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D2D communication technology enables the User Equipment (UE) in 5G networks to instantly connect with other UEs, with or without partial infrastructure involvement. In a Cloud Assisted energy harvesting system, it has improved user numbers and data transmission between mobile nodes. This research propose energy harvesting for mobile cloud computing in enhancing the QoS and latency of the network. The main aim of this research is to enhance energy optimization using discrete energy efficient offloading algorithm. The routing has been optimized using fuzzy logic cognitive Bellman-Ford routing algorithm. To identify the failing node and find an alternative node to deliver the seamless services, an unique weight-based approach has been presented. The method relies on two working node parameters: execution time and failure rate. Threshold values are specified for the parameters of the chosen master node. By contrasting the values with the threshold values, the alternative node is chosen. The experimental results shows comparative analysis in terms of throughput of 96%, QoS of 96%, latency of 28%, energy consumption of 51%, end-end delay of 41%, average power consumption of 41% and PDR of 85%
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Xuefei, E., Ma, Z., & Yu, K. (2020). Energy-efficient computation offloading and resource allocation in SWIPT-based MEC Networks. IEEE Access.
Wu, H., Han, X., Zhu, H., Chen, C., & Yang, B. (2022). An Efficient Opportunistic Routing Protocol with Low Latency for Farm Wireless Sensor Networks. Electronics, 11(13), 1936.
Zhao, F., Chen, Y., Zhang, Y., Liu, Z., & Chen, X. (2021). Dynamic offloading and resource scheduling for mobile-edge computing with energy harvesting devices. IEEE Transactions on Network and Service Management, 18(2), 2154-2165.
Xia, S., Yao, Z., Li, Y., & Mao, S. (2021). Online distributed offloading and computing resource management with energy harvesting for heterogeneous MEC-enabled IoT. IEEE Transactions on Wireless Communications, 20(10), 6743-6757.
Ben Ammar, M., Ben Dhaou, I., El Houssaini, D., Sahnoun, S., Fakhfakh, A., & Kanoun, O. (2022). Requirements for Energy-Harvesting-Driven Edge Devices Using Task-Offloading Approaches. Electronics, 11(3), 383.
Guo, M., Li, Q., Peng, Z., Liu, X., & Cui, D. (2022). Energy harvesting computation offloading game towards minimizing delay for mobile edge computing. Computer Networks, 204, 108678.
Hu, H., Wang, Q., Hu, R. Q., & Zhu, H. (2021). Mobility-aware offloading and resource allocation in a MEC-enabled IoT network with energy harvesting. IEEE Internet of Things Journal, 8(24), 17541-17556.
Rahmani, A. M., Mohammadi, M., Mohammed, A. H., Karim, S. H. T., Majeed, M. K., Masdari, M., & Hosseinzadeh, M. (2021). Towards data and computation offloading in mobile cloud computing: taxonomy, overview, and future directions. Wireless Personal Communications, 119(1), 147-185.
Famitafreshi, G., Afaqui, M. S., & Melià-Seguí, J. (2022). Enabling Energy Harvesting-Based Wi-Fi System for an e-Health Application: A MAC Layer Perspective. Sensors, 22(10), 3831.
Song, J., Song, Q., Wang, Y., & Lin, P. (2021). Energy–Delay Tradeoff in Adaptive Cooperative Caching for Energy-Harvesting Ultradense Networks. IEEE Transactions on Computational Social Systems, 9(1), 218-229.
Mahmood, A., Ahmed, A., Naeem, M., Amirzada, M. R., & Al-Dweik, A. (2022). Weighted utility aware computational overhead minimization of wireless power mobile edge cloud. Computer Communications, 190, 178-189.
Bi, H., Shang, W. L., Chen, Y., & Wang, K. (2022). Joint Optimization for Pedestrian, Information and Energy Flows in Emergency Response Systems With Energy Harvesting and Energy Sharing. IEEE Transactions on Intelligent Transportation Systems.
Rani, G. E., Sukumar, G. A., Chandra, T. U., Reddy, K. A., & Sakthimohan, M. (2021, August). Load Allocation as Quality and secured in Mobile Cloud Networking Location. In Journal of Physics: Conference Series (Vol. 1979, No. 1, p. 012045). IOP Publishing.
Abbasi, M., Mohammadi-Pasand, E., & Khosravi, M. R. (2021). Intelligent workload allocation in IoT–Fog–cloud architecture towards mobile edge computing. Computer Communications, 169, 71-80.
Maray, M., & Shuja, J. (2022). Computation Offloading in Mobile Cloud Computing and Mobile Edge Computing: Survey, Taxonomy, and Open Issues. Mobile Information Systems, 2022.
Hamdi, M., Hamed, A. B., Yuan, D., & Zaied, M. (2021). Energy-Efficient Joint Task Assignment and Power Control in Energy-Harvesting D2D Offloading Communications. IEEE Internet of Things Journal, 9(8), 6018-6031.
Xie, Z., Poovendran, P., & Premalatha, R. (2021). Retention based energy harvesting technique for efficient internet of things aided edge devices. Sustainable Energy Technologies and Assessments, 47, 101424.
Shukla, A. K., Upadhyay, P. K., Srivastava, A., & Moualeu, J. M. (2021). Enabling Co-Existence of Cognitive Sensor Nodes with Energy Harvesting in Body Area Networks. IEEE Sensors Journal, 21(9), 11213-11223.
Li, S., Zhang, N., Jiang, R., Zhou, Z., Zheng, F., & Yang, G. (2022). Joint task offloading and resource allocation in mobile edge computing with energy harvesting. Journal of Cloud Computing, 11(1), 1-14.
Kaliappan, V. K., Gnanamurthy, S., Kumar, C. S., Thangaraj, R., & Mohanasundaram, K. (2021). Reduced power consumption by resource scheduling in mobile cloud using optimized neural network. Materials Today: Proceedings, 46, 6453-6458.