Damage Recovery Method for Air–Sea Cross-Domain Communication Network Based on Improved Dijkstra and Load Balancing
Source abstract
Abstract
With the complexity of the future battlefield and the increasing demand for multi-domain operations, the importance of air–sea cross-domain communication networks is rising. Communication technology connecting air and sea faces many challenges: for example, multi-node failure may lead to network partition, communication interruption and even task failure. Therefore, research on the multi-node failure recovery method of air–sea cross-domain communication networks has become an urgent need to ensure their stability and mission continuity. This paper proposes a link selection strategy based on an improved Dijkstra algorithm and load balancing on the basis of link quality prediction. The simulation results show that the algorithm can effectively achieve network recovery.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Energy Efficient Wireless Sensor Networks · Satellite Communication Systems · Advanced Optical Network Technologies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
National Key Laboratory of Underwater Acoustic Technology, Harbin Engineering University, Harbin 150001, China
Key Laboratory of Marine Information Acquisition and Security (Harbin Engineering University), Ministry of Industry and Information Technology, Harbin 150001, China
College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001, China
Sanya Nanhai Innovation and Development Base of Harbin Engineering University, Sanya 572024, China
Funding
National Key Research and Development Program of China · Fundamental Research Funds for Central Universities of China · Innovation Fund Project of Marine Defense Technology Innovation Center in China · Sanya Science and Technology Innovation Project of China
References (30)
Show source-provided references
1. Research Progress and Development Trend of Air-Sea Cross-domain Communication
2. Cross-Domain Communication Buoy System Based on Optimal Communication Link Selection
3. Formation of robust multi-agent networks through self-organizing random regular graphs10.1109/TNSE.2015.2503983 ↗
4. Multi-UAV Collaborative Surveillance Network Recovery via Deep Reinforcement Learning10.1109/JIOT.2024.3446878 ↗
5. Xing, M., Deng, H., and Han, R. (2023). ICN-Oriented Mobility Support Method for Dynamic Allocation of Mobile Data Flows. Electronics, 12.10.3390/electronics12071701 ↗
6. Vijaya Vardan Reddy, S.P., Kishore, V.V., Diwakaran, S., Sujatha, V., and Jayakumar, T. (2024, January 4–5). A Robust Design of Fault Nodes Identification and Recovery Model Over Wireless Sensor Network. Proceedings of the Ninth International Conference on Science Technology Engineering and Mathematics (ICONSTEM), Chennai, India.10.1109/ICONSTEM60960.2024.10568749 ↗
7. Caleb, S., and Thangaraj, S.J.J. (2023, January 21–23). Enhancing Fault Tolerance in Wireless Mesh Networks through Adaptive and Resilient Routing Protocols. Proceedings of the 2023 International Conference on Data Science, Agents & Artificial Intelligence (ICDSAAI), Chennai, India.10.1109/ICDSAAI59313.2023.10452547 ↗
8. Hu, P., Xue, H., Wu, C., Guo, M., Li, J., Chen, X., Liu, S., Zhou, L., and Xie, S. (2024, January 23–26). HGR: A Hybrid Global Graph-Based Recovery Approach for Cloud Storage Systems with Failure and Straggler Nodes. Proceedings of the 44th International Conference on Distributed Computing Systems (ICDCS), Jersey City, NJ, USA.10.1109/ICDCS60910.2024.00075 ↗
9. Flow-aware multi-topology adaptive routing10.1109/LCOMM.2014.2334314 ↗
10. Menth, M., and Martin, R. (2005, January 16–19). Network resilience through multi-topology routing. Proceedings of the Fifth International Workshop on Design of Reliable Communication Networks, Naples, Italy.
11. Gardner, M.T., May, R., Beard, C., and Medhi, D. (2014, January 1–3). Using multi-topology routing to improve routing during geographically correlated failures. Proceedings of the 2014 10th International Conference on the Design of Reliable Communication Networks (DRCN), Ghent, Belgium.10.1109/DRCN.2014.6816134 ↗
12. Cevher, S., Ulutas, M., Altun, S., and Hokelek, I. (2016, January 27–30). Multi topology routing based IP fast re-route for software defined networks. Proceedings of the 2016 IEEE Symposium on Computers and Communication (ISCC), Messina, Italy.10.1109/ISCC.2016.7543903 ↗
13. Communication topology reconstruction method for multi-agent cooperative control in polymorphic networks
14. A double connectivity recovery algorithm in partition based on backbone polygon in sensor networks
15. Ma, G.Z. (2017). Fault-Tolerant Topology Control and Connectivity Restorantion in Wireless Sensor Networks. [Ph.D. Thesis, Beijing University of Posts and Telecommunications].
16. Multi-objective optimized connectivity restoring of disjoint segments using mobile data collectors in wireless sensor network10.1186/s13638-017-0852-0 ↗
17. Du, R., Fei, H., and W Zhang, W. (2016, January 10–11). Research and Design of a SpaceWire Network Dynamic Reconfiguration Method Based on Dijkstra Algorithm. Proceedings of the 2016 9th International Symposium on Computational Intelligence and Design (ISCID), Hangzhou, China.10.1109/ISCID.2016.1046 ↗
18. Shortest Path Problem under Pythagorean Fuzzy Network Using Dijkstra’s Algorithm
19. AMPLE: An adaptive traffic engineering system based on virtual routing topologies10.1109/MCOM.2012.6163600 ↗
20. Altenhofen, K., Zobel, J., and Scheuermann, B. (2024, January 3–6). Increasing Network Resilience Through Dynamic Routing with Disjoint Paths. Proceedings of the 2024 IFIP Networking Conference (IFIP Networking), Thessaloniki, Greece.10.23919/IFIPNetworking62109.2024.10619871 ↗
21. Willis, P., Shenoy, N., Hamilton, J., and Pan, Y. (2024, January 2–4). Resiliency in Networks Through Meshed Trees. Proceedings of the 15th International Conference on Network of the Future (NoF), Castelldefels, Spain.10.1109/NoF62948.2024.10741359 ↗
22. Zuo, J.X. (2022). Research on Topological Reconstruction of UAV Swarm Network and Key Technology. [Master’s Thesis, Xi’an Technological University].
23. SIDR: A swarm intelligence-based damage-resilient mechanism for UAV swarm networks10.1109/ACCESS.2020.2989614 ↗
24. Network topology optimization control algorithm for multiple unmanned surface vehicle
25. Distributed connectivity restoration in multichannel wireless sensor networks10.1016/j.comnet.2017.08.016 ↗
26. Pliatsios, D. (2024, January 17–19). Comparison of Swarm Intelligence Methods for Joint Resource Orchestration in Open Radio Access Network. Proceedings of the 14th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP), Rome, Italy.10.1109/CSNDSP60683.2024.10636586 ↗
27. Volovoda, T. (2024, January 22–24). Swarm Intelligence for UAV. Proceedings of the 7th International Conference on Actual Problems of Unmanned Aerial Vehicles Development (APUAVD), Kyiv, Ukraine.10.1109/APUAVD64488.2024.10765878 ↗
28. Bondy, J.A., and Murty, U.S.R. (2008). Graph Theory, Springer.10.1007/978-1-84628-970-5 ↗
29. A historic Review of Grey Forecasting Models
30. A comprehensive survey: Whale Optimization Algorithm and its applications10.1016/j.swevo.2019.03.004 ↗