Analytical models for randomized neighbor discovery protocols based on collision detection in wireless ad hoc networks

Sorribes, Jose Vicente; Lloret, Jaime; Peñalver, Lourdes

doi:10.1016/j.adhoc.2021.102739

Cited by 7 publications

(2 citation statements)

References 35 publications

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“…Shen et al 18 proposed a new beacon strategy, called a talk‐listen‐ack beacon, which increases the discovery probability while reducing the time slot length, and uses a random retreat mechanism to avoid the discovery probability of talk‐listen‐ack with continuous conflict. Sorribes et al 19 proposed an analysis model for random neighbor discovery protocols in static single‐hop environments based on conflict detection when conflicts exist in static single‐hop wireless ad hoc networks.…”

Section: Related Workmentioning

confidence: 99%

Three‐dimensional scan‐based algorithm for directional neighbor discovery in ad hoc networks

Lan

Liu

Wang³

et al. 2023

Int J Communication

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In recent years, neighbor discovery techniques using directional antennas have attracted widespread attention. Most currently available directional neighbor discovery techniques are designed based on two-dimensional (2D) space. Although these algorithms can accomplish the discovery between nodes, the algorithm portability is poor for three-dimensional (3D) platforms, and the application scenarios are limited since new communication scenarios such as unmanned aerial vehicle (UAV) groups and maritime fleets emerge where information needs to be delivered in real time and nodes are located in 3D space. This paper proposes a new deterministic directional neighbor discovery algorithm in 3D space named 3D scan-based algorithm (3D-SBA) to meet the needs of the line-of-sight (LOS) scenes. Four existing neighbor discovery algorithms, namely, SBA-based random mode selection (SBA-R), quorum, complete random algorithm (CRA), and SBA-based leader election algorithm (LE), have been extended to our proposed 3D algorithm model for simulation and comparative analysis with 3D-SBA. The simulation results show that the 3D-SBA algorithm consumes 51.15%, 180.20%, 9.48%, and 17.49% of the time slots compared with the four existing algorithms mentioned above. However, the quorum algorithm has a very high node collision rate, up to 92.11%.Ultimately, the 3D-SBA algorithm has the best performance considering the conflicts and the density of network nodes.

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Section: Related Workmentioning

confidence: 99%

Three‐dimensional scan‐based algorithm for directional neighbor discovery in ad hoc networks

Lan

Liu

Wang³

et al. 2023

Int J Communication

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“…Many researchers have done work for fire prevention and detection, but not on the reasonable practical scale A high version of the wildfire preventer has been proposed to be implemented. The referred articles [6,7] have implemented a node MCU for transferring data thought to use this because it has a lot of advantages. But an extra module for Wi-Fi is not preferable to designing a power supply circuit.…”

Section: Introductionmentioning

confidence: 99%

A Design and Development of the Smart Forest Alert Monitoring System Using IoT

Krishnamoorthy¹,

Asif²,

Kumar³

et al. 2023

Journal of Sensors

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Forest is one of the main sources of living organisms. Its needs start from the human breath to usage of the wood. But due to many reasons, area occupied by the forest is reducing every year. The reasons behind these environmental impacts are natural disasters (forest fires), deforestation activities, and unlawful actions. Forest fire could be creating most serious threat to wild animals and resources of human welfares. The primary phenomenon of the wild fire occurrence is circumstance hotness of the forest. The dry and hot atmosphere caused the fire in the forest. The deforestation and smuggling activities are also tridents to the available forest. The main consideration of this article is to detect wildfires in advance and protect forest resources from social crimes through advanced sensor integration in the IoT (Internet of Things) environment. A smart forest alert monitoring system has been proposed in this article to avoid forest mishap over by automated self-decision-making protective actions such as parameter measures and alert and implementing the harm mitigation actions related to the hot temperature, humidity, smoke, and smuggling of trees. All the sensors work as per the algorithm designed by the specific application of IoT (Internet of Things). The accurate predictions of the forest fire events and ensuring the forest safety have been tested and verified by a conducted case study on the real forest zone environment.

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