The Design of Wireless Monitoring Network Nodes Base on the JN5121

Zhang, Yan Jie; Wang, Xue Yong; Zhou, Hong

doi:10.4028/www.scientific.net/amm.333-335.2452

Cited by 1 publication

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“…However, it is very laborious to establish a wireless monitoring network covering an entire network. Challenges in the operation process include (a) difficulty covering the target network monitoring area due to the limited number, memory, and receiving signal range of monitoring sniffers; (b) the necessity of designing an algorithm to allocate the best channel for monitoring sniffers to improve the quality of monitoring (QoM) of the network; and (c) the inability to ensure that the monitoring network obtains all data packets transmitted in the network and the fact that data packets contain only limited information, which cannot facilitate complete performance evaluation and fault diagnosis of the network [11]. Regarding the second item, certain limitations of algorithms remain, so algorithm design is a primary research concern regarding current monitoring networks and also the topic of this paper in view of the multichannel characteristics of wireless networks.…”

Section: Introductionmentioning

confidence: 99%

Channel Allocation Algorithm Based on Swarm Intelligence for a Wireless Monitoring Network

et al. 2023

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In wireless networks, multiple monitoring nodes are used to collect users’ transmission data in real time, which can be used for fault diagnosis and analytical feedback of the wireless network. Due to the limited number of monitoring nodes, key issues include how to optimize and schedule the channel resources of each node to cover more users, obtain more network data, and maximize the quality of network monitoring. In this paper, a channel allocation algorithm based on swarm intelligence—“discrete bacterial foraging optimization”—is proposed based on the classic bacterial foraging optimization algorithm. The position of each dimension in the iterative process is discretized to binary 0 or 1 to encode and express the channel allocation problem of wireless monitoring networks, and the channel allocation scheme is optimized by location updates guided by bacterial foraging. Many simulation and practical experiments have proved the effectiveness of the algorithm, and it also has low complexity and provable convergence. Compared with similar algorithms, this algorithm improves monitoring quality by 1.428% while boosting speed by up to 32.602%. The algorithm has lower complexity, higher performance, and can converge to the optimal solution at a faster rate.

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Section: Introductionmentioning

confidence: 99%