Improvement of battery lifetime in software‐defined network using particle swarm optimization based cluster‐head gateway switch routing protocol with fuzzy rules

Sheela, Maria Antony Sahaya; Prabakaran, R.

doi:10.1111/coin.12271

Cited by 6 publications

(5 citation statements)

References 16 publications

(15 reference statements)

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“…If after three repetitions the answer does not change, then the waterwheel's position can be modified using Eq. (10).…”

Section: Phase 1: Position Identification and Hunting Of Insectsmentioning

confidence: 99%

“…There are a number of different security routing methods [8,9], including the most fundamental routing. In order for routers in a network to regulate the best path to take between any two points in the system, they need to be able to interconnect and share relevant information [10]. The primary function of a routing system is to determine the most efficient path for sending data from one device to another.…”

Section: Introductionmentioning

confidence: 99%

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An Energy-Aware Cluster Head Selection and Optimal Route Selection Algorithm for Maximizing Network Lifetime in MANETs

Devarayasamudram,

Chandrashekar,

Chetla

et al. 2024

MMEP

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Quality of Service (QoS) is a crucial aspect of Mobile Ad Hoc Networks (MANET) that needs examination to demonstrate optimal performance. The scientific community is increasingly concerned with the challenge of developing an energy-aware clustering method for MANETs. This is owing to the fact that the battery-operated sensor devices that form the backbone of these wireless networks cannot be recharged. The selection of a cluster's leader is a difficult problem in MANET. Additionally, the research focuses on Optimal Route Selection (ORS) within the MANET context, acknowledging the significance of establishing efficient communication paths between cluster heads and member nodes. Through the integration of a reliability pair factor and node energy considerations, the proposed ORS algorithm generates optimal paths based on maximizing energy efficiency while minimizing the sum of hops between nodes. The study suggests a new algorithm based on the way waterwheel plants move and change their places as they explore and exploit new territory in the quest for food. The suggested method is named Binary Waterwheel Plant Algorithm (BWPA). In this method, a novel model is used to represent both the binary search space and the mapping from continuous to discrete spaces. Particularly, mathematical models of the fitness and cost functions used by the algorithm are constructed. Through the use of a reliability pair factor and node energy, the proposed research paper on Optimal Route Selection (ORS) generates the optimal path between the cluster head and member node and establishes the path based on the maximum energy and sum of hops among the nodes. By fusing the reactive power of differential evolution with the exhaustive search efficiency of the BWPA, the proposed method extends the life of networks. The recommended method increases node lifetime by compounding the dynamic capabilities of discrepancy evolution with the high effectiveness of search.

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“…If after three repetitions the answer does not change, then the waterwheel's position can be modified using Eq. (10).…”

Section: Phase 1: Position Identification and Hunting Of Insectsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Energy-Aware Cluster Head Selection and Optimal Route Selection Algorithm for Maximizing Network Lifetime in MANETs

Devarayasamudram,

Chandrashekar,

Chetla

et al. 2024

MMEP

View full text Add to dashboard Cite

show abstract

“…This protocol modifies the DSDV protocol by implementing a stratified cluster head‐to‐entryway routing mechanism to send data from source nodes to destinations. The disadvantage of the CGSR routing protocol is that the frequent change in cluster head impacts the performance of the routing protocol since the cluster head nodes are involved in the cluster head selection process rather than concentrating on packet delivery 150 …”

Section: Taxonomy Of Iot Routing Protocolsmentioning

confidence: 99%

“…The disadvantage of the CGSR routing protocol is that the frequent change in cluster head impacts the performance of the routing protocol since the cluster head nodes are involved in the cluster head selection process rather than concentrating on packet delivery. 150 TORA. TORA routing protocol is a highly adaptable and distributed algorithm protocol that enables alternative paths for data transmission in the network.…”

Section: Hierarchical Routingmentioning

confidence: 99%

The importance of nature‐inspired metaheuristic algorithms in the data routing and path finding problem in the internet of things

Dong‐liang

Bei

Wang

2023

Int J Communication

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Summary Over the last decade, the Internet of Things (IoT) has become ever more popular, as is evident from its role in changing the human lifestyle and conferring remarkable privileges for them. It has a significant presence in various crucial areas, including smart cities, smart factories, manufacturing, transportation, and healthcare. Massive amounts of data generated by IoT devices have the potential to endanger the lifetime of nodes in IoT‐based networks due to increased communication power consumption. It has become crucial to propose solutions for network‐based issues, such as quality of service, security, network heterogeneity, congestion avoidance, reliable routing, and energy conservation. To address the mentioned problems, routing protocols play a critical role in data transmission among heterogeneous items. In such environments, routing refers to constructing routes between mobile nodes. Since identifying optimal routes among IoT nodes and establishing an effective routing protocol in an IoT network are an NP‐hard issue, employing metaheuristic algorithms may be a viable solution to overcome this problem. Various IoT routing protocols based on metaheuristic algorithms have been presented in recent years, but there is still a lack of systematic study for reviewing the existing works. The current study emphasizes the impact of metaheuristic algorithms in the IoT routing problem, discusses the optimization models, presents a comprehensive comparison of protocols based on critical parameters, and eventually suggests some hints for future studies.

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“…Enhancement of data transmission and reduction of energy hole problem by enhancing the routing discovery using Hybrid Improved Whale with Particle Swarm Optimization algorithm (HIW-PSO) in SDN-MANET for various applications is the key objective of this work. Cluster heads in MANETs are selected based on Particle Swarm Optimization (PSO) [22]. Basically, SDN architecture involves three planes namely the data plane, control plane and application plane.…”

Section: Proposed Modelmentioning

confidence: 99%

Hybrid Genetic Algorithm with Directed Acyclic Graph for Enhancing Data Transmission and Reducing Energy Hole Problem

sheela¹,

Prabakaran

Arun

2023

Preprint

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Software Defined Networking (SDN) is a smart architecture which enables a network to be controlled in a centralized manner. It plays a vital role in several real-time applications and has three planes- the data plane, control plane and application plane. The architecture of SDN is simple and is inbuilt with a centralized controller at the control plane. SDN operates efficiently on Mobile Adhoc NETworks (MANET) in various environments and applications. Due to the mobility of nodes, several research issues are faced by SDN-MANET. Some of the challenges include a large overhead and less packet delivery ratio. To overcome these challenges, a Hybrid Improved Whale optimization with Particle Swarm Optimization algorithm (HIW-PSO) is proposed with Directed Acyclic Graphs (DAG) topology. This algorithm enhances the data transmission by reducing the energy hole issue. The Directed Acyclic Graphs (DAG) topology is constructed by calculating the polynomial-time for lining of all participant nodes through its edges. The proposed algorithm is evaluated for packet delivery ratio, throughput, delay, network lifetime and energy consumption. Furthermore, the performance of HIW-PSO is evaluated against other standard contemporary optimization algorithms EHO and M-LWO. As a result, the proposed method achieves an energy consumption of 35.8%, PDR of 53.2 %, a throughput of 84.8%, network lifetime of 75.4% and delay of 23.8%.

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Improvement of battery lifetime in software‐defined network using particle swarm optimization based cluster‐head gateway switch routing protocol with fuzzy rules

Cited by 6 publications

References 16 publications

An Energy-Aware Cluster Head Selection and Optimal Route Selection Algorithm for Maximizing Network Lifetime in MANETs

An Energy-Aware Cluster Head Selection and Optimal Route Selection Algorithm for Maximizing Network Lifetime in MANETs

The importance of nature‐inspired metaheuristic algorithms in the data routing and path finding problem in the internet of things

Hybrid Genetic Algorithm with Directed Acyclic Graph for Enhancing Data Transmission and Reducing Energy Hole Problem

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