AI Article Synopsis
- A new self-assembling network routing algorithm addresses connectivity issues in communication networks caused by movement and environmental factors, particularly for robot clusters.
- It calculates dynamic forwarding probability based on node contributions to network connectivity and introduces a feedback mechanism to enhance robustness.
- The algorithm also assesses link quality using metrics like hop count and energy levels, optimizes node selection, and maintains stable connections, resulting in a network connectivity rate of over 97%, reduced delays, and increased network longevity.
Article Abstract
An enhanced self-assembling network routing algorithm is proposed for the problem of weak connectivity of communication networks caused by factors such as movement or environmental interference in the construction and operation, and the maintenance of construction robot clusters. Firstly, the dynamic forwarding probability is calculated based on the contribution of nodes joining routing paths to network connectivity, and the robust connectivity of the network is achieved by introducing the connectivity feedback mechanism; secondly, the influence of link quality evaluation index Q balanced hop count, residual energy, and load on link stability is used to select appropriate neighbors for nodes as the subsequent hop nodes; finally, the dynamic characteristics of nodes are combined with the topology control technology to eliminate low-quality links and optimize the topology by link maintenance time prediction and to set robot node priority. The simulation results show that the proposed algorithm can guarantee a network connectivity rate above 97% under heavy load, reduce the end-to-end delay, and improve the network survival time, providing a theoretical basis for achieving stable and reliable interconnection between building robot nodes.
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|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10221509 | PMC |
| http://dx.doi.org/10.3390/s23104754 | DOI Listing |
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