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A Mutual Energy Harvesting-induced Task Offloading Method for Wireless Sensor Networks coupled with the Internet of Things
Vasim Babu M, Gurumoorthy K B and Allwin Devaraj S
Conventional wireless networks form the smallest portion of the Internet of Things (IoT) paradigm for communication, information exchange, and device integrations. The energy dependency of the wireless networks is applicable for IoT, however, the resource constraint issues are addressed using intelligent techniques in this platform. This article introduces a Mutual Energy Harvesting-induced Task Offloading (MEHTO) for addressing the energy-constrained issue in conventional sensor networks. The offloading in IoT is used for balancing the energy management across the sensor networks coupled with IoT. The changes in network operations based on energy are recurrently analyzed using transfer learning. The active and drain states of the network are analyzed using available nodes, communication rate, and replacement delay. Depending on these attributes, the EH support from the IoT devices is formulated for maximizing energy-based service failures. In a critical non-harvesting drain state, the nodes/ network portion is released due to which the existing (pending) tasks are offloaded. With the further EH post the offloading, the network operations are restarted with the active state. The state changes are frequently monitored for reducing service disconnections and permanent node (network) failures. Therefore, recurrent state learning is reliable in identifying the need for offloading conserving energy, and preventing service failures. The proposed method is expected to improve the energy harvesting rate and reduce energy utilization, service failures, offloading time, response delay, and offloading ratio.
Keywords: Energy Harvesting, IoT, Sensor Network, Task Offloading, Transfer Learning