Sania Bhatti

Survey of Target Tracking Protocols Using Wireless Sensor Network

Target tracking is one of the non trivial applications of wireless sensor network which is set up in the areas of field surveillance, habitat monitoring, indoor buildings, and intruder tracking. Various approaches have been investigated for tracking the targets, considering diverse metrics like scalability, overheads, energy consumption and target tracking accuracy. This paper for the first time contributes a survey of target tracking protocols for sensor networks and presents their classification in a precise manner. The five main categories explored in this paper are, hierarchical, tree-based, prediction- based, mobicast message-based tracking and hybrid methods. To be more precise, the survey promotes overview of recent research literature along with their performance comparison and evaluation based on simulation with real data. Certainly this task is challenging and not straight forward due to differences in estimations, parameters and performance metrics, therefore the paper concludes with open research challenges.

Clustering and fault tolerance for target tracking using wireless sensor networks

Using wireless sensor networks to track a moving object provided a practical solution to a wide variety of applications including, for example, wild life, military operations, intruder tracking and monitoring in indoor office buildings. While much work has been done in this area, failures are not considered in most of the existing solutions. However, failures have to be handled carefully in target tracking applications because of their unpredictable and dynamic nature of communication, such as sensor energy depletion, severe environment conditions, unstable communication links and malicious attacks. Traditional approaches of fault tolerance are not well suited to address these new challenges. Therefore the authors propose a novel fault-tolerant target tracking (FTTT) protocol based on clustering. Also, the results of an investigation in terms of performance overheads and scalable nature of the FTTT protocol via comparative simulations with LEACH are discussed. Overall, in all the cases, FTTT consumes at least 25% less energy than LEACH.

Energy-aware fault-tolerant clustering scheme for target tracking wireless sensor networks

Over the last few years, the deployment of wireless sensor networks (WSNs) has been fostered in diverse applications. WSN has great potential for a variety of domains ranging from scientific experiments to commercial applications. Due to the deployment of WSNs in dynamic and unpredictable environments, these applications must have potential to cope with variety of faults. This paper proposes an energy-aware fault-tolerant clustering protocol for target tracking applications termed as the Fault-Tolerant Target Tracking (FTTT) protocol. The identification of redundant nodes (RNs) makes sensor node (SN) fault tolerance plausible and the clustering endorsed recovery of sensors supervised by a faulty cluster head (CH). The FTTT protocol intends two steps of reducing energy consumption: first, by identifying RNs in the network; secondly, by restricting the numbers of SNs sending data to the CH. Simulations validate the scalability and low power consumption of the FTTT protocol in comparison with LEACH protocol.

Model Checking of a Target Tracking Protocol for Wireless Sensor Networks

Dense collection of tiny Sensor Nodes (SNs), equipped with a variety of sensors are able to sense events, compute and communicate the estimations to the end user, form a distributed Wireless Sensor Network (WSN). The advances in WSNs have made it plausible to appraise critical aspects of object tracking WSNs that are continuous monitoring of object track and fault tolerance. This paper presents probabilistic performance evaluation of clustering, redundancy reduction, target tracking and fault tolerance phases of Fault-Tolerant Target Tracking (FTTT) protocol. This type of formal modeling with limited number of SNs helps to plan a scalable network with specific constraints related to the application, for example, object tracking quality, life time of the network, energy consumption, latency, QoS and network throughput.

Modelling and symmetry reduction of a target-tracking protocol using wireless sensor networks

To achieve precise modelling of real-time systems stochastic behaviours are considered which lead towards probabilistic modelling. Probabilistic modelling has been successfully employed in wide array of application domains including, for example, randomised distributed algorithms, communication, security and power management protocols. This study is an improvement over our previous work, which was based on the probabilistic analysis of a cluster-based fault tolerant target-tracking protocol (FTTT) using only grid-based sensor nodes arrangement. Probabilistic modelling is chosen for the analysis of FTTT protocol to facilitate benefits of symmetry reduction in conjunction with modelling. It is believed that for the first time correctness of the simplified version of a target-tracking protocol is verified by developing its continuous-time Markov chain (CTMC) model using symbolic modelling language. The proposed probabilistic model of a target-tracking wireless sensor networks will help to analyse the phases of FTTT protocol on a limited scale with finite utilisation of time. There are three main contributions of this study; first consideration of synchronised events between the modules, second, random placement of sensor nodes is taken into account in addition to grid-based sensor node arrangement, third one is the reduction in state space size through symmetry reduction technique, which also facilitates to analyse a larger size network. Symmetry reduction on Probabilistic Symbolic Model (PRISM) checker models is performed by PRISM-symm and the generic representatives in PRISM (GRIP) tool. Modelling of FTTT protocol is proved better with the usage of PRISM-symm after comparing the results of PRISM model, PRISM-symm and GRIP.