Secure and Efficient Data Transmission for Wireless Sensor Networks by using Optimized Leach Protocol

Kumar, M. Jogendra; Kumar, Gourav; Krishna, Pravin; Sai, N. Raghavendra

doi:10.1109/icict50816.2021.9358729

Cited by 17 publications

(4 citation statements)

References 11 publications

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“…Therefore, the node that acted as cluster head seems to be less dead. If the cluster head is not exhausted, the data collected from other nodes from the cluster are safely transmitted to the sink node [ 26 ]. Therefore, the energy weightage proposed helps the cluster save its energy for future use and prolong its lifetime in the network.…”

Section: Resultsmentioning

confidence: 99%

Optimization of Leach Protocol in Wireless Sensor Network Using Machine Learning

Ramesh

Rajasekaran

Dwivedi

et al. 2022

Computational Intelligence and Neuroscience

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The Wireless Sensor Network is a network formed in areas human beings cannot access. The data need to be sensed by the sensor and transferred to the sink node. Many routing protocols are designed to route data from a single node to the sink node. One of the routing protocols is the hierarchical routing protocol, which passes on the sensed data hierarchically. The Low Energy Adaptive Clustering Hierarchy (LEACH) is one of the hierarchical methods in which communication happens in two steps: the setup phase and the steady-state phase. The efficiency of the LEACH has to be optimized to improve the network lifetime. Therefore, the k-means clustering algorithm, which comes under the unsupervised machine learning method, is incorporated with the LEACH algorithm and has shown better results. But the selection of cluster head needs to improvise because it will transfer the summed-up data to the sink node, so it is to be efficient enough. So, this paper proposes the modified k-means algorithm with LEACH protocol for optimizing the Wireless Sensor Network. In the modified k-means algorithm, the weight of the cluster head is tested and elected, and the clusters are formed using the Euclidean distance formula. The proposed work yields 48.85% efficiency compared to the existing protocol. It is also proven that the proposed work showed more successful data transfer to the sink node. The cluster head selection process elects the more efficient node as the head with less failure rate. The proposed work optimistically balanced the whole network in terms of energy and successful data transfer.

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Section: Resultsmentioning

confidence: 99%

Optimization of Leach Protocol in Wireless Sensor Network Using Machine Learning

Ramesh

Rajasekaran

Dwivedi

et al. 2022

Computational Intelligence and Neuroscience

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“…Elshrkawey et al [ 30 ] and Kumar et al [ 31 ] mentioned secure data aggregation and secure data communication practices for protecting wireless MAC layers in WSNs. Here, the first article produced individual message authentication codes for each data aggregation channel of WSNs.…”

Section: Methodsmentioning

confidence: 99%

Interleaved Honeypot-Framing Model with Secure MAC Policies for Wireless Sensor Networks

Rajasoundaran

Maheswar

Muthuramalingam

et al. 2022

Sensors

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The Wireless Medium Access Control (WMAC) protocol functions by handling various data frames in order to forward them to neighbor sensor nodes. Under this circumstance, WMAC policies need secure data communication rules and intrusion detection procedures to safeguard the data from attackers. The existing secure Medium Access Control (MAC) policies provide expected and predictable practices against channel attackers. These security policies can be easily breached by any intelligent attacks or malicious actions. The proposed Wireless Interleaved Honeypot-Framing Model (WIHFM) newly implements distributed honeypot-based security mechanisms in each sensor node to act reactively against various attackers. The proposed WIHFM creates an optimal Wireless Sensor Network (WSN) channel model, Wireless Interleaved Honeypot Frames (WIHFs), secure hash-based random frame-interleaving principles, node-centric honeypot engines, and channel-covering techniques. Compared to various existing MAC security policies, the proposed model transforms unpredictable IHFs into legitimate frame sequences against channel attackers. Additionally, introducing WIHFs is a new-fangled approach for distributed WSNs. The successful development of the proposed WIHFM ensures resilient security standards and neighbor-based intrusion alert procedures for protecting MAC frames. Particularly, the proposed wireless honeypot methodology creates a novel idea of using honeypot frame traps against open wireless channel attacks. The development of a novel wireless honeypot traps deals with various challenges such as distributed honeypot management principles (node-centric honeypot, secretly interleaved-framing principles, and interleaving/de-interleaving procedures), dynamic network backbone management principles (On Demand Acyclic Connectivity model), and distributed attack isolation policies. This effort provides an effective wireless attack-trapping solution in dynamic WSNs. The simulation results show the advantage of the proposed WIHFM over the existing techniques such as Secure Zebra MAC (SZ-MAC), Blockchain-Assisted Secure-Routing Mechanism (BASR), and the Trust-Based Node Evaluation (TBNE) procedure. The experimental section confirms the proposed model attains a 10% to 14% superior performance compared to the existing techniques.

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“…Three different estimators choose bundle headers identically based on GWO and IPv6. In terms of throughput, dead and active fungus, and performance limits, the suggested approach is then contrasted with its current LEACH strategy [23].…”

Section: Related Workmentioning

confidence: 99%

Design and performance assessment of improved evolutionary computing based LEACH protocol for energy efficient and lifetime extension of wireless sensor network

Jain,

Mathur

2024

Eng. Res. Express

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The strengths of a Memetic Algorithm and an enhanced Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol are combined in this research study to propose a revolutionary method for improving the energy efficiency and longevity of Wireless Sensor Networks (WSNs). WSNs are widely used for a variety of applications, including industrial automation, healthcare, and environmental monitoring, where extending network lifetime and energy conservation are crucial. Although successful, conventional clustering algorithms like LEACH feature subpar cluster formation and premature cluster head failures. To get over these restrictions, a memetic algorithm is used to maximize cluster formation and reduce energy usage. This algorithm was influenced by natural evolution and cultural learning processes. The Memetic Algorithm iteratively improves the LEACH protocol in the proposed technique by enhancing dynamic clustering, energy-aware routing, and cluster head selection. These methods work together to increase energy efficiency and lengthen the life of the network. In compared to conventional LEACH-based WSNs and other cutting-edge algorithms, the paper's study of the simulation results shows how successful the suggested technique is. In light of network longevity, energy use, and data transmission efficiency, the results obtained demonstrate notable improvements.

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Secure and Efficient Data Transmission for Wireless Sensor Networks by using Optimized Leach Protocol

Cited by 17 publications

References 11 publications

Optimization of Leach Protocol in Wireless Sensor Network Using Machine Learning

Optimization of Leach Protocol in Wireless Sensor Network Using Machine Learning

Interleaved Honeypot-Framing Model with Secure MAC Policies for Wireless Sensor Networks

Design and performance assessment of improved evolutionary computing based LEACH protocol for energy efficient and lifetime extension of wireless sensor network

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