A Novel Clustering Algorithm For Coverage A Large Scale In Wireless Sensor Networks

Jerbi, Wassim; Guermazi, Abderrahmen; Trabelsi, Hafedh

doi:10.5121/ijcsa.2016.6201

Cited by 10 publications

(8 citation statements)

References 32 publications

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“…Their contribution was to elect a cluster head that has sufficient energy for a better now to coordinate with these member nodes and maintain the full coverage for applications which requires of useful data for the entire area to be covered. They proved that the results were better than LEACH protocol when parameters like connectivity rate, energy, scalability, and coverage were taken into account [6].…”

Section: The Salient Features Of the Proposed Methods Arementioning

confidence: 99%

“…The paper is concluded in Section 5 with future directions. Jerbi, W. et al (2016) considered the consequences of isolated nodes that are away from the cluster head (CH) or if CH is not within reach from these nodes. They proposed Orphan Low Energy Adaptive Clustering Hierarchy (O-LEACH), a routing protocol that incorporates the orphan nodes.…”

Section: The Salient Features Of the Proposed Methods Arementioning

confidence: 99%

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ENHANCED CLUSTER HEAD MANAGEMENT IN LARGE SCALE WIRELESS SENSOR NETWORK USING PARTICLE SWARM OPTIMIZATION (PSO) ON THE BASIS OF DISTANCE, DENSITY & ENERGY

Rastogi¹,

Rastogi²,

Darbari³

2019

IJCET

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Wireless Sensor Networks (WSNs) are utilized for a plethora of applications such as weather forecasting, monitoring systems, surveillance, and so on. The critical issues of the WSN are energy constraints, limited memory, and computation time. This spectrum of criticality takes a deep dive with large-scale WSNs. In such scenario, the network lifetime has to be efficiently utilized with the available resources by organizing into clusters. Even though the technique of clustering has proven to be highly effective in minimizing the energy, the tradition cluster based WSNs, the protocol overhead is high for Cluster Heads (CHs) as it receives and aggregates the data from its cluster members. Therefore, efficient management of CH along with routing behavior is vital in prolonging the network lifetime. In this paper, an enhanced CH-Management technique is proposed which efficiently elects its CH using Particle Swarm Optimization (PSO), hereafter referred to as PSO_DDE. The PSO_DDE approach considers various parameters such as within-cluster distance between nodes (intra-cluster distance), neighbor density, and residual energy of nodes for the best candidate selection of CH. Also, the cluster formation is defined by the k-means based on the Euclidian distance. The PSO_DDE approach is integrated with the Dynamic Source Routing (DSR) for efficiently traversing the data packet to the sink node. The performance metrics are compared with the existing approaches using NS-2 simulator, and the proposed approach shows superiority of results.

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Section: The Salient Features Of the Proposed Methods Arementioning

confidence: 99%

Section: The Salient Features Of the Proposed Methods Arementioning

confidence: 99%

ENHANCED CLUSTER HEAD MANAGEMENT IN LARGE SCALE WIRELESS SENSOR NETWORK USING PARTICLE SWARM OPTIMIZATION (PSO) ON THE BASIS OF DISTANCE, DENSITY & ENERGY

Rastogi¹,

Rastogi²,

Darbari³

2019

IJCET

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“…In [39,40], the authors proposed a security mechanism that permits to identify the malicious nodes through a query processing. This technique provides essential security properties such as confidentiality, integrity, freshness, and data authentication [41][42][43][44][45][46][47].…”

Section: Related Workmentioning

confidence: 99%

CoopECC: A Collaborative Cryptographic Mechanism for the Internet of Things

et al. 2021

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The emergence of IoT applications has risen the security issues of the big data sent by the IoT devices. The design of lightweight cryptographic algorithms becomes a necessity. Moreover, elliptic curve cryptography (ECC) is a promising cryptographic technology that has been used in IoT. However, connected objects are resource-constrained devices, with limited computing power and energy power. Driven by these motivations, we propose and develop a secure cryptographic protocol called CoopECC which leverages the organization of IoT nodes into cluster to distribute the load of cluster head (CH) among its cluster members. This technique proves that it optimizes the resource consumption of the IoT nodes including computation and energy consumption. Performance evaluation, done with TOSSIM simulator, shows that the proposed protocol CoopECC outperforms the original ECC algorithm, in terms of computation time, consumed energy, and the network’s lifespan.

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“…Distributed Energy Efficient clustering (DEEC) (2006) [6] was proposed to deal with the challenges of multilevel heterogeneous WSNs. In DEEC algorithm, CHs are selected on the strength of probability equation according to the ratio of remaining energy of each SN and the average energy of the sensor network.…”

Section: Introductionmentioning

confidence: 99%

A Novel Energy Efficient Routing Protocol EACBM for Scalable Wireless Sensor Networks

Toor¹,

Jain²

2018

IJCNIS

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Recent advancements in the field of wireless communication results in the improvement of Wireless Sensor Networks (WSNs) having low powered, low cost and smallest multi-operational sensing units called Sensor Nodes (SNs). The limited battery life of these SNs is the major issue of WSNs. The dissipation of SN energy for transmitting information of one SN to Base Station (BS) is the major cause of depletion of SN energy. Also, SNs energy is in direct relation with battery lifetime of WSNs. Due to which WSN is affected in terms of scalability, a lifetime of network and energy efficiency. Many routing protocols have been proposed to overcome this issue and clustering is the most dominant scheme in which the whole network is divided into small clusters. This clustering scheme is based on the principle of divide and conquers along with data aggregation. In this paper, authors propose a new routing protocol i.e. Energy Aware Cluster Based Multi-hop (EACBM) which uses the principle of clustering and multi-hop communication pattern for transferring information to BS. So that minimum SNs energy is consumed and hence increases the lifetime of WSN. It also uses the concept of subclustering to cover those areas of SNs where CH cannot reach to gather information or which cannot take part in any clustering process due to its far away position. Simulation results show that energy efficiency is greatly optimized by reducing the number of transmission distance between CH and BS via multi-hopping. It also shows how network lifetime, packets transmitted to BS and CH and number of dead SNs is affected by scaling i.e. by different network sizes (100*100m 2 ; 500*500m 2 and 1000*1000m 2) in EACBM by comparing it with SEP, LEACH, CEEC and LEFCA routing protocols.

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A Novel Clustering Algorithm For Coverage A Large Scale In Wireless Sensor Networks

Cited by 10 publications

References 32 publications

ENHANCED CLUSTER HEAD MANAGEMENT IN LARGE SCALE WIRELESS SENSOR NETWORK USING PARTICLE SWARM OPTIMIZATION (PSO) ON THE BASIS OF DISTANCE, DENSITY & ENERGY

ENHANCED CLUSTER HEAD MANAGEMENT IN LARGE SCALE WIRELESS SENSOR NETWORK USING PARTICLE SWARM OPTIMIZATION (PSO) ON THE BASIS OF DISTANCE, DENSITY & ENERGY

CoopECC: A Collaborative Cryptographic Mechanism for the Internet of Things

A Novel Energy Efficient Routing Protocol EACBM for Scalable Wireless Sensor Networks

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