A Centralized Routing for Lifetime and Energy Optimization in WSNs Using Genetic Algorithm and Least-Square Policy Iteration

Obi, Elvis; Mammeri, Zoubir; Ochia, Okechukwu E.

doi:10.3390/computers12020022

Cited by 4 publications

(3 citation statements)

References 46 publications

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“…Least-Square Policy Iteration is proposed by Obi et al [17] as an effective model-free Reinforcement Learning-based technique for optimization in WSNs. The subsequent protocol architecture is a centralized routing procedure for Lifetime Energy Optimization (LEOP) with a GA and Least-Square Policy Iteration (LSPI) for generation and energy optimization (CRPLEOGALSPI).…”

Section: Literature Reviewmentioning

confidence: 99%

Minimizing the Energy Consumption and Exploiting the NLT by E2HCA Model in WSN

Saritha,

Reddy

2024

JAIT

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In recent years, Wireless Sensor Network (WSN) has arisen as a practical option for many sectors needing smart technology. Despite its impressive credentials, Wireless Sensor Networks' excessive need for power remains a significant limitation. There is a pressing need to create a trustworthy Wireless Sensor Network with efficient energy and network lifetime due to the proliferation of tiny sensors with incomplete resources. One of the actual ways to deal with these matters is to divide the nodes into clusters. So, it is crucial to use existing energy efficiently to prevent energy waste. In this study, we suggest an Energy-Efficient Hybrid Clustering Algorithm to reduce the high-energy ingesting and increase the network lifetime of Wireless Sensor Networks. The position and speed of a gas molecule, among other Kinetic Gas Molecule Optimization particle characteristics, are initially determined by calculating their kinetic energy. Hybridization of Kinetic Gas Molecule Optimization arises from Kinetic Gas Molecule Optimization's faster convergence in space. Pelican Optimization Algorithm is used to fix the problems with Kinetic Gas Molecule Optimization by changing its inertia weight. Throughput the number of live/dead nodes are all validated against other prominent meta-heuristic methodologies in a MATLAB environment simulation of the proposed Kinetic Gas Molecule Optimization-Pelican Optimization Algorithm.

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Section: Literature Reviewmentioning

confidence: 99%

Minimizing the Energy Consumption and Exploiting the NLT by E2HCA Model in WSN

Saritha,

Reddy

2024

JAIT

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“…Xue et al [19], introduces the cross-layer-based Harris-hawks-optimization-algorithm (CL-HHO) routing protocol for WSN and k-medoids with improved artificial bee colony (K-IABC)-based energy-efficient clustering to achieve higher quality-of-service (QoS) performance. Least-Square Policy Iteration (LSPI), an effective model-free RL-based approach, is suggested by obi et al [20], to optimise network lifespan and energy usage in WSNs. A Centralised Routing Protocol for Lifetime and Energy Optimisation with a Genetic Algorithm (GA) and LSPI (CRPLEOGALSPI) is the designed protocol that was produced, which was not affected by the learning rate, selects a routing path in a given state after taking into account all feasible routing pathways.…”

Section: Literature Surveymentioning

confidence: 99%

Enhancing the Quality of Service by GBSO Splay Tree Routing Framework in Wireless Sensor Network

2023

KSII TIIS

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Quality of Service (QoS) is a critical feature of Wireless Sensor Networks (WSNs) with routing algorithms. Data packets are moved between cluster heads with QoS using a number of energy-efficient routing techniques. However, sustaining high scalability while increasing the life of a WSN's networks scenario remains a challenging task. Thus, this research aims to develop an energy-balancing component that ensures equal energy consumption for all network sensors while offering flexible routing without congestion, even at peak hours. This research work proposes a Gravitational Blackhole Search Optimised splay tree routing framework. Based on the splay tree topology, the routing procedure is carried out by the suggested method using three distinct steps. Initially, the proposed GBSO decides the optimal route at initiation phases by choosing the root node with optimum energy in the splay tree. In the selection stage, the steps for energy update and trust update are completed by evaluating a novel reliance function utilising the Parent Reliance (PR) and Grand Parent Reliance (GPR). Finally, in the routing phase, using the fitness measure and the minimal distance, the GBSO algorithm determines the best route for data broadcast. The model results demonstrated the efficacy of the suggested technique with 99.52% packet delivery ratio, a minimum delay of 0.19 s, and a network lifetime of 1750 rounds with 200 nodes. Also, the comparative analysis ensured that the suggested algorithm surpasses the effectiveness of the existing algorithm in all aspects and guaranteed end-to-end delivery of packets.

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“…Cyber-physical test bed experiments and theoretical closed-loop stability analysis enable smart manufacturing scenarios. This paper ends with questions and research ideas.GA-LSPI-based WSN centralized routing protocol was developed for lifetime and energy optimization (6) . Sink GAs generate network graph routing tables in polynomial time.…”

Section: Introductionmentioning

confidence: 99%

A Novel Packet Scheduler Policy for Multi-Hop Wireless Networks Using Diameter Based Consensus Algorithm

Joshi,

Parvati

2023

IJST

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Background: Over the time, the wireless communications have become more universal. Development of packet scheduling algorithms in wireless networks can proficiently improve delivery of packets via wireless links. Method of packet scheduling can promise quality of service and enhance transmission rate in wireless networks. Objectives: To develop an efficient packet scheduler policy to reduce the average End to End delay among the flowsand to fix the number of queues by finding diameter and TB-DVA. Methods: The timedbuffer distributed voting algorithm (TB-DVA) is a kind of voting algorithm that used to determine the maximum distance reported by all the nodes. We have used NS-3 simulator for simulation model and average throughput and average packet delay parameters are considered; we have compared the novel TB-DVA based Packet Scheduler policy with the traditional AODV Packet Scheduler policy. Mention the dataset considered. How comparison made with gold standards Findings: Comparing the new packet scheduler policy to the standard AODV packet scheduler policy, the simulation revealed that the new packet scheduler policy provides lower average end-to-end latency and high throughput. In comparison to the traditional AODV packet scheduler policy, average end-to-end delay is reduced by 7.14 percent and average throughput is enhanced by 9 percent. Novelty: The farthest node is determined by a distributed vote across all nodes.

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A Centralized Routing for Lifetime and Energy Optimization in WSNs Using Genetic Algorithm and Least-Square Policy Iteration

Cited by 4 publications

References 46 publications

Minimizing the Energy Consumption and Exploiting the NLT by E2HCA Model in WSN

Minimizing the Energy Consumption and Exploiting the NLT by E2HCA Model in WSN

Enhancing the Quality of Service by GBSO Splay Tree Routing Framework in Wireless Sensor Network

A Novel Packet Scheduler Policy for Multi-Hop Wireless Networks Using Diameter Based Consensus Algorithm

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