RARE: An Energy Efficient Target Tracking Protocol For Wireless Sensor Networks

Wireless sensors provide great potential for us to learn about our environment through monitoring and are used in various fields such as military and commercial applications.Target tracking is one application of wireless sensor networks and when designing protocols for target tracking in wireless sensor networks some issues to consider include single vs.multiple target tracking,types of nodes used in the network i.e.homogenous or heterogeneous,use of predictive or non-predictive tracking and energy efficiency of the protocol.Energy efficient target tracking algorithms that can be used for accurate tracking are highly desirable and in order to achieve energy savings,our research is focused on two issues regarding tracking data in wireless sensor networks:low quality data and repeated or redundant data.Regarding low quality data,we know that noise affects the signal being received from the target and as the distance between the target and sensor increases,the percentage of noise in the signal generally also increases.If we limit our tracking to only high quality data i.e.data with less noise from sensors nearer the target,then we can limit the number of sensors tracking a target and so conserve energy.In a randomly distributed wireless sensor network there is a high probability of overlapping sensing areas which means repeated/redundant data is sent to the cluster head.Reducing the amount of repeated/redundant data being sent to the cluster head also provides us with energy savings.We propose an energy efficient target tracking protocol that uses two algorithms; the RARE-Area(Reduced Area REporting)algorithm to address the issue of low quality data and the RARE-Node(Reduction of Active Node REdundancy)algorithm to address the issue of redundant or repeated data.The RARE-Area algorithm limits the number of sensors used for tracking by only allowing sensors that have a given quality of data to participate in tracking. When a sensor detects a target,it runs the RARE-Area algorithm and determines a weight W for its data.If the calculated weight W≥W_U where W_U is the threshold weight,then the sensor can participate in tracking.When calculating a weight for the sensor data there are two factors that are considered:a target distance factorα_d and a target motion factorα_m. The target distance factorα_d uses the target distance to approximate the quality of the signal being received from the target and maps the relationship between the target distance factorα_d and the target distance as a zero mean Gaussian distribution. The further away a target is from the sensor,the lower the quality of its data and hence the lower the value of the distance factor.The target motion factorα_m(m,s),however,is used to control the frequency of data transmissions and its effectiveness depends on the set weight threshold.The motion factor is used to reduce the probability that a sensor will forward data to the cluster head at the same rate when a target is stationary in its sensing area.We modify the frequency of data transmissions to the cluster head according to the target motion characteristics i.e.reduces the frequency when the target is stationary and increases the frequency when the target is moving.The RARE-Node algorithm reduces the amount of redundant data being sent to the cluster head.This algorithm considers the spatial relationship between two neighboring sensors to determine overlapping sensing areas and ensures that if a target is located in such an area between two neighboring sensors,only one of them will forward data to the cluster head.Energy savings using our protocol are obtained from reduction of the number of sensors involved in tracking,reduction in the frequency of transmission of data to the cluster head and also from reducing the amount of redundant data in the network. From our simulation results,energy savings that can extend the network lifetime up to 35%have been observed with a low to medium weighting threshold W_U i.e.W_U＜=0.3 and application of both algorithms.With this weighting,the effect on target tracking accuracy is not too negative.Also observed is that the target motion characteristics determine the best motion factor ratio to allocate for a target in motion and a target at rest and if the weighting threshold W_U is too low,and only the RARE-Area algorithm is implemented,no energy savings are obtained.