Node density based clustering to maximize the network lifetime of WSN using multiple mobile elements

Usha, M.; Sreenithi, S.; Sujitha, M.; Swarnalatha, S.

doi:10.1109/iceca.2017.8212783

Cited by 8 publications

(3 citation statements)

References 9 publications

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“…WSN energy-saving routing algorithms are required to perform a given task while maintaining a long network life cycle [14]. [19] is likely to be the cluster head.…”

Section: Related Workmentioning

confidence: 99%

Effective Aggregate Data Collection and Enhanced Network Lifetime Using Energy Efficient Aggregation Data Convening Routing in Wireless Sensor Network

D¹,

Saravanasundaram²,

Prakash³

et al. 2021

Preprint

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A wireless sensor network is a network system that uses wireless sensor nodes to monitor physical or environmental conditions as voice, temperature, and spatial dispersive movements. Each node can locally sense its environment, process information and data and send the data to one or more collection points within the WSN. In the existing solution categorized into member nodes and group/cluster heads(CH). The CH election process increases the overhead of the network and reduce the network lifetime. The processing and energy limitations of the nodes are considered for the CH election process. In this cluster formation methods aiming at Cluster head selection process and providing trust in hierarchical WSN are proposed. In this Energy Efficient Aggregation Data Convening Routing (E2ADCR) to estimate the routing path, and aggregate data collection to improve the network lifetime. The major advantage of this technique is to avoid the malicious or selfish node from becoming a dominant cluster in a group of clusters. Initially sink node selection is forward the Configuration Message (CM) to every node on network to construct the performing node. In this, cluster selection based on connection density, degree of the node angle, and residual energy (Quality Factor) that is evaluated from the link robustness, energy and degree of the node. Multi hop link transmission support path optimization technique is estimated in the path when the obstacle is present in the WSN. To introduce an Aggregated Support based Data Collection for evaluate each packet flow monitor on the network if any unrelated packet that will eliminate to forward to sink node. The new routing protocols, which were developed during this research, have better energy efficiency. The proposed routing path of the computational simplicity is achieved by a simple method.

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“…WSN energy-saving routing algorithms are required to perform a given task while maintaining a long network life cycle [14]. [19] is likely to be the cluster head.…”

Section: Related Workmentioning

confidence: 99%

Effective Aggregate Data Collection and Enhanced Network Lifetime Using Energy Efficient Aggregation Data Convening Routing in Wireless Sensor Network

D¹,

Saravanasundaram²,

Prakash³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Density-based cluster formation methods assume that nodes in each group are extracted from a probability distribution in relation to the total number of nodes in the network. Some works in this area are: to maximize the network lifetime [ 14 , 15 ], adaptive clustering [ 16 ], and density-based fuzzy imperialist competitive clustering algorithm [ 17 ]. The approaches of cluster formation based on cooperation have provided solutions to the problem of energy management using the information of the energy spectrum detected [ 18 ].…”

Section: Related Workmentioning

confidence: 99%

A Clustering WSN Routing Protocol Based on k-d Tree Algorithm

Anzola

Pascual

Bermúdez

et al. 2018

Sensors

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Clustering in wireless sensor networks has been widely discussed in the literature as a strategy to reduce power consumption. However, aspects such as cluster formation and cluster head (CH) node assignment strategies have a significant impact on quality of service, as energy savings imply restrictions in application usage and data traffic within the network. Regarding the first aspect, this article proposes a hierarchical routing protocol based on the k-d tree algorithm, taking a partition data structure of the space to organize nodes into clusters. For the second aspect, we propose a reactive mechanism for the formation of CH nodes, with the purpose of improving delay, jitter, and throughput, in contrast with the low-energy adaptive clustering hierarchy/hierarchy-centralized protocol and validating the results through simulation.

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“…In this article, a hybrid strategy known as node density based on clustering and multiple mobile collections (ND-CMMC) is presented. Taking into account a number of sensing area has distributed deployments of sensors, Initially, we suggest a new cluster head selection technique based on Regarding the node density, A node's density property is the quantity of its auxiliary nodes inside a specific range [1]. This translates to the areas where nodes are more thickly deployed tend to form clusters, and there are more nodes at the regions' centres most likely to be elected as CHs.…”

Section: Introductionmentioning

confidence: 99%

A Brief Survey on Cluster based Energy Efficient Routing Protocols in IoT based Wireless Sensor Networks

Priyadarsini

Saranya

Karthik

2022

IJRITCC

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The wireless sensor network (WSN) consists of a large number of randomly distributed nodes capable of detecting environmental data, converting it into a suitable format, and transmitting it to the base station. The most essential issue in WSNs is energy consumption, which is mostly dependent on the energy-efficient clustering and data transfer phases. We compared a variety of algorithms for clustering that balance the number of clusters. The cluster head selection protocol is arbitrary and incorporates energy-conscious considerations. In this survey, we compared different types of energy-efficient clustering-based protocols to determine which one is effective for lowering energy consumption, latency and extending the lifetime of wireless sensor networks (WSN) under various scenarios.

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Node density based clustering to maximize the network lifetime of WSN using multiple mobile elements

Cited by 8 publications

References 9 publications

Effective Aggregate Data Collection and Enhanced Network Lifetime Using Energy Efficient Aggregation Data Convening Routing in Wireless Sensor Network

Effective Aggregate Data Collection and Enhanced Network Lifetime Using Energy Efficient Aggregation Data Convening Routing in Wireless Sensor Network

A Clustering WSN Routing Protocol Based on k-d Tree Algorithm

A Brief Survey on Cluster based Energy Efficient Routing Protocols in IoT based Wireless Sensor Networks

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