Low energy adaptive clustering hierarchy with deterministic cluster-head selection

Handy, Matthias; Haase, Marc; Timmermann, Dirk

doi:10.1109/mwcn.2002.1045790

Cited by 858 publications

(498 citation statements)

References 9 publications

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“…Low Energy Adaptive Clustering Hierarchy (LEACH), described in [2], is probably one of the more referenced protocols in the sensor networks area. It is a powerful, efficient protocol created to be used in sensor networks with continued data flowing (unstopped sensor activity).…”

Section: Related Workmentioning

confidence: 99%

An Energy-Efficient Ant-Based Routing Algorithm for Wireless Sensor Networks

Camilo

Carreto

Silva

et al. 2006

Ant Colony Optimization and Swarm Intelligence

293

226

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Abstract. Wireless Sensor Networks are characterized by having specific requirements such as limited energy availability, low memory and reduced processing power. On the other hand, these networks have enormous potential applicability, e.g., habitat monitoring, medical care, military surveillance or traffic control. Many protocols have been developed for Wireless Sensor Networks that try to overcome the constraints that characterize this type of networks. Antbased routing protocols can add a significant contribution to assist in the maximisation of the network life-time, but this is only possible by means of an adaptable and balanced algorithm that takes into account the Wireless Sensor Networks main restrictions. This paper presents a new Wireless Sensor Network routing protocol, which is based on the Ant Colony Optimization metaheuristic. The protocol was studied by simulation for several Wireless Sensor Network scenarios and the results clearly show that it minimises communication load and maximises energy savings.

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Section: Related Workmentioning

confidence: 99%

An Energy-Efficient Ant-Based Routing Algorithm for Wireless Sensor Networks

Camilo

Carreto

Silva

et al. 2006

Ant Colony Optimization and Swarm Intelligence

293

226

View full text Add to dashboard Cite

show abstract

“…The Low-Energy Adaptive Clustering Hierarchy (LEACH) algorithm [25] and its related extensions [26][27][28] use probabilistic self-election, where each sensor node has a probability p of becoming a CH in each round. It guarantees that every node becomes a CH only once in 1/p rounds.…”

Section: Related Workmentioning

confidence: 99%

Performance Evaluation of a Topology Control Algorithm for Wireless Sensor Networks

Ababneh

2010

International Journal of Distributed Sensor Networks

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A main design challenge in the area of sensor networks is energy efficiency to prolong the network operable lifetime. Since most of the energy is spent for radio communication, an effective approach for energy conservation is scheduling sleep intervals for extraneous nodes, while the remaining nodes stay active to provide continuous service. Assuming that node position information is unavailable, we present a topology control algorithm, termed OTC, for sensor networks. It uses two-hop neighborhood information to select a subset of nodes to be active among all nodes in the neighborhood. Each node in the network selects its own set of active neighbors from among its one-hop neighbors. This set is determined such that it covers all two-hop neighbors. OTC does not assume the network graph to be a Unit Disk Graph; OTC also works well on general weighted network graphs. OTC is evaluated against two well-known algorithms from the literature, namely, Span and GAF through realistic simulations using TOSSIM. In terms of operational lifetime, load balancing and Spanner property OTC shows promising results. Apart from being symmetric and connected, the resulting graph when employing OTC shows good spanner properties.

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“…EC-MAC's definition could be extended to adhoc networks, where a group of nodes may select some type of coordinator to perform the base station functions, as proposed in [2] and [22]. Furthermore, because the coordinator's role consumes the resources of certain nodes, a group of schemes were proposed in which coordinators are rotated among network nodes [11] [12].…”

Section: Related Workmentioning

confidence: 99%

A unified interference/collision model for optimal MAC transmission power in ad hoc networks

Gobriel

Melhem

Mossé

2006

IJWMC

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Abstract:In this paper we address the issue of controlling transmission power in power-aware adhoc networks. We argue that minimum transmission power is not always optimal. Previous work that minimizes the transmission power does not consider both the energy consumed in collision resolution and the energy disbursed to overcome the interference resulting from neighboring nodes. We investigate the basic transmission power control for the 802.11 MAC protocol, in which the control frames and the data frames can be transmitted at different power levels. A unified collision and interference model of a uniformly distributed network is constructed. Based on this model, the end-to-end network throughput and the total energy consumption of the network are examined for different network parameters. For a net-work with a given node density, our results show the optimal transmission power for control messages and for data messages that will yield maximum throughput and minimum energy consumption per message.

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Low energy adaptive clustering hierarchy with deterministic cluster-head selection

Cited by 858 publications

References 9 publications

An Energy-Efficient Ant-Based Routing Algorithm for Wireless Sensor Networks

An Energy-Efficient Ant-Based Routing Algorithm for Wireless Sensor Networks

Performance Evaluation of a Topology Control Algorithm for Wireless Sensor Networks

A unified interference/collision model for optimal MAC transmission power in ad hoc networks

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