Automatic Topology Generation in Wireless Networks using Artificial Intelligence

Authors

  • Shabir Ahmad Institute of Southern Punjab Multan
  • Shafiq Hussain University of Sahiwal, Sahiwal, Pakistan
  • Mahboob Alam Superior University Lahore, Lahore, Pakistan
  • Arslan Ali Mansab Qurashi Quaid e Azam University Islamabad, Pakistan
  • Tayyab Ali Raza Barani Institute of Sciences ARID University Rawalpindi, Pakistan
  • Muhammad Imtiaz Jamil Comsats University Islamabad

Keywords:

Wireless devices, Topology, Artificial intelligence, Algorithm, Portable mode

Abstract

The wireless devices are capable to govern transmission in portable mode. The development of effective networking techniques requires additional protocol stacks of network research, which is the heart of the network model. In this work, we reviewed our previously designed algorithm TEAM for the generation of topologies automatically using artificial intelligence for present and future wireless networks. We conclude this study with the future challenges of applying AI to Wireless 5G networks. Artificial intelligence algorithm is based on a design that best routing solution involves changes in the environment, it is very likely that it is simply spending some time will be in the study. The proposed algorithm is tested in MATLAB by varying the iteration and number of nodes in a network. Our algorithm is flexible so that its cost in the sense of topology generation reduces gradually as the number of nodes in the wireless environment will increase.

References

S. -Y. Wu, "Key Technology Enablers of Innovations in the AI and 5G Era," 2019 IEEE International Electron Devices Meeting (IEDM), 2019, pp. 36.3.1-36.3.4, doi: 10.1109/IEDM19573.2019.8993613.

Wang, Yong, Shouguo Peng, Xuesong Zhou, Monirehalsadat Mahmoudi, and Lu Zhen. "Green logistics location-routing problem with eco-packages." Transportation Research Part E: Logistics and Transportation Review 143 (2020): 102118.

Ahmad, Shabir, Rana Muhammad Nadeem, Bilal Ehsan, Mohib Ullah, and Abu Buker Siddique. "Wireless networks throughput enhancement using artificial intelligence." Indian Journal of Science and Technology 10, no. 26 (2017): 1-5.

Dhungana, Aashish, and Eyuphan Bulut. "Peer-to-peer energy sharing in mobile networks: Applications, challenges, and open problems." Ad Hoc Networks 97 (2020): 102029.

Sheraz, Muhammad, Manzoor Ahmed, Xueshi Hou, Yong Li, Depeng Jin, Zhu Han, and Tao Jiang. "Artificial intelligence for wireless caching: schemes, performance, and challenges." IEEE Communications Surveys & Tutorials 23, no. 1 (2020): 631-661.

Rkhami, Anouar, Yassine Hadjadj-Aoul, and Abdelkader Outtagarts. "Learn to improve: A novel deep reinforcement learning approach for beyond 5G network slicing." In 2021 IEEE 18th Annual Consumer Communications & Networking Conference (CCNC), pp. 1-6. IEEE, 2021.

Jiang, Wei, Mathias Strufe, and Hans D. Schotten. "Experimental results for artificial intelligence-based self-organized 5G networks." In 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), pp. 1-6. IEEE, 2017.

AHMAD, Shabir, Bilal EHSAN, and Mohib ULLAH. "Intelligence Base Routing in Wireless Networks Using Linux Router." Uluslararası Doğa ve Mühendislik Bilimleri Dergisi 11, no. 3: 7-18 IJNES, 2017.

Sert, Seyyit Alper, and Adnan Yazıcı. "Optimizing the performance of rule-based fuzzy routing algorithms in wireless sensor networks." In 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), pp. 1-6. IEEE, 2019.

Shabir Ahmad, Shafiq Hussain, Umar Draz, Zanab Safdar, Junaid, Quratulain, Haroon Mahmood “Novel algorithm for throughput enhancement in wireless networks using multichannels “, Vol. 20 No. 8 pp. 203-213. IJCSNS, 2020.

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Published

2023-07-10