Energy-Balanced and Distributed Clustering Protocol for IoT Wireless Sensors

Hassan, Mohammed Falih; Pokhrel, Shiva Raj; Al-Musawi, Bahaa

doi:10.1109/wcncw48565.2020.9124835

Cited by 5 publications

(3 citation statements)

References 12 publications

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“…Finally, [36] has summarized three network parameters that affect energy consummation in WSNs. First, the optimal number of cluster heads for a given network setup.…”

Section: Related Workmentioning

confidence: 99%

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Innovative Fitness Functions for Robust Energy Management in WSNs

Hassan

Al-Musawi

Al-Janabi

2023

Preprint

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Wireless Sensor Networks (WSNs) are widely recognized as a crucial enabling technology for Internet of Things (IoT) applications. One of the primary challenges in designing WSNs is to ensure efficient energy management, which involves minimizing and uniformly distributing energy consumption among the wireless sensors to extend network lifetime. In this paper, we propose a set of mathematical tools in the form of fitness functions that can be used to measure, compare, and control the way in which the network manages energy consumption among the wireless sensors. Furthermore, we present an Optimized Energy Balanced and Distributed Clustering (OEBDC) protocol for WSNs, which utilizes these fitness functions to manage energy resources more efficiently by promoting uniform energy consumption, minimizing communication overhead, and extending network lifetime. The proposed tools can be integrated with other WSN protocols to manage energy resources according to specific requirements that suited different applications. We have evaluated the performance of the proposed protocol against well-established routing protocols for WSNs and found that OEBDC achieves a notable advantage in extending network lifetime compared to other protocols, while also demonstrating robust control in managing energy resources.

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“…Finally, [36] has summarized three network parameters that affect energy consummation in WSNs. First, the optimal number of cluster heads for a given network setup.…”

Section: Related Workmentioning

confidence: 99%

“…Overhead communications are necessary for organizing sensor nodes' communications; however, they consume energy as well. In [36], we proposed this metric for measuring the amount of energy usage in data communication compared to communication overhead. Let the normalized energy ( no E ) dissipated in overheads transmission be:…”

Section: Evaluation Metricsmentioning

confidence: 99%

Innovative Fitness Functions for Robust Energy Management in WSNs

Hassan

Al-Musawi

Al-Janabi

2023

Preprint

Self Cite

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“…A major criterion in WSN is bandwidth utilization along with energy-saving. Thus, developing the nodes in energy along with a bandwidth-aware manner is important [12]. A utmost energy-efficient architecture is the clustered network, particularly where SN leave in hundreds and thousands of numbers [13].…”

Section: Introductionmentioning

confidence: 99%

An Energy Efficient and Bandwidth Aware Optimal Routing for IoT in Agriculture

Jain

Chauhan

Jain

2021

Preprint

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The agriculture that is enabled with the Internet of Things (IoT) in addition to Wireless Sensors Networks (WSN) can aid the farmers in monitoring their product along with conditions in real-time. The indispensable issues that one has to confront with WSN are Energy-saving along with effective bandwidth usage. Lately, for the amelioration of network stability together with lifetime, disparate cluster-centered solutions are modeled. Nevertheless, most techniques are merely modeled in an energy-aware manner and utilize merely a distance parameter aimed at the data communication. It is imperative for satisfying the bandwidth use of IoT. Here, a cluster-centered energy as well as bandwidth aware routing model is proposed for agriculture data on IoT-centered WSN. Optimal Clusters Head (CH) selection as well as clustering is performed on the WSN for carrying out cluster-centered Data Aggregation (DA). The novel chaos mapping and Opposition centered Learning Grasshopper Optimization Algorithm (CO2GA) chooses the collection of CH as of agricultural Sensor Nodes (SN). Next, centered upon the distance betwixt the chosen CH and SN, the clusters are generated. The clusters share the data to their CH, and the Chaos key generated Advanced Encryption Standard with Rivest–Shamir–Adleman (CKAES-RSA) algorithm encrypt the aggregated data of CH. Lastly, the encrypted data of IoT data are shared with the Base Stations (BS) or Sink Node (Sn) by means of the optimal routing. Aimed at Optimal Route Selection (ORS), the paper utilizes a Deep Learning (DL) approach, explicitly crossover and mutation-based optimal Multi-Layer Perceptrons (CM-OMLP), which computes the fitness of hidden layer by regarding energy, bandwidth, trust, delay, along with congestion level. The proposed encryption and routing mechanism’s results are weighted against the first-rate techniques. The proposed work achieves the highest level of security aimed at the IoT data and fulfills the QoS requirements regarding packet delivery, throughput, delay, along with Network LifeTimes (NLT).

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