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Using association rules for energy conservation in wireless sensor networks

Research output: Contribution to conferencePaperpeer-review

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Using association rules for energy conservation in wireless sensor networks. / Chong, S.; Krishnaswamy, S.; Loke, S.; Gaber, M.

2008. 971-975 Paper presented at Proceedings of the 2008 ACM Symposium on Applied Computing, Fortaleza, Ceara, Brazil.

Research output: Contribution to conferencePaperpeer-review

Harvard

Chong, S, Krishnaswamy, S, Loke, S & Gaber, M 2008, 'Using association rules for energy conservation in wireless sensor networks', Paper presented at Proceedings of the 2008 ACM Symposium on Applied Computing, Fortaleza, Ceara, Brazil, 16/03/08 - 20/03/08 pp. 971-975.

APA

Chong, S., Krishnaswamy, S., Loke, S., & Gaber, M. (2008). Using association rules for energy conservation in wireless sensor networks. 971-975. Paper presented at Proceedings of the 2008 ACM Symposium on Applied Computing, Fortaleza, Ceara, Brazil.

Vancouver

Chong S, Krishnaswamy S, Loke S, Gaber M. Using association rules for energy conservation in wireless sensor networks. 2008. Paper presented at Proceedings of the 2008 ACM Symposium on Applied Computing, Fortaleza, Ceara, Brazil.

Author

Chong, S. ; Krishnaswamy, S. ; Loke, S. ; Gaber, M. / Using association rules for energy conservation in wireless sensor networks. Paper presented at Proceedings of the 2008 ACM Symposium on Applied Computing, Fortaleza, Ceara, Brazil.5 p.

Bibtex

@conference{1fdd6c98c8384883aa592bb5886726f7,
title = "Using association rules for energy conservation in wireless sensor networks",
abstract = "Frequent radio transmissions among sensors, or from sensors to the basestation, have always been a major energy drain. One of the approaches to reduce the data transmitted to the basestation is to shift the bulk of data processing to networked sensor nodes; for instance, sensors to send only data aggregates to reduce the overall amount of data exchanged. Sensor nodes, however, are quite limited in terms of their energy and processing power, and as such, traditional centralised data mining algorithms are infeasible to be directly implemented on sensors. In this paper, we modify APRIORI to find strong rules from sensor readings in a sensor network and using these rules, autonomously control sensor network operations or supplement sensor operations with a rule knowledge base. For example, triggers activated from the rules could be used to sleep sensors or reduce data transmissions to conserve sensor energy. Our work here includes a detailed implementation of a lightweight rule learning algorithm for a resource-constrainted sensor network, with simulation results for a group node setup running the algorithm.",
author = "S. Chong and S. Krishnaswamy and S. Loke and M. Gaber",
year = "2008",
month = mar,
day = "16",
language = "English",
pages = "971--975",
note = "Proceedings of the 2008 ACM Symposium on Applied Computing ; Conference date: 16-03-2008 Through 20-03-2008",

}

RIS

TY - CONF

T1 - Using association rules for energy conservation in wireless sensor networks

AU - Chong, S.

AU - Krishnaswamy, S.

AU - Loke, S.

AU - Gaber, M.

PY - 2008/3/16

Y1 - 2008/3/16

N2 - Frequent radio transmissions among sensors, or from sensors to the basestation, have always been a major energy drain. One of the approaches to reduce the data transmitted to the basestation is to shift the bulk of data processing to networked sensor nodes; for instance, sensors to send only data aggregates to reduce the overall amount of data exchanged. Sensor nodes, however, are quite limited in terms of their energy and processing power, and as such, traditional centralised data mining algorithms are infeasible to be directly implemented on sensors. In this paper, we modify APRIORI to find strong rules from sensor readings in a sensor network and using these rules, autonomously control sensor network operations or supplement sensor operations with a rule knowledge base. For example, triggers activated from the rules could be used to sleep sensors or reduce data transmissions to conserve sensor energy. Our work here includes a detailed implementation of a lightweight rule learning algorithm for a resource-constrainted sensor network, with simulation results for a group node setup running the algorithm.

AB - Frequent radio transmissions among sensors, or from sensors to the basestation, have always been a major energy drain. One of the approaches to reduce the data transmitted to the basestation is to shift the bulk of data processing to networked sensor nodes; for instance, sensors to send only data aggregates to reduce the overall amount of data exchanged. Sensor nodes, however, are quite limited in terms of their energy and processing power, and as such, traditional centralised data mining algorithms are infeasible to be directly implemented on sensors. In this paper, we modify APRIORI to find strong rules from sensor readings in a sensor network and using these rules, autonomously control sensor network operations or supplement sensor operations with a rule knowledge base. For example, triggers activated from the rules could be used to sleep sensors or reduce data transmissions to conserve sensor energy. Our work here includes a detailed implementation of a lightweight rule learning algorithm for a resource-constrainted sensor network, with simulation results for a group node setup running the algorithm.

M3 - Paper

SP - 971

EP - 975

T2 - Proceedings of the 2008 ACM Symposium on Applied Computing

Y2 - 16 March 2008 through 20 March 2008

ER -

ID: 71354