Publication Type : Conference Paper
Publisher : International Conference on Computing, Power and Communication Technologies (GUCON), IEEE
Source : International Conference on Computing, Power and Communication Technologies (GUCON), pp. 837-844, IEEE, 2019.
Url : https://ieeexplore.ieee.org/abstract/document/8940534
Campus : Coimbatore
School : School of Computing
Year : 2019
Abstract : Wireless sensor networks (WSNs) are the set of autonomous sensor nodes scattered in the physical environment to monitor the events and communicates with a base station to process crude information. The tiny sensor node accommodated a limited disposable battery and a small memory device. So that efficient energy management and data gathering are required to operate the sensor adequately long time and avoiding the data losses. There are several energy-efficient and data aggregation protocols in the literature, however, it is still a challenging issue. Many algorithms are proposed for solving the problem using mobile elements for separate data collection and recharging for WSNs. There are few approaches to joint recharging and data collection operation, but each having their own limitations. We introduce an efficient mobile element scheduling algorithm based on vertex coverage to perform the joint recharging and data collection of sensor nodes. Proposed algorithm efficiently schedules the mobile element based on the residual energy and available data of each sensor node in the network. It visits a few nodes in the network and performs the recharging and data aggregation operation on the nodes which are in the range of mobile element. With the simulation runs, we found that the proposed method increases network lifetime, by reducing the data loss and dead nodes.
Cite this Research Publication : B Sanjai Prasada Rao, Divya Singh, Tarachand Amgoth, "Joint wireless charging and data collection using mobile element for rechargeable wsns," International Conference on Computing, Power and Communication Technologies (GUCON), pp. 837-844, IEEE, 2019.