Dynamic sensor selection for target tracking in wireless sensor networks
- Authors: Armaghani, Farzaneh , Gondal, Iqbal , Kamruzzaman, Joarder
- Date: 2011
- Type: Text , Conference paper
- Relation: IEEE 74th Vehicular Technology Conference, VTC Fall 2011; San Francisco, United States; 5th-8th September 2011 p. 1-6
- Full Text: false
- Reviewed:
- Description: Optimum selection of sensors in target tracking applications has a great potential to maintain right trade-off between energy consumption and quality of tracking. In this paper, we propose a dynamic sensor selection scheme to achieve energy efficiency while ensuring the required quality of tracking. To this end, relative information utility projection of a target on sensors' observation is used in niche overlap measurements. Niche overlap measures are used to assess the similarity in information utilities where information utility is inversely proportional to error in target's state estimation based on prior distribution. The proposed scheme is a greedy approach in which sensor nodes are selected such that the overall niche overlap of all the selected nodes is maximized until the required level of accuracy is achieved. Our simulation results show significant improvement in tracking accuracy and network's lifetime over the existing methods.
Dynamic sensors collaboration to balance the accuracy-lifetime trade-off in multiple-target tracking
- Authors: Armaghani, Farzaneh , Gondal, Iqbal , Kamruzzaman, Joarder , Green, David
- Date: 2012
- Type: Text , Conference paper
- Relation: 2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2012; Sydney, NSW; Australia; 9th-12th September 2012 p. 675-681
- Full Text: false
- Reviewed:
- Description: Complex target tracking applications require active sensor nodes to collaboratively track multiple moving targets, which can balance the trade-off between the quality of tracking and network's lifetime. In this paper, we develop a distributed sensor-selection protocol (DSSP) to activate dynamic number of sensors based on the cost metrics. Cost metrics contains energy-aware leadership cost and eagerness-based tracking cost; which selects sensors with higher energy resources and information utilities. DSSP enables an even distribution of energy consumption among the nodes to prolong the network lifetime. Our results show that the proposed scheme can significantly improve the network lifetime while maintaining the high tracking accuracy as compared to the other schemes.
Dynamic clusters graph for detecting moving targets using WSNs
- Authors: Armaghani, Farzaneh , Gondal, Iqbal , Kamruzzaman, Joarder , Green, David
- Date: 2012
- Type: Text , Conference paper
- Relation: 76th IEEE Vehicular Technology Conference, VTC Fall 2012; Quebec City, Canada; 3rd-6th September 2012 p. 1-5
- Full Text: false
- Reviewed:
- Description: Efficient target tracking applications require active sensor nodes to track a cluster of moving targets. Clustering could lead to significant cost improvement as compared to tracking individual targets. This paper presents accurate clustering of targets for both coherent and incoherent movement patterns. We propose a novel clustering algorithm that utilises an implicit dynamic time frame to assess the relational history of targets in creating a weighted graph of connected components. The proposed algorithm employs key features of localisation algorithms in target tracking, namely, estimated current and predicted locations to determine the relational directions and distances of moving targets. Our simulation results show a significant improvement on the clustering accuracy and computation time by dynamically adjusting the history-window size and predicting the relationships among targets.
Sensor selection for tracking multiple groups of targets
- Authors: Armaghani, Farzaneh , Gondal, Iqbal , Kamruzzaman, Joarder , Green, David
- Date: 2014
- Type: Text , Journal article
- Relation: Journal of Network and Computer Applications Vol. 46, no. (2014), p. 36-47
- Full Text: false
- Reviewed:
- Description: Group target tracking is a challenge for sensor networks. It occurs where large numbers of closely spaced targets move together in different groups. In these applications, the sensor selection scheme plays a vital role in extending network lifetime while providing high tracking accuracy. Existing schemes cause an extreme imbalance between energy usages and tracking accuracy. They are capable of tracking only individual groups and without using prior knowledge about the groups. These problems make them impractical for group target tracking. With the aim of balancing the trade-off between lifetime and accuracy, we present a novel Multi-Sensor Group Tracking (MSGT) scheme. MSGT comprises the following steps to accomplish concurrent tracking of multiple groups: (1) Clustering to capture changes in the behavioural properties of groups, such as formation, merging, and splitting; (2) Sensor selection to activate the contributory sensors for the estimated group regions; and (3) Group tracking using the activated sensors. We develop a probabilistic decision-making strategy that triggers the clustering step adaptively with any detected change in group behavioural patterns. The sensor selection step coordinates periodic selection of leader and tracking sensor nodes in a distributed manner. We introduce cost metrics that include sensor′s energy parameters in the selection of active sensors that fully cover the group regions. The tracking step is a Bayesian modelling of the target groups which uses particle filtering algorithm to estimate the group locations. Simulation results show that our scheme achieves substantial improvements over existing approaches in terms of network lifetime and tracking accuracy.
Dynamic sensors selection for overlapped multiple-target tracking using eagerness
- Authors: Armaghani, Farzaneh , Gondal, Iqbal , Kamruzzaman, Joarder
- Date: 2012
- Type: Text , Conference paper
- Relation: 76th IEEE Vehicular Technology Conference, VTC Fall 2012; Quebec City, Canada; 3rd-6th September 2012 p. 1-6
- Full Text: false
- Reviewed:
- Description: Efficient target tracking applications use active sensor nodes collaboratively to track multiple moving targets by balancing the trade-off between the quality of tracking and network's lifetime. In this paper, we propose a low-energy dynamic sensor selection (LEDS) scheme to track multiple targets by estimating energy consumption of sensors and information utility projection of the targets on sensors to calculate the eagerness in tracking. Eagerness represents the eligibility of a sensor node to be selected for tracking, considering relative profiles of other sensors and location of all the targets in its vicinity. LEDS enables an even distribution of energy consumption among the nodes to prolong their remaining energies. Our results show that the proposed scheme can significantly improve the network lifetime over the existing methods while maintaining the high tracking accuracy in congested areas where multiple concurrent targets overlap.