A survey of connectivity restoration in wireless sensor networks

Wu, Chunhui; Chen, Hongsheng; Liu, Jiangang

doi:10.1109/cecnet.2013.6703273

Cited by 9 publications

(4 citation statements)

References 15 publications

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“…Network connectivity is very important for real-time data transmission [25]. To ensure that the network can transmit data efficiently and stably, it is essential to determine that the nodes in the network are connected to each other.…”

Section: Target Area Determinationmentioning

confidence: 99%

A Medium Access Control Protocol Based on Interference Cancellation Graph for AUV-Assisted Internet of Underwater Things

2023

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With the booming development of marine exploration technology, new studies such as the oceanix city, smart coastal city, and underwater smart cities have been proposed, and the Internet of Underwater Things (IoUT) has received a lot of attention. Data collection is an important application of the IoUT. The common method is to collect data by traversing the network using underwater intelligent devices, such as Autonomous Underwater Vehicles (AUVs). However, traditional data collection methods focus more on issues, such as path planning or the task assignment of AUVs. It is commonly known that the MAC protocol plays a crucial role in data transmission, which is designed to solve the competition issue for shared channels. However, the research on MAC is very challenging owing to the characteristics of hydroacoustic communication, e.g., the low bandwidth, high error rate, and long transmission latency. Hence, this paper proposes a MAC protocol based on an Interference Cancellation Graph (ICG-MAC) for AUV-assisted IoUT. It ensures that AUVs can join the network for data transmission immediately after arriving at the target area and they do not interfere with the normal work of other sensor nodes. Firstly, the target area to be reached by an AUV for data collection is defined according to the node degree and residual energy; then the interference model between neighboring nodes is analyzed and an Interference Cancellation Graphx is established, based on which the time slots are allocated for sensor nodes; and finally, the AUV moves to the target area for conflict-free data collection. The simulation results show that the proposed algorithm outperforms the comparison algorithms in terms of the network throughput and energy consumption. With the assistance of an AUV, better network connectivity and higher network traffic can be obtained.

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Section: Target Area Determinationmentioning

confidence: 99%

A Medium Access Control Protocol Based on Interference Cancellation Graph for AUV-Assisted Internet of Underwater Things

2023

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“…There are many traditional connectivity recovery methods in the two-dimensional plane. Previously, we reviewed the connectivity recovery algorithms in WSN in the twodimensional plane [1], mainly including deploying nodes at appropriate locations to achieve network connectivity recovery and waking up mobile nodes to move to corresponding locations to achieve connectivity recovery. Generally, the number of relay nodes deployed and the distance of node movement are two important factors to consider in connectivity recovery.…”

Section: Introductionmentioning

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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“…The second challenge lies in the high time complexities during real-time executions. Note that the real-time execution is an important indicator to evaluate the resilience of the USNET, since it relates to the self-healing time and even the degree of disruptions [22]. For example, the algorithm in [9] needs to find the global cut vertexes of the WSN during the self-healing process, which makes its on-line execution time complexity increase with the size of the WSN.…”

Section: Introductionmentioning

confidence: 99%

Resilient UAV Swarm Communications with Graph Convolutional Neural Network

Mou¹,

Gao²,

Liu³

et al. 2021

Preprint

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In this paper, we study the self-healing problem of unmanned aerial vehicle (UAV) swarm network (USNET) that is required to quickly rebuild the communication connectivity under unpredictable external disruptions (UEDs). Firstly, to cope with the one-off UEDs, we propose a graph convolutional neural network (GCN) and find the recovery topology of the USNET in an on-line manner. Secondly, to cope with general UEDs, we develop a GCN based trajectory planning algorithm that can make UAVs rebuild the communication connectivity during the self-healing process. We also design a meta learning scheme to facilitate the on-line executions of the GCN. Numerical results show that the proposed algorithms can rebuild the communication connectivity of the USNET more quickly than the existing algorithms under both one-off UEDs and general UEDs. The simulation results also show that the meta learning scheme can not only enhance the performance of the GCN but also reduce the time complexity of the on-line executions.

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A survey of connectivity restoration in wireless sensor networks

Cited by 9 publications

References 15 publications

A Medium Access Control Protocol Based on Interference Cancellation Graph for AUV-Assisted Internet of Underwater Things

A Medium Access Control Protocol Based on Interference Cancellation Graph for AUV-Assisted Internet of Underwater Things

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

Resilient UAV Swarm Communications with Graph Convolutional Neural Network

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