Time-Synchronization Free Localization Scheme with Mobility Prediction for UAWSNs

: Underwater Acoustic Wireless Sensor Network supports a lot of civil and military applications. It has come out as an effective tool to explore the ocean area of the earth. Sensor deployed underwater can help to relate the events occurring underwater with the rest of the world. To achieve the goal, the information gained from the sensors needs to be tagged with their real-time locations. In this paper, we have presents a time-synchronization free localization scheme for underwater networks. The scheme employs a mobile beacon in the network to move vertically and broadcast the beacon messages. The performance evaluation shows that the scheme reduces the error in location estimation caused by the mobility of the sensors by predicting their further location according to the mobility pattern of the sensor node.

Geometric sensitivity of beacon placement using airborne mobile anchors

Locating fixed sensing devices with a mobile anchor is attractive for covering larger deployment areas. However, the performance sensitivity to the geometric arrangement of anchor beacon positions remains unexplored. Therefore, localization using new RSSI-based localization algorithm, which uses a volumetric probability distribution function is proposed to find the most likely position of a node by information fusion from several mobile beacon radio packets to reduce error over deterministic approaches. This paper presents the guidelines of beacon selection that leads to design the most suitable trajectory, as a trade-off between the energy costs of travelling and transmitting the beacons versus the localization accuracy.

Scan and Z-Curve Trajectory for Mobile Anchor in Localization of Wireless Sensor Network

In the recent decades, Wireless Sensor Networks has become an inevitable and dependable research area in the field of communication. Sensor Networks is an apt application for the complicated and instant communication fields like the surveillance in the military services, monitoring of medical analysis and research, detecting forest fire break outs, and detection of acoustics. For an effective application of sensor networks, the research issue shall be laid on the path planning. By path planning it is meant the path through which the mobile beacon should travel without any interruption by enhancing the accuracy in localization process. Of late Global Positioning System (GPS) has become a reliable means for its precision in sensor localization. However, GPS does not provide cost-efficiency or energy-efficiency. As a result, single GPS could be positioned along the travel path. To optimize this constraint, in this paper, an attempt is made to derive the performances of two path planning techniques namely Z-curve and SCAN. It is known that in sensor localizing and for broadcasting of data, the mobile beacon is determined to travel in both directions, viz forward and backward. Comparison is made between the Z-curve trajectory positioned with mobile beacon and SCAN trajectory affixed with mobile beacon having a path planning scheme. The comparison results showed that Z-curve method yielded better performance in terms of high precision and short duration for localization. Further, Z-curve produced only minimum localization error.

Optimal path selection algorithm for mobile beacons in sensor network under non-dense distribution

When the traditional anchor aided location algorithm is used to select the mobile beacon path in the sensor network, there is no analysis of the energy imbalance of nodes in non-dense conditions, the optimal network node cannot be selected, and the selection error of the optimal path of the beacon is larger. A path selection algorithm for mobile beacons in a sensor network under non-dense distribution is proposed. Using the mobile beacon based wireless sensor network location algorithm, the weighted centroid algorithm and the extended Kalman filter (EKF) are used to obtain the accurate location results of the unknown nodes around the mobile beacon in the sensor network under non-dense distribution condition. The optimal node energy partition of the unknown node is obtained by the chaotic differential evolution method, and the optimal location of the optimal energy node in the wireless sensor network is calculated using the dynamic escape particle swarm optimization method, and the optimal beacon path is extracted. The experimental results show that the proposed algorithm can enhance the clustering performance of the optimal node in the wireless sensor network and has a better performance of dynamic node selection in wireless sensor network, and the convergence speed is faster and the operation time is shorter.