Multi‐objective lion optimization for energy‐efficient multi‐path routing protocol for wireless sensor networks

Singh, Onkar; Rishiwal, Vinay; Yadav, Mano

doi:10.1002/dac.4969

Cited by 15 publications

(6 citation statements)

References 21 publications

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“…The MAC protocol used for the execution of the proposed system was IEEE 802.11. To evaluate the overall performance, the proposed TMERP was compared with the EEMR, 17 ACACO, 18 PSOFCA 19 and APSA 24 . The evaluation metrics used for the performance evaluation were the routing overhead, energy consumption, hop count, average reliability, average link connectivity, and maximum round of networks 31,32 .…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

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An optimized ticket manager based energy‐aware multipath routing protocol design for IoT based wireless sensor networks

Roberts¹,

Thangavel²

2022

Concurrency and Computation

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Recently, wireless sensor networks (WSNs) and Internet of Things (IoTs) have emanated as an indispensable assets that play a critical role in revolutionizing the field of data communication. Owing to the evolution of communication standards, research trends in IoT based wireless sensor networks have been rapidly progressing toward achieving effective data routing with a prolonged network lifetime and minimized energy consumption. In this article, an optimized ticket manager based energy-aware multipath routing protocol (TMERP) is proposed. The proposed protocol design comprises three important functional entities: ticket manager (TM), routing planner (RP), and backup node (BN). The TM is responsible for controlling and monitoring all the constraints related to networking. Then, the RP minimizes the overall complexity of the optimal resource allocation by avoiding an end-to-end delay. Finally, the BN facilitates efficient data routing through the optimal selection of routing paths using the node trust evaluation and backup process to minimize data loss. Hence, the proposed multipath routing system has a distinct advantage in enhancing the network lifetime constraint with minimal energy consumption owing to the collective performance of its functional entities. The simulation results of the experimental studies show that the proposed protocol design achieved an improved performance in terms of network energy, throughput, and network operational lifetime by 39.3%, 47.9%, and 10.5%, respectively when compared with similar existing protocols.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

“…Singh et al 17 introduced an energy‐efficient multipath routing protocol using a multi‐objective lion optimisation scheme (EEMR). The authors addressed the problem of high energy consumption because different paths have unbalanced nodes.…”

Section: Related Workmentioning

confidence: 99%

An optimized ticket manager based energy‐aware multipath routing protocol design for IoT based wireless sensor networks

Roberts¹,

Thangavel²

2022

Concurrency and Computation

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“…In [13], an energy-efficient multipath routing (EEMR) protocol was developed which determined the optimum path using multi-objective lion optimization algorithm and the energy consumed was very less. The main focus was on satisfying the quality requirements like throughput, delay, packet loss and delivery ratio, energy consumption and latency.…”

Section: Related Workmentioning

confidence: 99%

DERNNet: Dual Encoding Recurrent Neural Network Based Secure Optimal Routing in WSN

Venkatesh¹,

Asha²

2023

Computer Systems Science and Engineering

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A Wireless Sensor Network (WSN) is constructed with numerous sensors over geographical regions. The basic challenge experienced while designing WSN is in increasing the network lifetime and use of low energy. As sensor nodes are resource constrained in nature, novel techniques are essential to improve lifetime of nodes in WSN. Nodes energy is considered as an important resource for sensor node which are battery powered based. In WSN, energy is consumed mainly while data is being transferred among nodes in the network. Several research works are carried out focusing on preserving energy of nodes in the network and made network to live longer. Moreover, this network is threatened by attacks like vampire attack where the network is loaded by fake traffic. Here, Dual Encoding Recurrent Neural network (DERNNet) is proposed for classifying the vampire nodes s node in the network. Moreover, the Grey Wolf Optimization (GWO) algorithm helps for transferring the data by determining best solutions to optimally select the aggregation points; thereby maximizing battery/ lifetime of the network nodes. The proposed method is evaluated with three standard approaches namely Knowledge and Intrusion Detection based Secure Atom Search Routing (KIDSASR), Risk-aware Reputation-based Trust (RaRTrust) model and Activation Function-based Trusted Neighbor Selection (AF-TNS) in terms of various parameters. These existing methods may lead to wastage of energy due to vampire attack, which further reduce the lifetime and increase average energy consumed in the network. Hence, the proposed DERNNet method achieves 31.4% of routing overhead, 23% of end-to-end delay, 78.6% of energy efficiency, 94.8% of throughput, 28.2% of average latency, 92.4% of packet delivery ratio, 85.2% of network lifetime, and 94.3% of classification accuracy.

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“…As a result, the network's layout is constantly changing, and links frequently fail due to movement limitations, wireless link sensitivity to external effects, and individual nodes' finite propagation range and leftover energy. Deepa Jeyaraj (2022) proposes SM-CSBO (sensory-modality-based cuckoo search butterfly optimisation), a new multipath routing protocol that uses a hybrid optimisation algorithm to find the best route between the source and the destination [22]. The aim is to choose the best way with the most secure links.…”

Section: International Journal On Recent and Innovation Trends In Com...mentioning

confidence: 99%

Secure Energy Aware Optimal Routing using Reinforcement Learning-based Decision-Making with a Hybrid Optimization Algorithm in MANET

Vinay Kumar,

Venkatramulu,

Rao

et al. 2023

IJRITCC

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Mobile ad hoc networks (MANETs) are wireless networks that are perfect for applications such as special outdoor events, communications in areas without wireless infrastructure, crises and natural disasters, and military activities because they do not require any preexisting network infrastructure and can be deployed quickly. Mobile ad hoc networks can be made to last longer through the use of clustering, which is one of the most effective uses of energy. Security is a key issue in the development of ad hoc networks. Many studies have been conducted on how to reduce the energy expenditure of the nodes in this network. The majority of these approaches might conserve energy and extend the life of the nodes. The major goal of this research is to develop an energy-aware, secure mechanism for MANETs. Secure Energy Aware Reinforcement Learning based Decision Making with Hybrid Optimization Algorithm (RL-DMHOA) is proposed for detecting the malicious node in the network. With the assistance of the optimization algorithm, data can be transferred more efficiently by choosing aggregation points that allow individual nodes to conserve power The optimum path is chosen by combining the Particle Swarm Optimization (PSO) and the Bat Algorithm (BA) to create a fitness function that maximizes across-cluster distance, delay, and node energy. Three state-of-the-art methods are compared to the suggested method on a variety of metrics. Throughput of 94.8 percent, average latency of 28.1 percent, malicious detection rate of 91.4 percent, packet delivery ratio of 92.4 percent, and network lifetime of 85.2 percent are all attained with the suggested RL-DMHOA approach.

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Multi‐objective lion optimization for energy‐efficient multi‐path routing protocol for wireless sensor networks

Cited by 15 publications

References 21 publications

An optimized ticket manager based energy‐aware multipath routing protocol design for IoT based wireless sensor networks

An optimized ticket manager based energy‐aware multipath routing protocol design for IoT based wireless sensor networks

DERNNet: Dual Encoding Recurrent Neural Network Based Secure Optimal Routing in WSN

Secure Energy Aware Optimal Routing using Reinforcement Learning-based Decision-Making with a Hybrid Optimization Algorithm in MANET

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