An Energy Efficient Clustering Approach Using Spectral Graph Theory in Wireless Sensor Networks

Thangaramya, K.; Logambigai, R.; SaiRamesh, L.; Kulothungan, K.; Ganapathy, A.

doi:10.1109/icrtccm.2017.41

Cited by 13 publications

(7 citation statements)

References 6 publications

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“…Their experimental results achieved that the better performance than the existing works that are available in this direction. Thangaramya et al (2017) presented a new and energy efficient clustering approach using spectral graph theory in WSNs. They have used a spectral graph theory for making decision over the clustering process in the proposed model.…”

Section: Literature Surveymentioning

confidence: 99%

FEBSRA: Fuzzy Trust Based Energy Aware Balanced Secure Routing Algorithm for Secured Communications in WSNs

Anitha¹,

Bapu²,

Kuppusamy³

et al. 2022

Wireless Pers Commun

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Energy efficiency is playing major role in the design of a sensor network for improving the network lifetime and the trust is also important for providing the security to the data communication process. Delay is also major challenge today due to the enormous volume of network users. For overcoming all these issues, many researchers have been developed energy efficient security mechanisms for fulfilling the requirements. Even though, they are not able to satisfy the current requirements and users in terms of energy consumption, delay and security. For this purpose, this paper propose a new algorithm called Fuzzy Trust Based Energy Aware Balanced Secure Routing Algorithm (FEBSRA) which is able to provide the effective delay constrained secured routing algorithm which uses the fuzzy logic is a form of many-valued logic in which the truth values of variables may be any real number between 0 and 1 both inclusive for making final decision over sensor nodes with the consideration of number of hops between the source and destination nodes, energy level of the nodes and the trust scores. Moreover, a new trust model is also introduced new formulae for calculating the trust scores with the consideration of energy level of the communication delay which is calculated by using number of hops used for the specific communication. The experimental results of the proposed secured routing algorithm demonstrated that the performance in terms of energy consumption, less delay and high throughput with security is better when compared to the existing systems.

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Section: Literature Surveymentioning

confidence: 99%

FEBSRA: Fuzzy Trust Based Energy Aware Balanced Secure Routing Algorithm for Secured Communications in WSNs

Anitha¹,

Bapu²,

Kuppusamy³

et al. 2022

Wireless Pers Commun

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“…In addition, in order to solve the problems brought by dynamic application scenarios, different node capability, and large number of nodes and improve the robustness of networking strategy of WSNs, some research works have been published to adjust the networking topology adaptively. 20 The cluster head is selected by fuzzy logic with constraints on energy and distance. However, due to the computation complexity, it is not feasible for IoT applications with limited nodes' abilities and resources.…”

Section: Related Workmentioning

confidence: 99%

“…DEEC strategy is improved on the basis of LEACH by considering the initial and residual energy of nodes to increase the network lifetime. Due to the broad use of IoT application, other factors have also been considered for networking, such as the number of neighbor nodes, the distance between node and base station, [12][13][14][15][16][17][18][19][20][21] to successfully achieve less energy consumption, longer network lifetime, and balanced load of network.…”

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confidence: 99%

Adaptive multi‐layer clustering strategies based on capacity weight for Internet of Things

Liu

Feng

et al. 2022

Concurrency and Computation

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Summary Due to the requirements brought by diversification of IoT applications, differentiation of nodes' capability, dynamic communication environment and demands, the real‐time information of nodes (actual energy consumption, living nodes' density, pairwise nodes' communication radius) should be considered comprehensively for the clustering strategies of wireless sensor networks to achieve efficient, stable, and flexible performance with limited energy and different quality of service (QoS). This article proposes an improved dynamic multi‐layer clustering strategy for various IoT applications with heterogeneous nodes' energy, unpredictable or fast‐changing distribution of alive nodes, and dynamic scenarios. In addition, an adaptive adjustment strategy based on capability weight for multi‐layer clustering network is proposed to reduce the impact of unreasonable head selection cycle of clustering. By analyzing the node energy, the change of node locations and historical data transmission of cluster head, different capability weights are assigned to each node to adaptively re‐cluster the clusters with heavy load and poor performance, further make the network topology better match current situation and specified QoS requirements. Experimental results have demonstrated that proposed strategy can achieve less energy consumption, longer network lifetime, and better load balancing, especially for the cases with heterogeneous initial energy, nonuniform distribution, and higher density of nodes.

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“…Many LEACH-based algorithms have been proposed to decrease the energy consumption and prolong the network lifetime by selecting the most desirable CHs, such as Advanced LEACH (ALEACH), EE-LEACH, LEACH-N, LEACH-T etc. [8][9][10][11]. However, these algorithms have been proven to be energy efficient; either they do not balance the load among CHs or have high overhead and required computations.…”

Section: Introductionmentioning

confidence: 99%

A new energy aware cluster head selection for LEACH in wireless sensor networks

Pour

Javidan

2021

IET Wireless Sensor Systems

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Internet of Things (IoTs) as a new network pattern for the intelligent world usually uses wireless sensor networks (WSNs) as a perception layer which consisted of numerous number of sensor nodes scattered in the environment to gather intended information. The selected information then is sent to a base station (BS) to be sent to cloud server for further processing. Since the energy of sensor nodes is limited, the most significant challenge in these networks is reducing the energy consumption of the network. It is proved that dividing the network to clusters can significantly reduce the energy consumption. One of the most popular clustering protocols in WSNs is the Low-Energy Adaptive Clustering Hierarchy (LEACH). In this protocol, cluster heads (CHs) are selected randomly which results in poor performance in real scenarios. In this article, a new energy aware CH selection algorithm is proposed which selects CHs based on the residual energy, the position and centrality of nodes. It uses a variable range upon which the centrality and the number of neighbours of each node are calculated. Simulation results show that the proposed algorithm outperforms LEACH, Multi-hope Routing with LEACH (MR-LEACH) and Enhanced Multi-hop LEACH (EM-LEACH) in terms of reducing energy consumption, increasing network lifetime and improving network reliability.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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An Energy Efficient Clustering Approach Using Spectral Graph Theory in Wireless Sensor Networks

Cited by 13 publications

References 6 publications

FEBSRA: Fuzzy Trust Based Energy Aware Balanced Secure Routing Algorithm for Secured Communications in WSNs

FEBSRA: Fuzzy Trust Based Energy Aware Balanced Secure Routing Algorithm for Secured Communications in WSNs

Adaptive multi‐layer clustering strategies based on capacity weight for Internet of Things

A new energy aware cluster head selection for LEACH in wireless sensor networks

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