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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
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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Throughput analysis of energy aware routing protoco l for real-time load distribution in wireless sensor network (wsn)

TL;DR: Making use of the cross-layer interactions between the physical layer and the network layer thus leads to an improvement in energy efficiency of the entire network when compared with other protocols and it also improves the response time in case of network change.
Journal ArticleDOI

On the throughput performance of cluster-based cognitive radio networks

TL;DR: Results show cluster based cooperative sensing throughput outperforms conventional cooperative sensing especially when the reporting channel has high probability of error.
Journal ArticleDOI

Ensuring Higher Security for Gathering and Economically Distributing the Data in Social Wireless Sensor Networks

TL;DR: Electronic object caching in such SWSNETs are shown to be able to reduce the Data provisioning cost which depends heavily on the service and pricing dependences among various stakeholders including Data providers, network service providers, and End Customers.
Book ChapterDOI

Target Detection, Localization, and Tracking in Wireless Sensor Networks

TL;DR: This chapter will investigate target detection approaches, sensor node localization algorithms, and target tracking schemes in wireless sensor network (WSN), a self-organized distributed network composed of a large quantity of small, inexpensive sensor nodes.
Journal ArticleDOI

Improving the Network Life Time of Wireless Sensor Network using EEEMR Protocol with Clustering Algorithm

TL;DR: The proposed Clustering algorithm in EEEMR Protocol is implemented and the proposed system energy consumption is decreased by 13% compared to the existing system.
References
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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.
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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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