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Proceedings ArticleDOI

Distributed clustering in ad-hoc sensor networks: a hybrid, energy-efficient approach

O. Younis, +1 more
- Vol. 1, pp 629-640
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TLDR
A protocol is presented, HEED (hybrid energy-efficient distributed clustering), that periodically selects cluster heads according to a hybrid of their residual energy and a secondary parameter, such as node proximity to its neighbors or node degree, which outperforms weight-based clustering protocols in terms of several cluster characteristics.
Abstract
Prolonged network lifetime, scalability, and load balancing are important requirements for many ad-hoc sensor network applications. Clustering sensor nodes is an effective technique for achieving these goals. In this work, we propose a new energy-efficient approach for clustering nodes in ad-hoc sensor networks. Based on this approach, we present a protocol, HEED (hybrid energy-efficient distributed clustering), that periodically selects cluster heads according to a hybrid of their residual energy and a secondary parameter, such as node proximity to its neighbors or node degree. HEED does not make any assumptions about the distribution or density of nodes, or about node capabilities, e.g., location-awareness. The clustering process terminates in O(1) iterations, and does not depend on the network topology or size. The protocol incurs low overhead in terms of processing cycles and messages exchanged. It also achieves fairly uniform cluster head distribution across the network. A careful selection of the secondary clustering parameter can balance load among cluster heads. Our simulation results demonstrate that HEED outperforms weight-based clustering protocols in terms of several cluster characteristics. We also apply our approach to a simple application to demonstrate its effectiveness in prolonging the network lifetime and supporting data aggregation.

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Citations
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An Efficient Energy Usage of Wireless Sensor Network

TL;DR: A variant of LEACH protocol is introduced which considers the distance between base station and sensors in the way that if a node is far from the base station then the probability that this node becomes a cluster header is low.

Distributed Fault Detection Method and Diagnosis of Fault Type in Clustered Wireless Sensor Networks

TL;DR: The results of simulations show that the detection accuracy and false alarm rate in the proposed method even when the probability of faulty nodes is high, is acceptable in comparison with existing algorithms.

Efficient Clustering Protocol Based on Stochastic Matrix & MCL and Data Routing for Mobile Wireless Sensors Network

TL;DR: This paper presents a new approach for data routing dedicated to mobile Wireless Sensors Network (WSN) based on clustering based on stochastic matrix and on the Markov Chain Cluster algorithm to organize a large number of mobile sensors into clusters without defining the required clusters number in advance.
Proceedings ArticleDOI

Dynamic water gate assignment scheme for data aggregation in long-thin sensor networks

TL;DR: This paper develops a dynamic water gate assignment scheme that reduces the response time while avoids network congestion for data collection in LT WSNs, which can accommodate the time-varying sensing data generating rates of sensors.

A Distributed and Energy-efficient Clustering Method for Hierarchical Wireless Sensor Networks

TL;DR: This work proposes a distributed, energy-efficient and flexible clustering approach based on the hierarchical agglomerative clustering (HAC) method, which can enhance network self-control capability and resource efficiency, and prolong the whole network lifetime.
References
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Estimating the Dimension of a Model

TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.

Estimating the dimension of a model

TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.
Book

Data Mining: Concepts and Techniques

TL;DR: This book presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects, and provides a comprehensive, practical look at the concepts and techniques you need to get the most out of real business data.
Journal ArticleDOI

An application-specific protocol architecture for wireless microsensor networks

TL;DR: This work develops and analyzes low-energy adaptive clustering hierarchy (LEACH), a protocol architecture for microsensor networks that combines the ideas of energy-efficient cluster-based routing and media access together with application-specific data aggregation to achieve good performance in terms of system lifetime, latency, and application-perceived quality.
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