PINC: Pickup Non-Critical Node Based k-Connectivity Restoration in Wireless Sensor Networks

Akram, Vahid Khalilpour; Dagdeviren, Zuleyha Akusta; Dağdeviren, Orhan; Challenger, Moharram

doi:10.3390/s21196418

Cited by 17 publications

(8 citation statements)

References 73 publications

(84 reference statements)

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“…This kind of recovery refers to not only doing some preprocessing such as saving neighbor node information, but also processing when the node fails. The authors in [38,40] adopt this active passive hybrid recovery method, and these two strategies are k-connected recovery algorithms, which have strong network robustness.…”

Section: Active Passive Hybridmentioning

confidence: 99%

Survey of Connectivity Restoration in 3D Wireless Ad Hoc/Sensor Networks

Chen,

Wu,

et al. 2024

International Journal of Distributed Sensor Networks

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Wireless ad hoc/sensor networks (WASN) have seen increased application in three-dimensional (3D) environments, such as underwater and aerial scenarios. However, WASN may be fragmented or unable to connect continuously due to the harsh surrounding environment or high mobility. Therefore, restoring the network connectivity and transmit data in real time is very important. This paper focuses on the critical task of restoring network connectivity in 3D WASN, a complex issue given that existing connectivity restoration algorithms for two-dimensional environments are not directly applicable or become overly complicated in 3D contexts. We present a comprehensive analysis of the current research landscape, summarizing key findings related to various aspects of 3D WASN connectivity restoration. These aspects include the application environment (underwater, in the sky, and recovery disaster), opportunities for restoration (active, passive, and active/passive), implementation strategies (clustering and sleep scheduling), and resource constraints (node deployment and movement control). Our study also proposes a classification of connectivity restoration solutions for 3D WASN, identifying existing gaps and suggesting potential future research directions. By providing specific insights and a structured overview of the field, we aim to contribute to the ongoing development of robust and resilient 3D WASN.

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Section: Active Passive Hybridmentioning

confidence: 99%

Survey of Connectivity Restoration in 3D Wireless Ad Hoc/Sensor Networks

Chen,

Wu,

et al. 2024

International Journal of Distributed Sensor Networks

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“…More recently, the authors in [25] have discussed connectivity estimation approaches for internet of things enabled wireless sensor networks. In this study, the authors review connectivity estimation approaches, describe their main ideas, and explain how they work by illustrating example networks.…”

Section: Related Workmentioning

confidence: 99%

Area Coverage Maximization under Connectivity Constraint in Wireless Sensor Networks

Tossa

Ansari

Ezin

et al. 2022

Sensors

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Wireless sensor networks (WSNs) have several important applications, both in research and domestic use. Generally, their main role is to collect and transmit data from an ROI (region of interest) to a base station for processing and analysis. Therefore, it is vital to ensure maximum coverage of the chosen area and communication between the nodes forming the network. A major problem in network design is the deployment of sensors with the aim to ensure both maximum coverage and connectivity between sensor node. The maximum coverage problem addressed here focuses on calculating the area covered by the deployed sensor nodes. Thus, we seek to cover any type of area (regular or irregular shape) with a predefined number of homogeneous sensors using a genetic algorithm to find the best placement to ensure maximum network coverage under the constraint of connectivity between the sensors. Therefore, this paper tackles the dual problem of maximum coverage and connectivity between sensor nodes. We define the maximum coverage and connectivity problems and then propose a mathematical model and a complex objective function. The results show that the algorithm, called GAFACM (Genetic Algorithm For Area Coverage Maximization), covers all forms of the area for a given number of sensors and finds the best positions to maximize coverage within the area of interest while guaranteeing the connectivity between the sensors.

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“…In recent years, network connectivity recovery has attracted extensive attention. Many studies [19][20][21][22] focus on connectivity recovery of single node failure. All existing algorithms can be divided into two categories: nonidentifying critical nodes and identifying critical nodes.…”

Section: Related Workmentioning

confidence: 99%

Distributed Connectivity Restoration Algorithm with Optimal Repair Path in Wireless Sensor and Actor Networks

Liu

Feng

et al. 2022

Journal of Sensors

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The actor nodes in wireless sensor and actor network (WSAN) are responsible for receiving the perceived data, processing and collaborating with each other. In most scenarios, maintaining the connectivity of the interactor network is necessary to plan the optimal coordinated response. However, actors are vulnerable to damage due to their limited energy and harsh environment. At worst, such failure can split the interactor network, which is affecting network performance. To restore the network connectivity, the existing methods replace the failed node by selecting a redundant node in the network. Multiple nodes may be involved in moving from the redundant node to the failed node, thus forming a repair path. However, the repair paths generated by such methods are often not optimal. In this paper, we use the gradient generation and diffusion mechanism to restore the connectivity of the interactor network and propose a gradient-based distributed connectivity recovery (GDCR) algorithm. GDCR selects an optimal repair path from the global network based on the generated gradient distribution under fully distributed and localized conditions. GDCR can timely respond to the repair and minimize the recovery range and movement overhead. Simulation results verify the performance of the proposed algorithm.

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PINC: Pickup Non-Critical Node Based k-Connectivity Restoration in Wireless Sensor Networks

Cited by 17 publications

References 73 publications

Survey of Connectivity Restoration in 3D Wireless Ad Hoc/Sensor Networks

Survey of Connectivity Restoration in 3D Wireless Ad Hoc/Sensor Networks

Area Coverage Maximization under Connectivity Constraint in Wireless Sensor Networks

Distributed Connectivity Restoration Algorithm with Optimal Repair Path in Wireless Sensor and Actor Networks

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