interaction Graph.

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M. Sharmila ¹, P. Balakrishnan ¹

Affiliations
1 School of Computing, SASTRA University, Thirumalaisamudram, Thanjavur - 613401, Tamilnadu, IN

Abstract

Background/Objectives: This research work reviews different techniques to protect the data and discussed about their merits and demerits which help to realize a secured cloud deduplication environment. Methods: Hybrid cloud based deduplication approach is proposedto avoid the data duplication and to ensure the confidentiality in the cloud. Further, the security investigations ensure that the proposed security framework enhances the data security with an insignificant additional overhead. Mention the data source accessed and keywords used; inclusion and exclusion criteria etc. Findings: Provide your findings. Applications: This approach makes us to understand the elements of good cloud deduplication framework which can be directly used by any cloud storage service provider to reduce their storage costs.

Keywords

Cloud Computing, Data Deduplication, Hybrid Cloud, Private Cloud, Public Cloud.

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