Systematic study of topology control methods and routing techniques in wireless sensor networks

Kavra, Radhika; Gupta, Anjana; Kansal, Sangita

doi:10.1007/s12083-022-01325-4

Cited by 17 publications

(13 citation statements)

References 164 publications

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“…In the context of network QoS, a process-based quality parameter ensures that the network has a long life, with minimal packet loss, less delay, high accuracy, and fast sensing capabilities [30]. QoS is improved with the utilization of clustering in WSN where retransmission and packet loss will be reduced considerably [5].…”

Section: Improve Quality Of Servicementioning

confidence: 99%

Certain Investigation on Improved Cluster Protocol with Trust security for Wireless Sensor Networks

Ramesh¹,

Renjith

AntoBennet

et al. 2022

IJEER

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Immense development of Micro Electro Mechanical Systems (MEMS) made an incredible advancement in wireless technology. The Wireless Sensor Network (WSN) has created many opportunities for the development of various applications in the fields of military, research, medical, engineering, etc. In this research article, a novel trust-based energy-aware clustering protocol is proposed. The clustering algorithm concentrates on reducing the time spent on cluster formation, controlling redundant data forwarding, and prolonging the network's lifespan. In this model, clustered nodes are classified into three levels like Cluster heads (CH), secondary CHs, and sensor nodes (SN) are used to sense the environmental changes and report to the Base Station (BS). An extension of the lifetime of a WSN is possible by the use of secure multi-hop routing with an aggregation technique to forward data from a cluster to the BS. Compared to relevant works on clustering with the routing protocol, the simulation result showed improved energy efficiency and network lifetime.

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Section: Improve Quality Of Servicementioning

confidence: 99%

Certain Investigation on Improved Cluster Protocol with Trust security for Wireless Sensor Networks

Ramesh¹,

Renjith

AntoBennet

et al. 2022

IJEER

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“…Over the years, various researchers have solved the optimal routing or path-finding problem. Most of these works in the field of wireless sensor networks (WSNs), fog, and IoT systems focus on optimal routing protocols and data forwarding techniques, which in most cases have a single objective, e.g., optimize energy usage [ 5 , 6 , 7 ]. As concluded in [ 5 ], one of the drawbacks of existing routing techniques is fixed static routing and the reliability of decision-making nodes.…”

Section: Introductionmentioning

confidence: 99%

“…Nature-inspired algorithms, including particle swarm optimization (PSO), are used for energy-efficient clustering and routing, optimal coverage, data aggregation, and sensor localization, as classified in [ 8 ]. The systematic study of topology control methods and routing techniques in wireless sensor networks [ 7 ] reviewed recent articles, including topology-aware PSO and ant colony optimization (ACO)-based routing techniques in static and mobile wireless sensor networks, and stated that these techniques do not incorporate delay-sensitive routing or timely data delivery. According to [ 7 ], the latest routing algorithms based on PSO and ACO techniques lag where the topology and routing requirement are delay-sensitive and concerned with data delivery ratio, throughput, and quality of service (QoS).…”

Section: Introductionmentioning

confidence: 99%

“…The systematic study of topology control methods and routing techniques in wireless sensor networks [ 7 ] reviewed recent articles, including topology-aware PSO and ant colony optimization (ACO)-based routing techniques in static and mobile wireless sensor networks, and stated that these techniques do not incorporate delay-sensitive routing or timely data delivery. According to [ 7 ], the latest routing algorithms based on PSO and ACO techniques lag where the topology and routing requirement are delay-sensitive and concerned with data delivery ratio, throughput, and quality of service (QoS). Although several real-time routing techniques attempt to satisfy minimum latency and maximum throughput, the study [ 7 ] concluded that the research in this field is in an early stage and limited to some well-known protocols.…”

Section: Introductionmentioning

confidence: 99%

“…According to [ 7 ], the latest routing algorithms based on PSO and ACO techniques lag where the topology and routing requirement are delay-sensitive and concerned with data delivery ratio, throughput, and quality of service (QoS). Although several real-time routing techniques attempt to satisfy minimum latency and maximum throughput, the study [ 7 ] concluded that the research in this field is in an early stage and limited to some well-known protocols. These findings are further supported by swarm-intelligence-based optimization techniques for the WSN survey [ 9 ], which concluded that there are still some open research challenges, including weighing the energy consumption, QoS, security, and reliability of the network.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Multi-Objective Path Optimization in Fog Architectures Using the Particle Swarm Optimization Approach

Morkevičius

Liutkevičius

Venčkauskas

2023

Sensors

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IoT systems can successfully employ wireless sensor networks (WSNs) for data gathering and fog/edge computing for processing collected data and providing services. The proximity of edge devices to sensors improves latency, whereas cloud assets provide higher computational power when needed. Fog networks include various heterogeneous fog nodes and end-devices, some of which are mobile, such as vehicles, smartwatches, and cell phones, while others are static, such as traffic cameras. Therefore, some nodes in the fog network can be randomly organized, forming a self-organizing ad hoc structure. Moreover, fog nodes can have different resource constraints, such as energy, security, computational power, and latency. Therefore, two major problems arise in fog networks: ensuring optimal service (application) placement and determining the optimal path between the user end-device and the fog node that provides the services. Both problems require a simple and lightweight method that can rapidly identify a good solution using the constrained resources available in the fog nodes. In this paper, a novel two-stage multi-objective path optimization method is proposed that optimizes the data routing path between the end-device and fog node(s). A particle swarm optimization (PSO) method is used to determine the Pareto Frontier of alternative data paths, and then the analytical hierarchy process (AHP) is used to choose the best path alternative according to the application-specific preference matrix. The results show that the proposed method works with a wide range of objective functions that can be easily expanded. Moreover, the proposed method provides a whole set of alternative solutions and evaluates each of them, allowing us to choose the second- or third-best alternative if the first one is not suitable for some reason.

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CO-LEACH: Cooperative Data Collection Protocol for Data-Heterogeneous WSNs

Zhang,

Wu,

et al. 2024

Lecture Notes in Computer Science

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Systematic study of topology control methods and routing techniques in wireless sensor networks

Cited by 17 publications

References 164 publications

Certain Investigation on Improved Cluster Protocol with Trust security for Wireless Sensor Networks

Certain Investigation on Improved Cluster Protocol with Trust security for Wireless Sensor Networks

Multi-Objective Path Optimization in Fog Architectures Using the Particle Swarm Optimization Approach

CO-LEACH: Cooperative Data Collection Protocol for Data-Heterogeneous WSNs

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