Mobility Profiling Using Markov Chains for Tree-Based Object Tracking in Wireless Sensor Networks

Yen, Li-Hsing; Yang, Chia-Cheng

doi:10.1109/sutc.2006.92

Cited by 12 publications

(7 citation statements)

References 8 publications

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“…Heuristic based on Markov-model [15] using geometric information determined by Voronoi diagram assigns the weights to nodes. A tree construction algorithm based on a maximum spanning tree [15], registers saving of message transmissions in the object tracking based on crossing rates between nodes. The mobility models independent to object mobility profile becomes interest to our work.…”

Section: B Mobility Profile Independent Object Trackingmentioning

confidence: 99%

Location tracking of fast-paced mobile entity using CDS for VANETs

Misra

Baveja

2010

The 7th IEEE International Conference on Mobile Ad-Hoc and Sensor Systems (IEEE MASS 2010)

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Location tracking of mobile entity becomes a research challenge for applications in vehicular networks, mobile sensor networks and mobile adhoc networks. The GPS based tracking in vehicular networks has limitations in certain scenarios such as inside tunnels, tall buildings, dense forests, etc. Tracking of fast-paced mobile entity (say mobile node) finds applications in vehicular networks such as chasing, hit-and-run accidents, etc. Connected dominating set(CDS) provides a virtual backbone in adhoc network. This paper uses connected dominating set(CDS) based virtual backbone in vehicular adhoc networks for tracking of fast-paced mobile node's location. We show that using a simple heuristics that the location updates for mobile node can be reduced to the tune of 40%.

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Section: B Mobility Profile Independent Object Trackingmentioning

confidence: 99%

Location tracking of fast-paced mobile entity using CDS for VANETs

Misra

Baveja

2010

The 7th IEEE International Conference on Mobile Ad-Hoc and Sensor Systems (IEEE MASS 2010)

View full text Add to dashboard Cite

show abstract

“…Heuristic based on Markov-model [15] using geometric information determined by Voronoi diagram assigns the weights to sensor nodes. A tree construction algorithm based on a maximum spanning tree [15], registers saving of message transmissions in the object tracking based on crossing rates between sensors. The mobility models independent to object mobility profile becomes interest to our work.…”

Section: B Mobility Profile Independent Object Trackingmentioning

confidence: 99%

“…The mobility models independent to object mobility profile becomes interest to our work. We also use Markov-model independent to mobility-profile but difference between [15] and our proposed Markov model lies in heuristics. The object tracking method based on Markov-model reported in [15] used geometric information based on Voronoi diagram for modeling mobility profile.…”

Section: B Mobility Profile Independent Object Trackingmentioning

confidence: 99%

“…We also use Markov-model independent to mobility-profile but difference between [15] and our proposed Markov model lies in heuristics. The object tracking method based on Markov-model reported in [15] used geometric information based on Voronoi diagram for modeling mobility profile. Weight determination for CDS in our approach is also based on Markov model but differs from [15] in heuristics of neighborhood set information.…”

Section: B Mobility Profile Independent Object Trackingmentioning

confidence: 99%

“…The object tracking method based on Markov-model reported in [15] used geometric information based on Voronoi diagram for modeling mobility profile. Weight determination for CDS in our approach is also based on Markov model but differs from [15] in heuristics of neighborhood set information. Other difference with [15] lies in consideration of node mobility.…”

Section: B Mobility Profile Independent Object Trackingmentioning

confidence: 99%

See 2 more Smart Citations

Location Updates of Mobile Node in Wireless Sensor Networks

Misra

Mandal

2009

2009 Fifth International Conference on Mobile Ad-Hoc and Sensor Networks

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The mobility of nodes with a purpose called as robotic-mobility is used for replenishing energy to strategic military applications. Connected dominating set(CDS) provides a virtual backbone in adhoc network. Assuming a CDS based backbone in place, we give a technique of maintaining the location of mobile node for a given topology setting. We show that using a weighted CDS reduces the maintenance of location updates for mobile node. The complexity of our mobilenode maintanence algorithm is at most O(d. log d) where d is number of boundary crossings in the single node's movement. The simulation shows that our weighted CDS method for mobile-nodes achieve 40% reduction in location maintenance using to shortest-hop path in CDS.

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An efficient location tracking structure for wireless sensor networks

Chen

Wang

2009

Computer Communications

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Mobility Profiling Using Markov Chains for Tree-Based Object Tracking in Wireless Sensor Networks

Cited by 12 publications

References 8 publications

Location tracking of fast-paced mobile entity using CDS for VANETs

Location tracking of fast-paced mobile entity using CDS for VANETs

Location Updates of Mobile Node in Wireless Sensor Networks

An efficient location tracking structure for wireless sensor networks

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