Analysis of Cluster based Target Tracking in Wireless Sensor Networks

Abstract

Wireless Sensor Networks (WSNs), is one of the most emerging technologies in recent years. Signal processing between sensor nodes to the base station is most important task for these networks. Target tracking in WSN mainly focuses on localization and object tracking. This paper addresses various cluster based target tracking techniques in wireless sensor networks. To support reliability, energy efficiency and efficient routing, nodes are often grouped into clusters. The clusters can be formed before the intrusion enters the network which is called the static method or clusters are created by using signal strength from target which is called the dynamic method. This paper gives a various cluster based target tracking methods for efficient target tracking in WSN.

Object Tracking in Wireless Sensor Networks: Challenges and Solutions

“…Instead of reporting to a centralized sink node, cluster members are to report to their cluster head only, which aggregate data and subsequently report to the sink node. To that end, clustering is considered as a hierarchical architecture (Abbasi and Younis, 2007;Gopal and Krishnamoorthy, 2013) that is efficiently used to minimize energy consumption in WSNs when transmitting data from all sensors to the sink node (Heinzelman et al, 2002).…”

“…If a cluster head goes down, for battery depletion for example, all the sensors in the cluster become useless. Second and due to fixed membership, sensor nodes in different clusters cannot share information and collaborate on data processing (Gopal and Krishnamoorthy, 2013). Finally, fixed membership prevents the adaptability to dynamic scenarios in which nodes in the region of high (low) event concentration may stay active (go to sleep) state (Li and Zhou, 2011).…”

“…3. When a sensor, hopefully the one that is the nearest to the object or the one with the highest energy, detects an object, it volunteers to play the role of a cluster head (Abbasi and Younis, 2007;Gopal and Krishnamoorthy, 2013). Typically, multiple sensor nodes may detect the event of interest so multiple volunteers may exist.…”

“…Furthermore, since only one cluster is active within the vicinity of the object with high probability, redundant data are suppressed, leading to better tracking quality. Furthermore, energy consumption is reduced since one cluster is active at a time in accordance to object movement (Gopal and Krishnamoorthy, 2013).…”