Secured and Dynamic Decentralized Computational Offloading Framework for Mobile Cloud Computing
Shanthi AL1, Ramesh V2
1Shanthi AL., Research Scholar, SCSVMV, Kanchipuram
2Ramesh V., Asst Professor, SCSVMV, Kanchipuram
Manuscript received on 25 August 2019. | Revised Manuscript received on 07 September 2019. | Manuscript published on 30 September 2019. | PP: 2589-2593 | Volume-8 Issue-11, September 2019. | Retrieval Number: K18760981119/2019©BEIESP | DOI: 10.35940/ijitee.K1876.0981119
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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: Mobile Cloud Computing is represented as an advanced mobile computing technique by integrating with resource rich servers of various clouds and networks towards infinite mobility, computation, functionality and storage in favour to overcome the restrictions of mobile devices. Mobile Cloud Computing is a platform where storing and processing of data are performed away from mobile devices and processed in the cloud and bringing back results to mobile device to improve the capabilities of mobile devices. The main objective of this study is to minimize response time and to improve the battery performance of mobile devices. In this research, an intelligent secure and dynamic decentralized framework is proposed which will provide accurate decision for execution environment for the application either local or at cloud using SENN classifier and DCNN Model. Modified Fuzzy C Means Clustering algorithm is put forward to create alike clusters for the profiler parameters information collected by smonitor. Moreover, the proposed framework provides more security by encrypting the input image data while transferred to cloud server using blowfish technique can protect the application data from threats. The test results in simulation environment proved that SDCNN framework achieved significant performance by minimizing the consumption of energy and execution time by offloading computation intensive task to clouds.
Keywords: Mobile Clouds, Offloading, Decision Making, Decentralized resource allocation, Clustering, Energy Consumption.
Scope of the Article: Mobile Cloud Computing and Application Services