FL-SDUAN: A Fuzzy Logic-Based Routing Scheme for Software-Defined Underwater Acoustic Networks
Source abstract
Abstract
In underwater acoustic networks, the accurate estimation of routing weights is NP-hard due to the time-varying environment. Fuzzy logic is a powerful tool for dealing with vague problems. Software-defined networking (SDN) is a promising technology that enables flexible management by decoupling the data plane from the control plane. Inspired by this, we proposed a fuzzy logic-based software-defined routing scheme for underwater acoustic networks (FL-SDUAN). Specifically, we designed a software-defined underwater acoustic network architecture. Based on fuzzy path optimization (FPO-MST) and fuzzy cut-set optimization (FCO-MST), two minimum spanning tree algorithms under different network scales were proposed. In addition, we compared the proposed algorithms to state-of-the-art methods regarding packet delivery rate, end-to-end latency, and throughput in different underwater acoustic network scenarios. Extensive experiments demonstrated that a trade-off between performance and complexity was achieved in our work.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Underwater Vehicles and Communication Systems · Energy Harvesting in Wireless Networks · Energy Efficient Wireless Sensor Networks
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Postdoctoral Research Base, Henan Institute of Science and Technology, Xinxiang 453003, China
School of Information Engineering, Henan University of Science and Technology, Luoyang 471023, China
Adam Smith Business School, University of Glasgow, Glasgow G12 8QQ, UK
Funding
National Natural Science Foundation of China · Key Scientific and Technological Project of Henan Province · Young Scholar Training Program of Higher Education in Henan Province · Key Scientific Research Projects of Colleges and Universities in Henan Province
References (44)
Show source-provided references
1. Reliable data collection techniques in underwater wireless sensor networks: A survey10.1109/COMST.2021.3134955 ↗
2. Advances in software-defined technologies for underwater acoustic sensor networks: A survey10.1155/2019/3470390 ↗
3. Design and implementation of SDN-based underwater acoustic sensor networks with multi-controllers10.1109/ACCESS.2018.2835477 ↗
4. SM-UAN: A software-defined underwater acoustic network of multi-controllers for inland waterway systems10.1109/ACCESS.2020.3038997 ↗
5. PCDE-Sync: A Time Synchronization Mechanism Based on Partial Clustering and the Doppler Effect for Underwater Acoustic Networks
6. SoftWater: Software-defined networking for next-generation underwater communication systems10.1016/j.adhoc.2016.02.016 ↗
7. Software-defined underwater acoustic networking platform and its applications10.1016/j.adhoc.2015.01.010 ↗
8. Ghannadrezaii, H., Bousquet, J., and Haque, I. (2019). Cross-Layer Design for Software-Defined Underwater Acoustic Networking, OCEANS.10.1109/OCEANSE.2019.8867186 ↗
9. An SDN-based framework for QoS routing in internet of underwater things10.1007/s11235-021-00812-y ↗
10. Luo, H., Liu, C., and Liang, Y. (2019, January 17). A SDN-based testbed for underwater sensor networks. Proceedings of the ACM Turing Celebration Conference, Chengdu, China.10.1145/3321408.3321410 ↗
11. Sreeraj, A., Vijayalakshmi, P., and Rajendran, V. (2022, January 7–9). A Deep Learning Enabled Software-Defined Radio based Routing Protocol for Underwater Acoustic Sensor Networks. Proceedings of the 2022 International Conference on Sustainable Computing and Data Communication Systems, Erode, India.10.1109/ICSCDS53736.2022.9760848 ↗
12. SDN-Enabled Energy-Aware Routing in Underwater Multi-Modal Communication Networks10.1109/TNET.2021.3056772 ↗
13. An SDN Architecture for AUV-Based Underwater Wireless Networks to Enable Cooperative Underwater Search10.1109/MWC.001.1900387 ↗
14. A software-defined clustering mechanism for underwater acoustic sensor networks10.1109/ACCESS.2019.2937832 ↗
15. Fast Node Clustering Based on an Improved Birch Algorithm for Data Collection Towards Software-Defined Underwater Acoustic Sensor Networks10.1109/JSEN.2021.3055948 ↗
16. A Scheme for Delay-Sensitive Spatiotemporal Routing in SDN-Enabled Underwater Acoustic Sensor Networks10.1109/TVT.2019.2931312 ↗
17. Ghafoor, H., and Koo, I. (2017). Cognitive routing in software-defined underwater acoustic networks. Appl. Sci., 7.10.3390/app7121312 ↗
18. Trusted node selection in clusters for underwater wireless acoustic sensor networks using fuzzy logic10.1016/j.phycom.2021.101388 ↗
19. Fuzzy and PSO Based Clustering Scheme in Underwater Acoustic Sensor Networks Using Energy and Distance Parameters10.1007/s11277-019-06483-y ↗
20. One-Leap Fuzzy Enabled Clustering Technique for Under Water Wireless Sensor Networks to Improve the Stability and Energy Exhaustion Rate of the Nodes10.1088/1742-6596/1172/1/012080 ↗
21. Energy efficient architecture for intra and inter cluster communication for underwater wireless sensor networks10.1007/s11277-016-3302-0 ↗
22. Goyal, N., Dave, M., and Verma, A.K. (2014, January 13–14). Fuzzy based clustering and aggregation technique for under water wireless sensor networks. Proceedings of the 2014 International Conference on Electronics and Communication Systems, Coimbatore, India.10.1109/ECS.2014.6892804 ↗
23. A dynamic hierarchical clustering data gathering algorithm based on multiple criteria decisions making for 3D underwater sensor networks10.1155/2020/8835103 ↗
24. Intelligent exhaustion rate and stability control on underwater WSN with fuzzy based clustering for efficient cost management strategies10.1007/s10257-019-00411-0 ↗
25. Bennouri, H., and Berqia, A. (2019, January 15–19). Energy performances of a routing protocol based on fuzzy logic approach in an underwater wireless sensor network. Proceedings of the 2019 International Conference on High Performance Computing and Simulation, Dublin, Ireland.10.1109/HPCS48598.2019.9188061 ↗
26. Li, N., Martinez, J.F., Ortega, V.H., and Santidrian, L.L. (2018, January 16–18). Cross-Layer Balanced Relay Node Selection Algorithm for Opportunistic Routing in Underwater Ad-Hoc Networks. Proceedings of the 2018 IEEE 32nd International Conference on Advanced Information Networking and Applications, Krakow, Poland.10.1109/AINA.2018.00087 ↗
27. Mulla, A., and Jadhav, V. (2018, January 14–15). Energy Efficient Routing Protocol for Underwater Acoustic Sensor Network. Proceedings of the 2018 Second International Conference on Intelligent Computing and Control Systems, Madurai, India.10.1109/ICCONS.2018.8662952 ↗
28. Fuzzy logic vector-based forwarding routing protocol for underwater acoustic sensor networks10.1002/ett.3252 ↗
29. Rahman, M., Lee, Y., and Koo, I. (2017, January 18–21). FLCOR: Fuzzy Logic-based cooperative opportunistic routing for underwater acoustic sensor networks. Proceedings of the 9th International Conference on Computer and Automation Engineering, Sydney, Australia.10.1145/3057039.3057074 ↗
30. EECOR: An Energy-Efficient Cooperative Opportunistic Routing Protocol for Underwater Acoustic Sensor Networks10.1109/ACCESS.2017.2730233 ↗
31. Grid based Fuzzy Optimized Routing Protocol for Underwater sensor networks
32. Pressure Sensor Based Reliable (PSBR) Routing Protocol for Underwater Acoustic Sensor Networks
33. Huang, C., Wang, Y., Shen, H., Hu, K., Hsu, P., and Chang, T. (2009, January 19–22). A direction-sensitive routing protocol for underwater wireless sensor networks. Proceedings of the International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, Berlin, Germany.10.1007/978-3-642-02568-6_43 ↗
34. Pabani, J.K., Luque-Nieto, M.N., Hyder, W., and Otero, P. (2021). Energy-efficient packet forwarding scheme based on fuzzy decision-making in underwater sensor networks. Sensors, 21.10.3390/s21134368 ↗
35. A Fuzzy Based Energy Efficient Clustering Routing Protocol in Underwater sensor networks
36. Survey on network virtualization using OpenFlow: Taxonomy, opportunities, and open issues
37. Kurniawan, M.T., Fathinuddin, M., Widiyanti, H.A., and Simanjuntak, G.R. (2021, January 29–30). Network Slicing on SDN using FlowVisor and POX Controller to Traffic Isolation Enforcement. Proceedings of the 2021 International Conference on Engineering and Emerging Technologies, Istanbul, Turkey.10.1109/ICEET53442.2021.9659765 ↗
38. On Fuzzy Solutions of the Nonsquare Fully Fuzzy Linear Equation System with Arbitrary Triangular Fuzzy Numbers10.3233/JIFS-17774 ↗
39. A Fuzzy Rule-Based Penalty Function Approach for Constrained Evolutionary Optimization10.1109/TCYB.2014.2359985 ↗
40. Jyotsna, W.C., and Sarate, G.G. (2015, January 28–30). Channel estimation model for underwater Acoustic Sensor Network. Proceedings of the International Conference on Industrial Instrumentation and Control, Pune, India.
41. Shallow Water Acoustic Channel Modeling Based on Analytical Second Order Statistics for Moving Transmitter/Receiver10.1109/TSP.2015.2411219 ↗
42. Palan, N.G., Barbadekar, B.V., and Patil, S. (2017, January 30–31). Low Energy Adaptive Clustering Hierarchy (LEACH) Protocol: A Retrospective Analysis. Proceedings of the International Conference on Inventive Systems and Control, Coimbatore, India.10.1109/ICISC.2017.8068715 ↗
43. Das, D., and Ameer, P.M. (2017, January 5–8). Energy efficient geographic clustered multi-hop routing for underwater sensor networks. Proceedings of the TENCON 2017—2017 IEEE Region 10 Conference, Penang, Malaysia.10.1109/TENCON.2017.8227899 ↗
44. Ejaz, M., Javaid, N., Maqsood, H., Shakeel, U., Khan, Z.A., and Qasim, U. (2016, January 23–25). An Energy Efficient Hybrid Clustering Routing Protocol for Underwater WSNs. Proceedings of the 2016 30th International Conference on Advanced Information Networking and Applications Workshops, Crans-Montana, Switzerland.10.1109/WAINA.2016.157 ↗