A hybrid clustering routing protocol based on machine learning and graph theory for energy conservation and hole detection in wireless sensor network

Masoud, Mohammad; Jaradat, Yousef; Jannoud, Ismael; Sibahee, Mustafa A. Al

doi:10.1177/1550147719858231

Cited by 18 publications

(9 citation statements)

References 35 publications

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“…In addition, the differences between the present work and other proposals are presented. Hassan [24] Wang et al [25] Guodong [26] Wang et al [27] Passos [7] Masoud [6] Afaneh [2] Wang [29] Current Work…”

Section: Related Workmentioning

confidence: 99%

“…Thus, the central offices of local governments require the monitoring and surveillance of sensors placed in previously defined areas or strata of cities to make the operation of services effective, such as traffic management systems, health management (telemedicine), rubbish collection systems, and image recognition systems, among others [ 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Novel Approach Sizing and Routing of Wireless Sensor Networks for Applications in Smart Cities

Inga

Ortega

2021

Sensors

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Citizens are expected to require the growth of multiple Internet of Things (IoT) -based applications to improve public and private services. According to their concept, smart cities seek to improve the efficiency, reliability, and resilience of these services. Consequently, this paper searches for a new vision for resolving problems related to the quick deployment of a wireless sensor network (WSN) by using a sizing model and considering the capacity and coverage of the concentrators. Additionally, three different routing models of these technology resources are presented as alternatives for each WSN deployment to ensure connectivity between smart meters and hubs required for smart metering. On the other hand, these solutions must reduce costs when this type of wireless communication network is deployed. The present work proposes various optimization models that consider the physical and network layers in order to integrate different wireless communication technologies, thus reducing costs in terms of the minimum number of data aggregation points. Using a heterogeneous wireless network can reduce resource costs and energy consumption in comparison to a single cellular technology, as proposed in previous works. This work proposes a sizing model and three different models for routing wireless networks. In each case, constraints are evaluated and can be associated with different real-world scenarios. This document provides an optimization model that encompasses all of the proposed constraints; due to the combinatorial nature of the problem, this would require a heuristic technique.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Novel Approach Sizing and Routing of Wireless Sensor Networks for Applications in Smart Cities

Inga

Ortega

2021

Sensors

View full text Add to dashboard Cite

show abstract

“…Sensor nodes can send their collected data directly to the sink node [6], but this consumes more energy and leads to the node's premature death, introducing other problems into the network such as the coverage/ hole problem [7]. Clustering is utilized to balance energy consumption between sensor nodes.…”

Section: Introductionmentioning

confidence: 99%

Genetic Algorithm Energy Optimization in 3D WSNs with Different Node Distributions

Jaradat¹,

Masoud²,

Jannoud³

et al. 2022

Intelligent Automation &Amp; Soft Computing

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Optimal node clustering in wireless sensor networks (WSNs) is a major issue in reducing energy consumption and extending network node life time and reliability measures. Many techniques for optimizing the node clustering process in WSN have been proposed in the literature. The metaheuristic algorithms are a subset of these techniques. Genetic algorithm (GA) is an evolutionary metaheuristic technique utilized to improve the network reliability and extending the network life time by optimizing the clustering process in the network. The GA dynamic clustering (GA-DC) algorithm is proposed in this paper to extend the network reliability and node life time of three dimensional (3D) WSN. The GA-DC algorithm made use of an improved fitness function that takes into account a variety of metrics such as energy expenditure per protocol round, clustering distance, and the number of long-distance wireless connections. There have been two types of simulation scenarios run. First, simulation results show that the GA-DC algorithm increases network life time by 80% and network throughput by 55% when compared to the well-known LEACH protocol. Second, simulation results show that the uniform node distribution outperforms the normal and exponential distributions in terms of network life time by 5.7% and 7%, network reliability by 4.2% and 76%, and data throughput by 10.85% and 19.54%, respectively

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“…Other classes of distributed algorithms have benefited from a topological characterisation, including distributed mutual exclusion algorithms for controlling concurrent access to shared resources 28 . Topology-informed routing algorithms have been proposed to reduce energy consumption and prolong network lifetime 29 . Concurrently, network topology optimisation strategies have been deployed to ensure uniformly distributed traffic and more efficient use of resources 30 .…”

Section: Introductionmentioning

confidence: 99%

Topological network features determine convergence rate of distributed average algorithms

Sirocchi

Bogliolo²

2022

Sci Rep

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Gossip algorithms are message-passing schemes designed to compute averages and other global functions over networks through asynchronous and randomised pairwise interactions. Gossip-based protocols have drawn much attention for achieving robust and fault-tolerant communication while maintaining simplicity and scalability. However, the frequent propagation of redundant information makes them inefficient and resource-intensive. Most previous works have been devoted to deriving performance bounds and developing faster algorithms tailored to specific structures. In contrast, this study focuses on characterising the effect of topological network features on performance so that faster convergence can be engineered by acting on the underlying network rather than the gossip algorithm. The numerical experiments identify the topological limiting factors, the most predictive graph metrics, and the most efficient algorithms for each graph family and for all graphs, providing guidelines for designing and maintaining resource-efficient networks. Regression analyses confirm the explanatory power of structural features and demonstrate the validity of the topological approach in performance estimation. Finally, the high predictive capabilities of local metrics and the possibility of computing them in a distributed manner and at a low computational cost inform the design and implementation of a novel distributed approach for predicting performance from the network topology.

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A hybrid clustering routing protocol based on machine learning and graph theory for energy conservation and hole detection in wireless sensor network

Cited by 18 publications

References 35 publications

Novel Approach Sizing and Routing of Wireless Sensor Networks for Applications in Smart Cities

Novel Approach Sizing and Routing of Wireless Sensor Networks for Applications in Smart Cities

Genetic Algorithm Energy Optimization in 3D WSNs with Different Node Distributions

Topological network features determine convergence rate of distributed average algorithms

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