GRD Journals | Global Research and Development Journal for Engineering | International Conference on Innovations in Engineering and Technology (ICIET) - 2016 | July 2016
e-ISSN: 2455-5703
Tracking Coordinated and Adaptive Information using Security from Target Wireless Sensor Network 1P.
Ramya 2M. Satheesh Kumar 3M. Kaveri 1,3 P.G Student 2Assistant Professor 1,2,3 Department of Information Technology 1,2,3 K.L.N. College of Engineering, Pottapalayam, Sivagangai 630612, India Abstract Wireless sensor network (WSNs) consist of sensor node with sensing and communication capabilities. The important problem of WSNs applications is Energy conservation. Clustered sensor network uses cluster heads (CHs) for data gathering. In Target tracking applications, sensor nodes in multiple clusters do not uses a single target path, which leads to redundant data transmissions from CHs to the sink so much energy is to waste. In this paper we propose coordinated and adaptive information collecting strategy (CAICS) for Target tracking in clustered WSNs. In CAICS a coordinated node selection method considering the spatial correlation of sensing nodes is proposed to dynamically select the best set of nodes for tracking missions. And an adaptive aggregation node is selected for data collection to reduce the redundant data transmission and balance the energy cost. Experimental results exhibit that the proposed approach reduces the computational complexity of node selections without degrading tracking accuracy and achieves a significant energy consumption reduction and network lifetime extension compared with the state-of-the-art approaches. Keyword- Energy Conservation, WSNs, Clustered sensor network, Target tracking, Adaptive, CAICS __________________________________________________________________________________________________
I. INTRODUCTION WIRELESS sensor networks (WSNs) have emerged as an gorgeous technology which can consist of large number of cerebral sensor nodes. With sensing, processing and wireless communicating capabilities.[2] In WSNs, one of important applications is target tracking, such as vehicle tracking and migration tracking of animals. [3] The sensor nodes collectively monitor the roaming path of moving targets in the deployed area. Since the sensor nodes are always deployed in an unattended environment, it is very difficult to replace their battery after the deployment. As a result, energy efficiency is the most critical design issue for WSNs. In a target tracking application, the sensor nodes which can sense the target at a particular time are kept in active mode while the remaining nodes are to be retained in inactive mode so as to conserve energy until the target approaches them. Clustering is an important approach to organize a closely deployed network. The clustering algorithms keep only a portion of nodes (CHs) active and save the energy for the rest of the nodes. [1].The target will often be detected by the nodes in multiple clusters at the same time. When all the nodes report their data to the respective CHs, each involved CH has to send the data to the sink. This way may produce much redundant data that causes unnecessary energy consumption. The data gathering approaches for clustered WSNs can be categorized into: DL-cluster [5] and MH-cluster [13].In DL-cluster each CH aggregates the sensed data from its Cluster Members (CMs) and directly transmits it to the sink, while in MH-cluster a hierarchical CHs model is built and the data can be aggregated hop by hop through multiple intermediate CHs. These approaches are not efficient for target tracking because of redundant data transmissions. A simple 5-cluster sensor network is taken as an example in Fig. 1. In Fig. 1(a), CH1, CH2 and CH3 obtain the sensed data from their CMs and send them to the sink respectively. We can see that there are 3 data flows from CHs to the sink. In Fig. 1(b), CH1 and CH3 send the aggregated data to CH2 which further aggregates the data. Therefore, there is only one data flow from CH2 to the sink. However, when the target moves to the position shown in Fig. 1(c), two data flows are established from CH2 and CH4 to the sink, because CH3 always transmits its data to CH2 and CH5 to CH4. If we want to change their transmission routes dynamically according to the position of the moving target, a lot of communications among CHs are needed. It will cause more energy cost and time delay. With these motivations, we propose a coordinated and adaptive information collecting strategy (CAICS) for target tracking in clustered WSNs. The major objective of CAICS is to reduce the redundant data transmission and keep a reliable object tracking with minimum energy consumption.
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