scispace - formally typeset
Proceedings ArticleDOI

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

O. Younis, +1 more
- Vol. 1, pp 629-640
Reads0
Chats0
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.

read more

Content maybe subject to copyright    Report

Citations
More filters
Journal ArticleDOI

Position-Based Aggregator Node Election in Wireless Sensor Networks

TL;DR: PANEL, a position-based aggregator node election protocol for wireless sensor networks, is introduced and it is shown that, on one hand, PANEL creates more cohesive clusters than HEED, and, on the other hand, that PANEL is more energy efficient thanHEED.
Proceedings ArticleDOI

Grid-based Coordinated Routing in Wireless Sensor Networks

TL;DR: This work explores grid-based coordinated routing in wireless sensor networks and compares the energy available in the network over time for different grid sizes.

The Interplay Between Signal Processing and Networking in Sensor Networks: A Perspective on Large-scale Networks for Military Applications

TL;DR: The paper aims to demonstrate that capturing and exploiting dependencies between signal processing and networking offer design choices resulting in improved network performance.
Journal Article

Efficient and Practical Query Scoping in Sensor Networks

TL;DR: Vonoi scoping is proposed, a distributed algorithm to constrain the dissemination of messages from different sinks that has the property that a query originated by a given sink is forwarded only to the nodes for which that sink is the closest (under the chosen metric).
Proceedings ArticleDOI

Mobile Data Gathering with Space-Division Multiple Access in Wireless Sensor Networks

TL;DR: This paper formalizes the MDG-SDMA problem into an integer program (IP) and proposes three heuristic algorithms that provide practically good solutions to the problem of minimizing the total time of a data gathering tour which consists of two parts: data uploading time and moving time.
References
More filters
Journal ArticleDOI

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.
Related Papers (5)