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

Bhatti, Sania; Memon, Aasma; Jokhio, Imran Ali; Memon, Mohsin Ali

doi:10.1049/iet-com.2011.0246

Cited by 5 publications

(5 citation statements)

References 22 publications

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“…The usability of this approach is also analysed considering a smart grid scenario. Bhatti et al (2012) This probabilistic model of target-tracking WSNs 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.…”

Section: Clusteringmentioning

confidence: 99%

Investigation on different clustering techniques in wireless sensor networks

Meenatchi

Prabu

2018

IJAIP

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In the recent years, we have witnessed hyperbolic interest within the potential use of wireless sensor networks (WSNs) in an exceedingly wide selection of applications like area observation, healthcare observation, pollution observation, fire detection, landslide detection, natural disaster hindrance, machine health observation, etc., it is become a hot research space. To support high scalability and higher knowledge aggregation, sensor nodes are typically sorted into disjoint, non-overlapping subsets known as clusters. Clusters produce stratified WSNs that incorporate economical utilisation of restricted resources of sensor nodes and so extends network period. Specifically, we will examine the performance in terms of the ability and quality aspects of those schemes. We tend to conjointly discuss enhancements to be created for future planned cluster schemes. Finally, we tend to summarise and conclude the paper with some future directions.

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Section: Clusteringmentioning

confidence: 99%

Investigation on different clustering techniques in wireless sensor networks

Meenatchi

Prabu

2018

IJAIP

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“…The cluster head module communicates with snetwork module and snetwork module communicate with sensor node module. The detailed states and transitions contained in modules of FTTT, coding for development of parallel combination of sensor nodes, cluster heads and a target are presented in our work [22]. Authors in [22] also presented modules with synchronized events and value relationship of variables during modeling.…”

Section: International Journal Of Computer Theory and Engineering Vomentioning

confidence: 99%

“…The detailed states and transitions contained in modules of FTTT, coding for development of parallel combination of sensor nodes, cluster heads and a target are presented in our work [22]. Authors in [22] also presented modules with synchronized events and value relationship of variables during modeling. PRISM transforms these modules into a multi-terminal binary decision diagram (MTBDD) representation, performs computation of set of entire reachable states and eliminates unreachable states.…”

Section: International Journal Of Computer Theory and Engineering Vomentioning

confidence: 99%

Evaluating FTTT Protocol via PRISM, PRISM-symm and GRIP

Bhatti¹,

Memon²,

Memon³

2017

IJCTE

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Abstract-Probabilistic model checking is used for verifying stochastic behaviors of systems. Model checking plays imperative role for scrutinizing of novel protocols in almost every field including computer communications, networks, security, and biology prior to extensive simulations. In this paper we present an overview of few diverse case studies which are implemented using one of the leading probabilistic symbolic models checking tool, called Probabilistic Symbolic Model ( I. INTRODUCTIONProbabilistic model checking is one of the most popular verification methods useful to accomplish accuracy evaluation which is otherwise intricate and time consuming to attain via simulations now a days. This type of model checking is used for formal verification related to the quantitative properties of stochastic behaviors of systems. Probabilistic model checking is related to the construction and scrutiny of a probabilistic model from a high-level description of a system's behavior. Model analysis is performed by specifying one or more quantitative properties which are stated in temporal logic. These properties help to measure correctness of the system along with reliability andAlthough a number of probabilistic and hybrid model checking tools are being successfully employed by researchers [6] excess deployment in diverse domains. In this paper, an overview of varying protocols verified via PRISM is presented. Section II discusses about PRISM model checker and the models it supports. Section III presents eleven different communication protocols which have been verified via PRISM. Section IV specifies a case study of FTTT protocol. Finally, Section V states concluding remarks. II. PRISM MODEL CHECKERPRISM is an open source probabilistic model checker and available to run on the majority of operating systems. The website of PRISM [1] developed at University of Oxford offers its download, tutorials, a huge repository of publications and case studies. It supports Discrete Time Markov Chain (DTMC), Markov Decision Process (MDP), Continuous Time Markov Chain (CTMC) and probabilistic timed automata. The system models are stated in a high level language via guarded command mutation which is based on reactive modules formalism. A set of modules representing the components of a system constitutes a PRISM model and each module comprises of states and transitions. States represent the possible configuration of the system and transitions correspond to change of states relating to time. PRISM performs model checking by expressing properties in PCTL, CSL and LTL. To specify additional quantitative measures, costs and rewards are added to the properties. Fig. 1 illustrates the two main parts of a system specification in PRISM: the model and the properties. PRISM provides results in either log form or in the form of a graph [2], [3]. PRISM has capability to work out quantitative measures corresponding to model behaviour such as expected time for transmission, expected total transmission energy. To specify these measures, it makes use of...

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“…These cluster-based target tracking protocols were proposed almost with the same motivation that the cluster schemes can well trade-off between the energy efficiency and the tracking quality. A probabilistic model for studying the relationships of cluster-based fault tolerant targettracking protocol was reported in Bhatti et al (2012). However, such protocols have not quantitatively divided the underlying relationship between the clustering schemes and the system performances.…”

Section: Cluster-based Target Trackingmentioning

confidence: 99%

On optimisation of cluster-based sensor network tracking system

Wang

Zhao

Zheng

et al. 2013

IJAHUC

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Tracking mobile targets using low-cost Wireless Sensor Network (WSN) requires not only good tracking accuracy but also network longevity. Cluster-based tracking protocols leverage the fact that only sensors in the vicinity of the target can contribute to target detection, while other sensors should sleep to save energy, which provides good tradeoff between energy efficiency and tracking accuracy. However, for the complexity of cluster-based tracking protocols, it is challenging to quantify the tradeoff between energy efficiency and tracking accuracy. In this paper, a convolution-based method is presented to quantify the relationship between the cluster parameters and the energy-quality metrics of the tracking system, which provides Pareto optimal parameters to jointly optimise the energy efficiency and the tracking accuracy of cluster-based WSN tracking system. The presented results are verified in popular cluster-based tracking protocols via extensive simulations, which shows the effectiveness of the optimisation framework.

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

Cited by 5 publications

References 22 publications

Investigation on different clustering techniques in wireless sensor networks

Investigation on different clustering techniques in wireless sensor networks

Evaluating FTTT Protocol via PRISM, PRISM-symm and GRIP

On optimisation of cluster-based sensor network tracking system

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