A Survey of Target Tracking Algorithm Based on Potts-Model of Wireless Sensor Networks
|School||Central China Normal University|
|Course||Computer System Architecture|
|Keywords||Wireless Sensor Networks Potts-Model Targets Tracking 2Step-LeastSquare Optimization algorithm A-SAS algorithm energy consumption|
Wireless Sensor Networks is one kind of the Ad hoc, and its wide application prospects makes it become research hot spot in recent years. Due to its special characteristics, reducing the energy consumption and tracking the targets, for example, are the core issue of the survey task. No matter in military or in civilian aspects, the wireless sensor nodes are very suited for tracking moving targets of the networks. The typical application in these case such as intrusion detection, disaster relief and vehicle tracking. Based on the energy condition of the wireless sensor networks consumes, the network will collapse and stop working if there are some nodes out of energy in advance. To reduce the energy consumption of the sensor nodes and tracking the moving targets in the network, this article proposed a more accurate and efficient algorithm. we use the theoretical research methods and emulational experiment installations, in order to improve the utilization ratio of the energy that the sensor nodes carries and prolong the network lifetime. All these researches are based on the Potts-Model of the wireless sensor networks.The main contents of research in this article are as follows:1.Introduced the background and the derivation process of Potts-Model. As we already know that Ising-Model is to study the phase changes in physics, Potts-Model is an Ising-like-Model. Using an Ising-like formulation, the sleep and wake modes of a sensor node are modeled as spins with ferromagnetic neighborhood interactions; and clique potentials are defined to characterize the node behavior. the threshold voltage is used to describe the characteristics of the node behaviour. This paper uses the features of this model to tracking targets in the wireless sensor networks.2.Briefly analyze the Adaptive Sensor Activity Scheduling (A-SAS) algorithm in distributed sensor networks to enable detection and dynamic footprint tracking of spatial-temporal events that proposed by Abhishek Srivastav. Individual sensor nodes are designed to make local probabilistic decisions based on the most recently sensed parameters and the expected behavior of their neighbors. The proposed algorithm Abhishek proposed naturally leads to a distributed implementation without the need for a centralized control. 3.Proposed a guaranteed tracking targets trajectory precision and more energy saving algorithm, according to the energy consumption characteristics of wireless sensor networks. It is called2Step-Least Square Optimization target localization algorithm. Refers to the2Step, first step is to distribute the weights according to the signal strength and estimate a series of the target location information, the second step is using the Least Squares estimate the best position.4.Compared A-SAS algorithm and the2Step-Least Square Optimization target localization algorithm, the latter which is aimed at improving the target location accuracy and reducing the network computing costs. And the simulation results show the latter algorithm is more practicable.