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Localized energy efficient detection and tracking of dynamic phenomena

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Localized energy efficient detection and tracking of dynamic phenomena. / Tiwari, R.; Thai, M.T.; Helal, Sumi.

53rd IEEE Global Communications Conference, GLOBECOM 2010. IEEE, 2010.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Tiwari, R, Thai, MT & Helal, S 2010, Localized energy efficient detection and tracking of dynamic phenomena. in 53rd IEEE Global Communications Conference, GLOBECOM 2010. IEEE. https://doi.org/10.1109/GLOCOM.2010.5683257

APA

Tiwari, R., Thai, M. T., & Helal, S. (2010). Localized energy efficient detection and tracking of dynamic phenomena. In 53rd IEEE Global Communications Conference, GLOBECOM 2010 IEEE. https://doi.org/10.1109/GLOCOM.2010.5683257

Vancouver

Tiwari R, Thai MT, Helal S. Localized energy efficient detection and tracking of dynamic phenomena. In 53rd IEEE Global Communications Conference, GLOBECOM 2010. IEEE. 2010 https://doi.org/10.1109/GLOCOM.2010.5683257

Author

Tiwari, R. ; Thai, M.T. ; Helal, Sumi. / Localized energy efficient detection and tracking of dynamic phenomena. 53rd IEEE Global Communications Conference, GLOBECOM 2010. IEEE, 2010.

Bibtex

@inproceedings{d4c20e6319334089938120aa775d24f2,
title = "Localized energy efficient detection and tracking of dynamic phenomena",
abstract = "Dynamic phenomena such as oil spills, mud flow, diffusion or leakage of gases in the environment are characterized by non-deterministic variations in shape, size and direction of motion. Due to the absence of any well defined model for tracking their dynamics, the detection and tracking of such phenomena through Wireless Sensor Networks (WSNs) is very challenging. Most of the existing works consider static phenomena with certain shapes, only few of them study dynamic phenomena. However, existing works studying dynamic phenomena mainly concentrate on reducing the communication overheads and neglect the energy consumed in sensing, which result in higher energy consumption and shorter network lifetime. In this paper, we propose a novel protocol for detection and tracking dynamic phenomena through WSNs, with an objective to minimize the resource usage and energy consumption. We also propose a robust localized clustering method, which helps in reducing the network traffic generated by the information packets destined to a Centralized Query Processor (CQP). The experimental results show that, in comparison to the existing work, our protocol consumes 90% less energy and generates 65% less network traffic. {\textcopyright}2010 IEEE.",
keywords = "Clustering methods, Communication overheads, Detection and tracking, Direction of motion, Dynamic phenomena, Energy consumption, Energy efficient, Information packets, Mud flow, Network lifetime, Network traffic, Query processor, Resource usage, Energy utilization, Oil spills, Telecommunication, Wireless sensor networks",
author = "R. Tiwari and M.T. Thai and Sumi Helal",
year = "2010",
doi = "10.1109/GLOCOM.2010.5683257",
language = "English",
isbn = "9781424456369",
booktitle = "53rd IEEE Global Communications Conference, GLOBECOM 2010",
publisher = "IEEE",

}

RIS

TY - GEN

T1 - Localized energy efficient detection and tracking of dynamic phenomena

AU - Tiwari, R.

AU - Thai, M.T.

AU - Helal, Sumi

PY - 2010

Y1 - 2010

N2 - Dynamic phenomena such as oil spills, mud flow, diffusion or leakage of gases in the environment are characterized by non-deterministic variations in shape, size and direction of motion. Due to the absence of any well defined model for tracking their dynamics, the detection and tracking of such phenomena through Wireless Sensor Networks (WSNs) is very challenging. Most of the existing works consider static phenomena with certain shapes, only few of them study dynamic phenomena. However, existing works studying dynamic phenomena mainly concentrate on reducing the communication overheads and neglect the energy consumed in sensing, which result in higher energy consumption and shorter network lifetime. In this paper, we propose a novel protocol for detection and tracking dynamic phenomena through WSNs, with an objective to minimize the resource usage and energy consumption. We also propose a robust localized clustering method, which helps in reducing the network traffic generated by the information packets destined to a Centralized Query Processor (CQP). The experimental results show that, in comparison to the existing work, our protocol consumes 90% less energy and generates 65% less network traffic. ©2010 IEEE.

AB - Dynamic phenomena such as oil spills, mud flow, diffusion or leakage of gases in the environment are characterized by non-deterministic variations in shape, size and direction of motion. Due to the absence of any well defined model for tracking their dynamics, the detection and tracking of such phenomena through Wireless Sensor Networks (WSNs) is very challenging. Most of the existing works consider static phenomena with certain shapes, only few of them study dynamic phenomena. However, existing works studying dynamic phenomena mainly concentrate on reducing the communication overheads and neglect the energy consumed in sensing, which result in higher energy consumption and shorter network lifetime. In this paper, we propose a novel protocol for detection and tracking dynamic phenomena through WSNs, with an objective to minimize the resource usage and energy consumption. We also propose a robust localized clustering method, which helps in reducing the network traffic generated by the information packets destined to a Centralized Query Processor (CQP). The experimental results show that, in comparison to the existing work, our protocol consumes 90% less energy and generates 65% less network traffic. ©2010 IEEE.

KW - Clustering methods

KW - Communication overheads

KW - Detection and tracking

KW - Direction of motion

KW - Dynamic phenomena

KW - Energy consumption

KW - Energy efficient

KW - Information packets

KW - Mud flow

KW - Network lifetime

KW - Network traffic

KW - Query processor

KW - Resource usage

KW - Energy utilization

KW - Oil spills

KW - Telecommunication

KW - Wireless sensor networks

U2 - 10.1109/GLOCOM.2010.5683257

DO - 10.1109/GLOCOM.2010.5683257

M3 - Conference contribution/Paper

SN - 9781424456369

BT - 53rd IEEE Global Communications Conference, GLOBECOM 2010

PB - IEEE

ER -