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A Prediction based Dynamic Tracking Algorithm For Wireless Sensor Networks

Sanaei Asl, Arman | 2020

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 53279 (19)
  4. University: Sharif University of Technology
  5. Department: Computer Engineering
  6. Advisor(s): Hemmatyar, Ali Mohammad Afshin; Jahangeri, Amir Hossein
  7. Abstract:
  8. Recently, advances in the fabrication and integration of sensing, communication technologies and economical deployment of large scale sensor networks which are capable of large scale target tracking, become possible.therfore, the wireless sensor networks are a fast growing and marvelous research area that has attracted considerable research attention in the recent past. The creation of large-scale sensor networks interconnencting several hundered to a few thousand sensor nodes opens-up several wide range of application and technical challenges. Sensor nodes have been deployed to play significant roles in battlefield, disaster-prone area, traffic control, habitat monitoring and intruder tracking. One of the most important application of these networks is target tracking. In this application, wireless sensor networks consisted of many sensor nodes which are used to sense, detect a target and track that target until it goes out of the monitored field. Because of the nodes have limitation of energy consumption and Existance of multiple targets in real Enviroment, Power consumption and multiple target tracking issues are of great important. The target tracking algorithm can be mainly classify into four schems, such as message-based tracking, tree-based tracking, prediction-based tracking and cluster-based tracking. Among them, the cluster-based tracking protocols are more energy efficient and hence, many protocols are reported to solve the energy consumption problem, such as CRTA, DPT and CDDTA. The proposed algorithm uses a prediction-based clustering approach for scalable and cluster-based tracking mechanism to provide a distributed and energy efficient solution. The algorithm is robust against both node and prediction failure which may result in temporary loss of the target. Futher to that, a novel Error Correction procedure is executed to recover lost target quickly. The lost target occurs when the target changes it direction or speed so abruptly that it moves significant away from the predicted location and falls out of the detectable area. The simulation results show that in comparison with the existing algorithm is able to track multiple target with random way point model more accurately over a wide of target speed. Furthermore, the proposed algorithm reduced communicatin that transmits between clusters and hence, energy consumption in our algorithm is extermly efficient. Therefore, the network’s lifetime is extended when compared with the existing algorithms
  9. Keywords:
  10. Network Model ; Wireless Sensor Network ; Scalability ; Target Tracking Problem ; Error Correction ; Dynamic Target Tracking ; Energy Consumption Reduction

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