Reliable routing data aggregation using efficient clustering in WSN

Kamble, Sneha; Dhope, Tanuja Satish

doi:10.1109/icaccct.2016.7831640

Cited by 8 publications

(3 citation statements)

References 8 publications

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“…Here × 𝑙 is the model-𝑙 product and 𝑌 (1) T , 𝑌 (2) T , 𝑌 (3) T , … , 𝑌 (𝑧) T ∈ 𝑅 𝑘×𝑧 which represents the number of CMs connected to each node 𝑣 𝑖 for each vertex. 𝑌 𝑖∈{1,2,...,𝑧} as shown in the next equation, ( 7)…”

Section: Proposed Solutionmentioning

confidence: 99%

“…1, which plays a crucial role in aggregating data and transmitting it to the appropriate base stations located at a reasonable distance. However, when the base station is situated several hops away, the transmission latency and packet loss tend to increase [2]. This underscores the need for effective optimization of the movement of the data-gathering agent, particularly when it needs to traverse multiple hops to reach the base station.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Hypergraph Clustered Gray Relational Analysis HGPSO Algorithm for Data Aggregation in WSN

Pushkin,

Ranvijay

2023

Cybernetics and Information Technologies

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Wireless Sensor Networks (WSN) aggregate data from multiple sensors and transfer it to a central node. Sensor nodes should use as little energy as possible to aggregate data. This work has focused on optimal clustering and cluster head node selection to save energy. HyperGraphs (HGC) and cluster head selection based on distance and energy consumption are unique approaches to spectral clustering. GRA computes a relational matrix to select the cluster head. The network’s Moving Agent (MA) may use Hypergraphed Particle Swarm Optimization (HGPSO) to collect data from cluster heads. Compared to the clustering algorithm without agent movement, the HGC-GRA-HGPSO approach has increased residual energy by 5.59% and packets by 2.44%. It also has improved residual energy by 2.45% compared to Grey Wolf Optimizer-based Clustering (GWO-C).

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Section: Proposed Solutionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Hypergraph Clustered Gray Relational Analysis HGPSO Algorithm for Data Aggregation in WSN

Pushkin,

Ranvijay

2023

Cybernetics and Information Technologies

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“…Cluster heads handle routing, resource scheduling, data aggregation, etc. [11,31] to manage clusters. In such designs, ordinary nodes do nothing other than delivering packets to their designated cluster heads.…”

Section: Introductionmentioning

confidence: 99%

Plane-separated routing in ad-hoc networks

Ergenç

Onur

2022

Wireless Netw

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Control and user (data) plane separation (CUPS) is a concept applied in various networking areas to scale network resources independently, increase the quality of service, and facilitate the autonomy of networks. In this study, we leverage this concept to design a plane-separated routing algorithm, CUPS-based hierarchical routing algorithm (CHRA), as an energy-efficient and low-latency end-to-end communication scheme for clustered ad-hoc networks. In CHRA, while cluster heads constitute the control plane to conduct network discovery and routing, ordinary nodes residing in the user plane forward packets according to the routing decisions taken by the control plane. Exploiting the CUPS, we avoid exhausting cluster heads by offloading packet-forwarding to ordinary nodes and improve the quality of service by utilizing alternative paths other than the backbone of cluster heads. Our simulation results show that CHRA offers a better quality of service in terms of end-to-end latency and data-to-all ratio, and promotes fairness in energy-consumption in both stationary and mobile scenarios.

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