EESCA: Energy efficient structured clustering algorithm for wireless sensor networks

Yuvaraj, P; Narayana, Komanapalli Venkata Lakshmi

doi:10.1109/cast.2016.7915024

Cited by 17 publications

(7 citation statements)

References 10 publications

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“…When first node dies, the residual energy of all nodes will be exhausted in hundreds of rounds. Table 9 and Figure 8 show a network lifetime comparison of the proposed CFSFDP-E, KM-LEACH [ 3 ], DBCH [ 20 ] and EESCA [ 21 ].…”

Section: Experimental Results and Analysismentioning

confidence: 99%

“…The Energy Efficient Structured Clustering Algorithm (EESCA) is a hybrid cluster head selection method with parameter location centrality and nodes’ residual energy on the fixed clusters [ 21 ]. The area of deployment is exactly divided into four regions based on coordinates.…”

Section: Experimental Results and Analysismentioning

confidence: 99%

“… Since the clustering process needs to be repeated in every round, we set a dynamic threshold for cluster head selection and it can determine an appropriate number of CHs and make every CM be clustered reasonably. With the same simulation environment and parameters, it is proved that our proposed CFSFDP-E algorithm in WSN outperforms the classical protocols (LEACH [ 13 ], LEACH-C [ 14 ], PEGASIS [ 15 ] and SEP [ 16 ]), some improved protocols based on LEACH (ALEACH [ 17 ], C-LEACH [ 18 ] and K-LEACH [ 19 ]) and some new protocols which were proposed in the last three years (KM-LEACH [ 3 ], DBCH [ 20 ] and EESCA [ 21 ]). …”

Section: Introductionmentioning

confidence: 99%

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An Energy-Balanced Clustering Protocol Based on an Improved CFSFDP Algorithm for Wireless Sensor Networks

Zhang

Liu

2018

Sensors

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Clustering, as an essential part in an hierarchy protocol that can prolong the network lifetime, is influenced by the cluster head selection and clustering scheme. A new clustering algorithm called clustering by fast search and finding of density peaks (CFSFDP) based on local density and distance is implementable and efficient. In this paper, we combine this clustering algorithm with a hierarchy protocol in wireless sensor networks (WSNs). However, energy consumption in each round is unbalanced only considering these two variables during the clustering phase, which leads to the early death of the first node. In order to solve this problem, we take residual energy into consideration in our improved CFSFDP-E (energy) algorithm so as to ultimately balance the energy consumption of the network. We analyze different forms of energy and choose a dynamic threshold for each round in the CFSFDP-E algorithm. Simulation results demonstrate that the proposed approach can not only postpone the death of the first node by almost 50% compared to LEACH, but that it also outperforms several related protocols with respect to energy efficiency.

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Section: Experimental Results and Analysismentioning

confidence: 99%

Section: Experimental Results and Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An Energy-Balanced Clustering Protocol Based on an Improved CFSFDP Algorithm for Wireless Sensor Networks

Zhang

Liu

2018

Sensors

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“…The use of k-means and FCM in explorative way is shown in [10−13]. In 2016, Yuvaraj and Narayana [14] suggested a hybrid cluster head selection method with the parameters Location centrality and Nodes' lingering energy on the fixed clusters. The recreation result represents that the proposed calculation is great at burden offsetting with low control overhead and stretching out system lifetime contrasted with regular steering calculation drain.…”

Section: Introductionmentioning

confidence: 99%

Cluster Head Selection and Packet Delivery Estimation Based on K-Means and FCM

Khandelwal*,

Jain

2019

IJRTE

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In this paper comparative study have been presented for the efficient cluster head selection based on k-means and fuzzy c-means (FCM) clustering algorithms. It is observed that the nodes assignment after the clustering is different through k-means and FCM. It is because of the variant initialization mechanism of the k-means and FCM. But the assignment of cluster does not affect the results. It is clearly depicted from the packet delivery time results by our approach. It shows that the k-means and FCM have the capability of CHs selection in the required time frame and it shows the effectiveness in different iterations also. When aggregate packet delivery has been considered the same situation has been observed which depicts the capability of our approach. K-means found to be faster in comparison to FCM.

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“…In direct communication protocol, sensor nodes, which are far from the BS, dissipate faster than others do because they send their data to the BS directly. The second category involve Minimum Transmission Energy (MTE) protocols [4], where nodes route data to the BS through intermediate nodes, each node acting as a router for the other nodes [5].…”

Section: Introductionmentioning

confidence: 99%

Untitled

2018

IJASSN

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Wireless Sensor Networks (WSN) is widely deployed in different fields of applications of smart grid to provide reliable monitoring and controlling of the electric power grid. The objective of this paper is simulate and analyze impact of various smart grid environments on performance of four different WSN routing protocols namely the Low Energy Adaptive Clustering Hierarchy (LEACH) and Centralized LEACH (LEACT-C) as well as other two conventional protocols namely Minimum Transmission Energy (MTE) and Static Clustering. This analysis would be beneficial in making the correct choice of WSN routing protocols for various smart grid applications. The performance of the four protocols is simulated using NS-2 network simulation on Ubuntu. The results are analyzed and compared using number of data signals received at base station, energy consumption, and network lifetime as performance metrics. The results show that the performance of various protocols in the smart grid environments have deteriorated due log normal channel characteristics and consequently network lifetime have decreased significantly. The results also indicate that clustering based routing protocols have more advantageous over conventional protocols; MTE and static clustering. Also, centralized clustering approach is more effective as it distributes energy dissipation evenly throughout the sensor nodes which reduce energy consumption and prolong the networks' lifetime. This approach is more effective in delivering data to base station because it has global knowledge of the location and energy of all the nodes in the network.

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EESCA: Energy efficient structured clustering algorithm for wireless sensor networks

Cited by 17 publications

References 10 publications

An Energy-Balanced Clustering Protocol Based on an Improved CFSFDP Algorithm for Wireless Sensor Networks

An Energy-Balanced Clustering Protocol Based on an Improved CFSFDP Algorithm for Wireless Sensor Networks

Cluster Head Selection and Packet Delivery Estimation Based on K-Means and FCM

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