Multi-Path Routing Protocol with Unavailable Areas Identification in Wireless Sensor Networks

Gao, Deyun; Yang, O.W.W.; Zhang, Hongke; Chao, Han-Chie

doi:10.1007/s11277-011-0301-z

Cited by 9 publications

(6 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Also, we can see that when the moving direction of the object changes significantly, the estimation error will increase. In points (15,20), (5,15), and (38, 25), the estimation errors become larger apparently.…”

Section: Experimental Results and Analysis Of Object Trackingmentioning

confidence: 97%

“…We put the calibration board in the monitor area and choose four points for calibrating. The coordinations of these four points are (12.8, 29.8), (5, 29.8), (41,5), and (5,5). Then, similarly, we can use the information of these four points to compute the homographic matrix In the experiment, the object moves along the predefined path.…”

Section: Experimental Results and Analysis Of Object Trackingmentioning

confidence: 99%

“…In the calibration board, the coordinates of four reference nodes are (29, 60), (66, 60), (66, 33), and (30, 32.5). With these reference nodes, the homographic matrix can be obtained in Equation (5).…”

Section: The Developed Ordinary Sensor Node and Camera Sensor Nodementioning

confidence: 99%

“…Object localization and tracking aim at confirming the position, movement direction of object, which has become a popular application specially in military and civil aspects, such as monitor and control, navigation, and so on . The information gathered by sensors is meaningful only with the presence of position information, which also can help to improve routing efficiency, coverage performance, and so on . Localization is the process of determining the position of an object in space.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A hybrid localization and tracking system in camera sensor networks

Gao

Zhu

et al. 2012

Int J Communication

Self Cite

View full text Add to dashboard Cite

SUMMARYPosition information is of vital importance in the various applications in energy-constrained wireless sensor networks. It has to design a localization mechanism considering both precision and energy consumption factors. In this paper, we propose a hybrid localization system in wireless sensor networks, which is composed of coarse-grained localization system and fine-grained localization system. The coarse-grained localization system takes the wireless signal strength as the reference for distance and gets the rough region as the unknown node. The fine-grained localization system is in charge of location refinement that takes image to localize the unknown node with camera sensor nodes. On the basis of the hybrid localization system, we furthermore design a hybrid tracking system for localizing a moving object. Finally, we build up a test bed to conduct experiments with our developed sensor network. The experiment results show that the proposed hybrid localization and tracking system can achieve high position precision and low energy consumption.

show abstract

Section: Experimental Results and Analysis Of Object Trackingmentioning

confidence: 97%

Section: Experimental Results and Analysis Of Object Trackingmentioning

confidence: 99%

Section: The Developed Ordinary Sensor Node and Camera Sensor Nodementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A hybrid localization and tracking system in camera sensor networks

Gao

Zhu

et al. 2012

Int J Communication

Self Cite

View full text Add to dashboard Cite

show abstract

“…An energy efficient treebased routing protocol for data aggregation tree-clustered data-gathering protocol (TCDGP) is proposed in [14] which avoid the root node from dying rapidly. Recently, Gao et al proposed a micro sensor multi-path routing protocol (MSMRP) in [15]. In this paper, the authors design a neighbour node table exchanging mechanism that can help build an alternate route around the unavailable areas and try to avoid the multiple paths intersect.…”

Section: Related Workmentioning

confidence: 99%

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

Bhatti¹,

Memon²,

Jokhio³

et al. 2012

IET Commun.

View full text Add to dashboard Cite

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.

show abstract

Multi-path Reliable Routing with Pipeline Schedule in Wireless Sensor Networks

Zhang

Guo

et al. 2016

Wireless Algorithms, Systems, and Applications

View full text Add to dashboard Cite

Multi-Path Routing Protocol with Unavailable Areas Identification in Wireless Sensor Networks

Cited by 9 publications

References 14 publications

A hybrid localization and tracking system in camera sensor networks

A hybrid localization and tracking system in camera sensor networks

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

Multi-path Reliable Routing with Pipeline Schedule in Wireless Sensor Networks

Contact Info

Product

Resources

About