Improved Response Time and Energy Management for Mobile Cloud Computing Using Computational Offloading

Author:

S. Raj Dr. Jennifer

Abstract

The mobile devices capabilities are found to be greater than before by utilizing the cloud services. There are various of service rendered by the cloud paradigm and the mobile devices usually allows the execution of the resource-intensive applications on the resource- constrained mobile device to be offloaded to the cloudlets that are resource rich thus enhancing the its processing capabilities. But accessing the cloud services within the minimum response time and energy consumption still remains as a serious research problem. So the proposed method put forth in the paper scopes in developing a frame work to choose the optimal cloud service provider. The frame work proposed is categorized into two stages where the initial stage engages the classifier to segregate the mobile device according to the fuzzy K-nearest neighbor and cultivates an improved computational offloading employing the Hidden Markov Model and ACO- ant colony optimization. The algorithm proffered is implemented in the MATLAB version 9.1 and the performance is evinced on the basis of the response time, energy consumption and the processing cost. The results obtained through the proposed method proves to provide an 89% better response time, 95 % better energy consumption and 50% enhanced processing cost compared to the few existing computational offloading methods put forth for the mobile cloud computing.

Publisher

Inventive Research Organization

Cited by 21 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. An Associate Degree Algorithmic for Computation offloading in Mobile Cloud Computing;2023 International Conference on Computational Intelligence, Communication Technology and Networking (CICTN);2023-04-20

2. Analysis of Data Sequence Mining and Electronic Imaging Systems;2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC);2022-11-10

3. Computation Offloading in Mobile Cloud Computing and Mobile Edge Computing: Survey, Taxonomy, and Open Issues;Mobile Information Systems;2022-06-28

4. An Efficient Heterogeneous Framework Technique for Optimizing Energy in Green Cloud Computing;2022 6th International Conference on Trends in Electronics and Informatics (ICOEI);2022-04-28

5. Implementation of Dynamic Resource Allocation using Adaptive Fuzzy Multi-Objective Genetic Algorithm for IoT based Cloud System;2022 4th International Conference on Smart Systems and Inventive Technology (ICSSIT);2022-01-20

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