Hybrid-learning based data gathering in wireless sensor networks

Mohammad Abdur Razzaque; Ismail Fauzi; Akhtaruzzaman Adnan

doi:10.1007/978-3-642-36543-0_10

Hybrid-learning based data gathering in wireless sensor networks

Mohammad Abdur Razzaque, Ismail Fauzi, Akhtaruzzaman Adnan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Prediction based data gathering or estimation is a very frequent phenomenon in wireless sensor networks (WSNs). Learning and model update is in the heart of prediction based data gathering. A majority of the existing prediction based data gathering approaches consider centralized and some others use localized and distributed learning and model updates. Our conjecture in this work is that no single learning approach may not be optimal for all the sensors within a WSN, especially in large scale WSNs. For, example for source nodes, which are very close to sink, centralized learning could be better compared to distributed one and vice versa for the further nodes. In this work, we explore the scope of possible hybrid (centralized and distributed) learning scheme for prediction based data gathering in WSNs. Numerical experimentations with two sensor datasets and their results of the proposed scheme, show the potential of hybrid approach.

Original language	English
Title of host publication	Intelligent Information and Database Systems - 5th Asian Conference, ACIIDS 2013, Proceedings
Pages	90-99
Number of pages	10
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-36543-0_10
Publication status	Published - 11 Mar 2013
Event	5th Asian Conference on Intelligent Information and Database Systems - Kuala Lumpur, Malaysia Duration: 18 Mar 2013 → 20 Mar 2013 Conference number: 5

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	7803 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	5th Asian Conference on Intelligent Information and Database Systems
Abbreviated title	ACIIDS 2013
Country/Territory	Malaysia
City	Kuala Lumpur
Period	18/03/13 → 20/03/13

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10.1007/978-3-642-36543-0_10

Cite this

Razzaque, M. A., Fauzi, I., & Adnan, A. (2013). Hybrid-learning based data gathering in wireless sensor networks. In Intelligent Information and Database Systems - 5th Asian Conference, ACIIDS 2013, Proceedings (PART 2 ed., pp. 90-99). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7803 LNAI, No. PART 2). https://doi.org/10.1007/978-3-642-36543-0_10

Razzaque, Mohammad Abdur ; Fauzi, Ismail ; Adnan, Akhtaruzzaman. / Hybrid-learning based data gathering in wireless sensor networks. Intelligent Information and Database Systems - 5th Asian Conference, ACIIDS 2013, Proceedings. PART 2. ed. 2013. pp. 90-99 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

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abstract = "Prediction based data gathering or estimation is a very frequent phenomenon in wireless sensor networks (WSNs). Learning and model update is in the heart of prediction based data gathering. A majority of the existing prediction based data gathering approaches consider centralized and some others use localized and distributed learning and model updates. Our conjecture in this work is that no single learning approach may not be optimal for all the sensors within a WSN, especially in large scale WSNs. For, example for source nodes, which are very close to sink, centralized learning could be better compared to distributed one and vice versa for the further nodes. In this work, we explore the scope of possible hybrid (centralized and distributed) learning scheme for prediction based data gathering in WSNs. Numerical experimentations with two sensor datasets and their results of the proposed scheme, show the potential of hybrid approach.",

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Razzaque, MA, Fauzi, I & Adnan, A 2013, Hybrid-learning based data gathering in wireless sensor networks. in Intelligent Information and Database Systems - 5th Asian Conference, ACIIDS 2013, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 7803 LNAI, pp. 90-99, 5th Asian Conference on Intelligent Information and Database Systems, Kuala Lumpur, Malaysia, 18/03/13. https://doi.org/10.1007/978-3-642-36543-0_10

Hybrid-learning based data gathering in wireless sensor networks. / Razzaque, Mohammad Abdur; Fauzi, Ismail; Adnan, Akhtaruzzaman.
Intelligent Information and Database Systems - 5th Asian Conference, ACIIDS 2013, Proceedings. PART 2. ed. 2013. p. 90-99 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7803 LNAI, No. PART 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - Prediction based data gathering or estimation is a very frequent phenomenon in wireless sensor networks (WSNs). Learning and model update is in the heart of prediction based data gathering. A majority of the existing prediction based data gathering approaches consider centralized and some others use localized and distributed learning and model updates. Our conjecture in this work is that no single learning approach may not be optimal for all the sensors within a WSN, especially in large scale WSNs. For, example for source nodes, which are very close to sink, centralized learning could be better compared to distributed one and vice versa for the further nodes. In this work, we explore the scope of possible hybrid (centralized and distributed) learning scheme for prediction based data gathering in WSNs. Numerical experimentations with two sensor datasets and their results of the proposed scheme, show the potential of hybrid approach.

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Razzaque MA, Fauzi I, Adnan A. Hybrid-learning based data gathering in wireless sensor networks. In Intelligent Information and Database Systems - 5th Asian Conference, ACIIDS 2013, Proceedings. PART 2 ed. 2013. p. 90-99. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-36543-0_10

Hybrid-learning based data gathering in wireless sensor networks

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