Optimization Framework for Distributed Clustering Scheme in Wireless Sensor Networks

Yang, Dong; Shufen, Xiao

doi:10.1109/snpd.2007.300

Cited by 1 publication

(3 citation statements)

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“…where, ECH is energy that cluster heads consumes, Enon-CH is energy that sensor nodes consume, l is the bit length of data, EDA is energy necessary to receiving one bit of data, Eelec is energy necessary to starting up to transmit one bit of data, Ecal is energy necessary to calculate one bit of data, 1 and 2 energy necessary to propagating one bit respectively, dCH-CH is the communication distance between clusters, dnode-CH is the communication distance between sensor nodes and cluster heads. Above equations are the results using CCM (Cluster Consumption Model) in [20] and is based on assuming that the number of data bits transmitted by cluster heads is same as the number of data bits from sensor nodes by taking into account data gathering, that is, the ratio of data gathering is (n-1) -1 . Because we can consider that cluster heads transmit l bits of data by data gathering, if sensor nodes in every cluster gather l bits of data, respectively.…”

Section: Cluster Setup Stagementioning

confidence: 99%

“…CNS is a concept that the target or the source to sense is on the centre of the cluster and it was implemented by CBERRP (Clustering-Based Expanding-Ring Routing Protocol) in [30].…”

Section: Introductionmentioning

confidence: 99%

“…Besides, several clustering protocols such as distributed clustering algorithm, BSCA (BS Clustering Algorithm) [14]that elects randomly cluster heads similarly in LEACH-C, CBERRP(Clustering-Based Expanding-Ring Routing Protocol) [15], FLOG, MOCA (Multi-hop Overlapping Clusters Algorithm) [17], LENO (Least Rotation Near-Optimal) [18], WCA (Weighted Clustering Algorithm), DAC (Distributed Asynchronization Clustering) [19], MICA (MICa Adjustments) [20], EESH (Energy Efficient Strong Head clustering algorithm) [20] have been presented.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Energy Balanced and Efficient Clustering Method for Wireless Sensor Networks

Lee

Sin

Jang

et al. 2017

IJCT

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In this paper the energy balanced and efficient clustering method based on balance of energy consumption of nodes in WSN is proposed, which may be applied to any WSN. The almost static centralized protocol that differs from previous methods is proposed, the main feature of which is that the sinks transmit most of control message and process most of data. First, EBEC method is proposed, which optimizes by considering energy consumption on transmitting and receiving data, energy consumption on the reclustering and hot-spot problem that be optimized individually in previous works. In order to implement this method, VW BAK-C algorithm is used by introducing the concept of variable weighted Euclid distance to k-clustering algorithm. Second, the previous clustering methods are classified into random method and the method based on QoS according to the characteristic of cluster head rotation, and average of total energy consumption of nodes is analyzed mathematically. The proposed method is compared and analyzed. Third, the performance of the proposed method is evaluated by comparing with other clustering methods through simulation.

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Section: Cluster Setup Stagementioning

confidence: 99%

“…CNS is a concept that the target or the source to sense is on the centre of the cluster and it was implemented by CBERRP (Clustering-Based Expanding-Ring Routing Protocol) in [30].…”

Section: Introductionmentioning

confidence: 99%