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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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Journal ArticleDOI

Looking Around First: Localized Potential-Based Clustering in Spontaneous Networks

TL;DR: A new budget-based clustering algorithm for self-organizing networks that applies a proportional budget distribution based on the connectivity degree of the nodes, which matches the principle that nodes in real networks are not uniformly distributed.
Journal ArticleDOI

Multi-Agent System for Fault Tolerance in Wireless Sensor Networks

TL;DR: This work proposes a novel multi-agent fault tolerant system for wireless sensor networks that consists of a resource manager, a fault tolerance manager and a load balancing manager, and also proposes fault-tolerant protocols that use multi- agent and mobile agent setups.
Dissertation

Endocrine inspired control of wireless sensor networks : deployment and analysis

Tom Blanchard
TL;DR: This work developed a number of endocrine inspired methods aimed both at improving the power usage of nodes in a wireless sensor network and improving the quality of the data collected, inspired by the human endocrine systems ability to maintain homeostasis, or balance, in a large number of parameters simultaneously.
Journal ArticleDOI

Optimization Methods for Energy Consumption Estimation in Wireless Sensor Networks

TL;DR: In this contribution the stochastic optimization method-genetic algorithm is used to minimize the energy consumption of the wireless sensor nodes depending on the frequency of the transmitted data and the period of the transmission process.
Journal ArticleDOI

Multihop Deterministic Energy Efficient Routing Protocol for Wireless Sensor Networks MDR

TL;DR: A dynamic and multi-hop clustering and routing protocol for thorough behavior analysis is proposed, taking distance and energy into consideration, and this protocol is named as Multi-hop Deterministic energy efficient Routing protocol (MDR).
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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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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