EECED: An Energy Efficient Clustering Algorithm for Event-Driven Wireless Sensor Networks

Buyanjargal, Otgonchimeg; Kwon, Youngmi

doi:10.5772/13722

Cited by 7 publications

(7 citation statements)

References 10 publications

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“…However, the process of selecting CHs without taking into consideration the nodes' locations may have a negative impact on the overall performance [14]. Other research work considered clustering algorithms based on the location information of the sensor nodes as in [14][15][16][17][18]. However, these algorithms improved only the network lifetime and did not consider the sensing coverage.…”

Section: Related Workmentioning

confidence: 99%

Energy-Efficient and Coverage-Aware Clustering in Wireless Sensor Networks

Awad¹,

Taqieddin²,

Seyam³

2012

WET

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Energy efficiency and sensing coverage are essential metrics for enhancing the lifetime and the utilization of wireless sensor networks. Many protocols have been developed to address these issues, among which, clustering is considered a key technique in minimizing the consumed energy. However, few clustering protocols address the sensing coverage metric. This paper proposes a general framework that addresses both metrics for clustering algorithms in wireless sensor networks. The proposed framework is based on applying the principles of Virtual Field Force on each cluster within the network in order to move the sensor nodes towards proper locations that maximize the sensing coverage and minimize the transmitted energy. Two types of virtual forces are used: an attractive force that moves the nodes towards the cluster head in order to reduce the energy used for communication and a repulsive force that moves the overlapping nodes away from each other such that their sensing coverage is maximized. The performance of the proposed mechanism was evaluated by applying it to the well-known LEACH clustering algorithm. The simulation results demonstrate that the proposed mechanism improves the performance of the LEACH protocol considerably in terms of the achieved sensing coverage, and the network lifetime

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Section: Related Workmentioning

confidence: 99%

Energy-Efficient and Coverage-Aware Clustering in Wireless Sensor Networks

Awad¹,

Taqieddin²,

Seyam³

2012

WET

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“…And in each cluster, a cluster-head is selected to report the cluster-decision to the FC according to some rules. In [12], a Low Energy Adaptive Clustering Hierarchy (LEACH) is proposed, in which a pre-elector cluster-head will broadcasts its energy, if there no any other node's energy is bigger than its own energy, then it is the finally selected cluster-head of this cluster. [13] is similar with [12], in which the base station broadcasts all node's energy, and then each node sets a time to start advertising itself to form clusters based on the broadcasting information.…”

Section: A Clustering Schemementioning

confidence: 99%

“…In [12], a Low Energy Adaptive Clustering Hierarchy (LEACH) is proposed, in which a pre-elector cluster-head will broadcasts its energy, if there no any other node's energy is bigger than its own energy, then it is the finally selected cluster-head of this cluster. [13] is similar with [12], in which the base station broadcasts all node's energy, and then each node sets a time to start advertising itself to form clusters based on the broadcasting information. In order to resolve the energy consumption problem associated with the repetitive setup, [14] proposes a Routed-Robin Cluster Header (RRCH) method that fixes the cluster and selects the head in a round-robin method.…”

Section: A Clustering Schemementioning

confidence: 99%

Cooperative Spectrum Sensing and Weighted-Clustering Algorithm for Cognitive Radio Network

Liu

Chen²

2011

IJIEEB

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Abstract-Cognitive radio is a promising technique for efficient utilization of idle authorized spectrum since it is able to sense the spectrum and reuse the frequency when the primary user is absent. In order to overcome the fading, shadowing or hidden terminals in independent detection, cooperative detection is presented. The performance of cooperative sensing is studied in this paper. To enhance the sensing ability, some weighted-cooperative spectrum sensing techniques have been proposed. In this paper, different from the previous studies, we propose a novel weighted-clustering cooperative spectrum sensing algorithm based on distances for cognitive radio network. We firstly classify the secondary users into a few clusters according to several existent methods, and then use cluster-head to collect the observation results come from different secondary users in the same cluster and make a cluster-decision. Considering the different distances between the clusters and the fusion center, different weightings are used to weight the clusterdecisions before combining. The simulation results show that our proposed method improve the probability of detection and reduce the probability of error.

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“…The base station uses balanced clustering technique [7] for distribution of the load of cluster heads, and iterative cluster splitting algorithm to get ideal number of clusters. After that, it makes a multiple CH-to-CH routing paths [8,9]. Finally, it creates schedule for each cluster and broadcasts it to sensor networks.…”

Section: Related Workmentioning

confidence: 99%

Energy Enhanced Base Station Controlled Dynamic Clustering Protocol for Wireless Sensor Networks

Padmanabhan¹,

Kamalakkannan²

2013

JACN

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Abstract-The energy efficiency is the determinant aspect of the wireless sensor network life time. Various routing protocols are used to reduce the energy consumption and to improve the network lifetime. To support high scalability and better data aggregation, sensor nodes are often grouped into disjoint, non overlapping subsets called clusters. Clusters create hierarchical WSNs which incorporate efficient utilization of limited resources of sensor nodes and thus extends network lifetime. This paper discusses an improved clustering protocol to minimize the energy consumption and maximize the network life-time. The simulation results show that the proposed algorithm reduces the overall energy consumption and improves the lifetime over its comparatives.Index Terms-Clustering, EEBDCP, ener gy enhancement, si ireless sensor networks.

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EECED: An Energy Efficient Clustering Algorithm for Event-Driven Wireless Sensor Networks

Cited by 7 publications

References 10 publications

Energy-Efficient and Coverage-Aware Clustering in Wireless Sensor Networks

Energy-Efficient and Coverage-Aware Clustering in Wireless Sensor Networks

Cooperative Spectrum Sensing and Weighted-Clustering Algorithm for Cognitive Radio Network

Energy Enhanced Base Station Controlled Dynamic Clustering Protocol for Wireless Sensor Networks

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