Resource aware and reliable data reporting algorithm for object tracking in WSNs

摘要

Object tracking have become one of the major applications of Wireless Sensor Networks (WSNs) due to its wide real-life applications such as wildlife animal monitoring and military area intrusion detection. Many recent articles have been dedicated to localization of objects; however, few of these articles were concentrated on the reliability of network data reporting along with objects localization. In this work, an efficient data reporting method is proposed for object tracking in WSNs. Energy is considered as one of the most critical resources for WSN. Data transmission from the nodes to the sink along with the minimum energy path could be one of the solutions to minimize the overall network energy consumption. However, this might lead to unbalanced energy among sensor nodes resulting in, energy hole problem. Moreover, the reliable data transmission is an essential aspect that should be considered when designing a WSN for object tracking application, where the loss of data packets will affect the accuracy of the tracking and location estimation of a mobile object. Furthermore, due to the limited memory resources of sensor nodes, full utilization of such resources with less buffer overflow remains as a one of main consideration when a WSN application is designed. Consequently, this paper aims to achieve both minimum energy consumption in reporting operation and balanced energy consumption among sensor nodes for WSN lifetime extension. In addition, data reliability is considered in our model where, the sensed data can reach the sink node in a more reliable way. Finally, buffer space is considered in to reduce the packet loss and energy consumption due to the retransmission of the same packets. This work first formulates the problem as 0/1 Integer Linear Programming (ILP) problem, and proposes SWARM intelligence to solve the optimization problem. Through simulation, the performance of proposed method to report information about the detected objects to the sink is compared with the previous work such as LR-based object tracking algorithm, EBRP, ACO, TADR, SEB, and CLR-Routing.