Publication

Abstract : Several studies have demonstrated in Wireless Sensor Network for reducing the energy consumption of nodes However, these benefits are dependent on the path taken by the SenCar, particularly in delay-sensitive applications, the sensed data must be collected within a given time constraint. An approach proposed to address this problem is to form a hybrid moving pattern in which a mobile-sink node only visits anchor points, as opposed to all nodes. Sensor nodes that are no anchor point forward their sensed data via multi-hopping to the nearest anchor point. The optimal TSP nearest neighbour algorithm is used for finding the optimal path taken by the SenCar. The new method is proposed for energy transfer mobile collector to sensor nodes by using WerMDG. The simulation result show that the energy consumption is reduced when comber with the existing method. Index Terms-Data collection, mobile sinks, scheduling, wireless sensor networks (WSNs), WerMDG I .INTRODUCTION Wireless sensor networks (WSNs) are composed of a large number of sensor nodes deployed in a field. Some of the applications are military environment monitoring, agriculture, home automation, smart transportation and health. The each sensor node has the capability to collect and process the sensed data, and to forward any sensed data back to one or more sink nodes via their wireless transceiver in a multihop manner. The recent breakthrough in wireless energy transfer technology due to Kurs, et al. [6] has opened up a new dimension to prolonging sensor network lifetime. It was shown in [6] that by exploiting coupled magnetic resonance, it is feasible to transfer energy wirelessly between two coils. Their experiment showed that with this technology it is capable of transferring 60 watts with about 40% efficiency over a distance of 2 meters. Intel has also demonstrated [7] that wireless recharging is effective for transferring 60 watts of power over a distance of up to two to three meters with efficiency of 75%. On the other hand, recent advances in Radio Frequency (RF)-based wireless energy transfer can also increase sustainability of WSNs [8]-[10]. Clearly, wireless energy transfer will have a profound impact on the design of WSNs, which is attributed to its following advantages: (1) it can provide reliable energy without being affected by the dynamics of environments; (2) it eliminates wires or plugs between the charger and receiver; (3) it does not interfere with the normal operations of sensors such as sensing, packets delivering and receiving. The main work of this paper is to provide a distributed and adaptive solution that jointly selects the sensors to be recharged, and finds the optimal data generating and uploading rates and the optimal scheduling and routing paths for each node, and determines the optimal sojourn time for the mobile collector at each anchor point, such that the overall network utility can be maximized. II.RELATED WORK A. Energy Harvesting Networks and Data Collection Prolonging sensor lifetime in energy harvesting/rechargeable networks has recently attracted considerable attention in the wireless networking research community. In [1], [2], the authors proposed solutions for fair and high throughput data extraction in the presence of renewable energy sources, which aims to compute the lexicographically maximum data collection rate for each node. Chen, et al. [3] considered the problem of maximizing throughput over a finite-horizon time period for a sensor network with energy replenishment. Liu, et al. [7] studied the problem of joint energy management and resource allocation in rechargeable sensor networks to maximize network utility while maintaining perpetual operation. In addition, energy harvesting techniques have been considered along with the traditional data collection with a static data sink.