Geometric Constraint Based Range Free Localization Scheme For Wireless Sensor Networks (WSNs)

Localization of the wireless sensor networks (WSNs) is an emerging area of research. The accurate localization is essential to support extended network lifetime, better covering, geographical routing, and congested free network. In this thesis, we proposed four distributed range-free localization schemes. The proposed schemes are based on the analytical geometry, where an arc is used as the geometric primitive shape. The simulation and experimental validation are performed to evaluate the performance of the proposed schemes. First, we have proposed a mobile beacon based range-free localization scheme (MBBRFLS). The proposed scheme resolved the two underlying problems of the constraint area based localization: (i) localization accuracy depends on the size of the constraint area, and (2) the localization using the constraint area averaging. In this scheme, the constraint area is used to derive the geometric property of an arc. The localization begins with an approximation of the arc parameters. Later, the approximated parameters are used to generate the chords. The perpendicular bisector of the chords estimate the candidate positions of the sensor node. The valid position of the sensor node is identified using the logarithmic path loss model. The performance of proposed scheme is compared with Ssu and Galstyan schemes. From the results, it is observed that the proposed scheme at varying DOI shows 20.7% and 11.6% less localization error than Ssu and Galstyan schemes respectively. Similarly, at the varying beacon broadcasting interval the proposed scheme shows 18.8% and 8.3% less localization error than Ssu and Galstyan schemes respectively. Besides, at the varying communication range, the proposed scheme shows 18% and 9.2% less localization error than Ssu and Galstyan schemes respectively. To further enhance the localization accuracy, we have proposed MBBRFLS using an optimized beacon points selection (OBPS). In MBBRFLS-OBPS, the optimized beacon points minimized the constraint area of the sensor node. Later, the reduced constraint area is used to differentiate the valid or invalid estimated positions of the sensor node. In this scheme, we have only considered the sagitta of a minor arc for generating the chords. Therefore, the complexity of geometric calculations in MBBRFLS-OBPS is lesser than MBBRFLS. For localization, the MBBRFLS-OBPS use the perpendicular bisector of the chords (corresponding to the sagitta of minor arc) and the approximated radius. The performance of the proposed MBBRFLS-OBPS is compared with Ssu, Galstyan, and Singh schemes. From the results, it is observed that the proposed scheme using CIRCLE, vii SPIRAL, HILBERT, and S-CURVE trajectories shows 74.68%, 78.3%, 73.9%, and 70.3% less localization error than Ssu, Galstyan, and Singh schemes respectively. Next, we have proposed MBBRFLS using an optimized residence area formation (ORAF). The proposed MBBRFLS-ORAF further improves the localization accuracy. In this scheme, we have used the adaptive mechanism corresponding to the different size of the constraint area. The adaptive mechanism defines the number of random points required for the different size of the constraint area. In this scheme, we have improved the approximation accuracy of the arc parameters even at the larger size of the constraint area. Therefore, the localization accuracy is improved. The previous scheme MBBRFLS-OBPS use the residence area of the two beacon points for approximation. Therefore, the larger size of the constraint area degrades the approximation accuracy. In the MBBRFLS-ORAF, we have considered the residence area of the three non-collinear beacon points, which further improves the localization accuracy. The performance of the proposed scheme is compared with Ssu, Lee, Xiao, and Singh schemes. From the results, it is observed that the proposed MBBRFLS-ORAF at varying communication range shows 73.2%, 48.7%, 33.2%, and 20.7% less localization error than Ssu, Lee, Xiao, and Singh schemes respectively. Similarly, at the different beacon broadcasting intervals the proposed MBBRFLS-ORAF shows 75%, 53%, 38%, and 25% less localization error than Ssu, Lee, Xiao, and Singh schemes respectively. Besides, at the varying DOI the proposed MBBRFLS-ORAF shows 76.3%, 56.8%, 52%, and 35% less localization error than Ssu, Lee, Xiao, and Singh schemes respectively. Finally, we have proposed a localization scheme for unpredictable radio environment (LSURE). In this work, we have focused on the radio propagation irregularity and its impact on the localization accuracy. The most of the geometric constraint-based localization schemes suffer from the radio propagation irregularity. To demonstrate its impact, we have designed an experimental testbed for the real indoor environment. In the experimental testbed, the three static anchor nodes assist a sensor node to perform its localization. The impact of radio propagation irregularity is represented on the constraint areas of the sensor node. The communication range (estimated distance) of the anchor node is derived using the logarithmic regression model of RSSI-distance relationship. The additional error in the estimated distances, and the different placement of the anchor nodes generates the different size of the constraint areas. To improve the localization accuracy, we have used the dynamic circle expansion technique. The performance of the proposed LSURE is compared with APIT and Weighted Centroid schemes using the various deployment scenarios of the anchor nodes. From the results, it is observed that the proposed LSURE at different deployment scenarios of anchor nodes shows 65.94% and 73.54% less localization error than APIT and Weighted Centroid schemes

Localization in Wireless Sensor Networks

The technique of nding physical co-ordinates of a node is known as localization. Importance of localization arises from the need to tag the sensed data and associate events with their location of occurrence. Location information of a sensor node can be obtained by using GPS. But, installing GPS in every node is not a feasible solution. This is because: (i) sensor nodes are deployed in a very large number. Installing GPS at every node will increase the cost as well as size, (ii) GPS consume power, which will effect the network lifetime. Moreover, location cannot be pre-programmed as it is un-known where nodes will be deployed during their operational phase. In this thesis, we have made an attempt to address localization in static as well as mobile sensor networks. For static network we have proposed two distributed range based localization techniques called (i ) Localization using a single anchor node (LUSA), (ii ) Dis- tributed binary node localization estimation (DBNLE). Both the techniques are proposed for grid environment. In LUSA, we have identied three types of node: anchor, special and unknown node. For every anchor node there exists two special node and they are placed perpendicular to the anchor node. Localization in LUSA is achieved by a single anchor node and two special nodes. Localization occurs in two steps. First special nodes are localized and then the unknown nodes. We have compared LUSA with a closely related localization technique called Multi-duolateration (MDL). It is observed that the localization error and localization time is lesser in LUSA. In DBNLE a node is localized with only two location aware nodes instead of three nodes in most localization techniques. This not only reduces the localization time but also the dependency. For mobile WSNs, we have proposed a distributed localization technique called dead reckoning localization in mobile sensor networks (DRLMSN). In DRLMSN, localization is done at discrete time intervals called checkpoint. Unknown nodes are localized for the rst time using three anchor nodes. In their subsequent localization, only two anchor nodesare used. Using Bezouts theorem, we estimate two possible locations of a node. A dead reckoning approach is used to select one among the two estimated locations. We have used Castalia simulator to evaluate the performance of the schemes