Energy Efficient Resource Scheduling Using Optimization Based Neural Network in Mobile Cloud Computing
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Computer Science Applications
Link
https://link.springer.com/content/pdf/10.1007/s11277-020-07448-2.pdf
Reference26 articles.
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2. Chen, M.-H., Dong, M., & Liang, B. (2018). Resource sharing of a computing access point for multi-user mobile cloud offloading with delay constraints. IEEE Transactions on Mobile Computing, 17(12), 2868–2881.
3. Sarkar, J. L., Panigrahi, C. R., Pati, B., Trivedi, R., & Debbarma, S. (2018). E2G: A game theory-based energy efficient transmission policy for mobile cloud computing. In K. Saeed et al. (Eds.), Progress in advanced computing and intelligent engineering, Advances in Intelligent Systems and Computing, (vol. 563). Berlin: Springer. https://doi.org/10.1007/978-981-10-6872-0_65
4. Akki, P., & Vijayarajan, V. (2019). Machine learning algorithm-based minimisation of network traffic in mobile cloud computing. In Proceedings of the 2nd international conference on data engineering and communication technology (pp. 573–584). Berlin: Springer.
5. Chakri, A., Khelif, R., Benouaret, M., & Yang, X.-S. (2017). New directional bat algorithm for continuous optimization problems. Expert Systems with Applications, 69, 159–175.
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