Enhancing CNN Weights for Improved Routing in UAV Networks for Catastrophe Relief with MSBO Algorithm

Authors

  • Sachin Kumar Gupta Department of Electronics and Communication Engineering, Central University of Jammu, Samba-181143, Jammu, (UT of J&K), India
  • Suhail Mohi Ul Din Department of Electronics and Communication Engineering, Indian Institute of Technology, Bhilai, Chhattisgarh – 491002, India
  • Kamal Upreti Department of Computer Science, Christ University, Delhi NCR-201003, India
  • Shubham Mahajan Amity School of Engineering and Technology (ASET), Amity University, Gurugram, Panchgaon, Haryana-122412, India
  • Saroj S. Date Department of Artificial Intelligence and Data Science, CSMSS Chh. Shahu College of Engineering, Chh. Sambhajinagar, Maharashtra, India

DOI:

https://doi.org/10.13052/jmm1550-4646.2056

Keywords:

Modified smell bees optimization (MSBO), routing protocols, optimization algorithms, UAV networks, CNN, catastrophe relief

Abstract

UAVs have become key in various applications lately, from catastrophe relief to environmental monitoring. The plan of powerful and reliable directing protocols in UAV networks is seriously hampered by the dynamic and habitually eccentric mobility patterns of UAVs. This study proposes a novel technique to beat these challenges by utilizing the Modified Smell Bees Optimization (MSBO) algorithm to upgrade the weights of CNNs. This study’s principal objective is to further develop UAV network routing decisions by using CNNs’ ability for design recognition and the Modified SBO’s optimization abilities. Our methodology comprises of randomly relegating CNN weights to a populace of bees at start, evaluating their wellness by fitness of directing performance, and iteratively fine-tuning these weights utilizing local and global search procedures got from bee searching. Broad simulations and performance evaluations show that our recommended approach incredibly expands the general dependability of UAV’s, brings down communication latency, and improves directing productivity. Future exploration in UAV network improvement gives off an impression of being going in a promising direction with the integration of CNNs for pattern recognition and the Modified SBO for weight enhancement. In addition to progressing UAV routing conventions, this work sets out new open doors for machine learning applications of bio-inspired optimization algorithms.

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Author Biographies

Sachin Kumar Gupta, Department of Electronics and Communication Engineering, Central University of Jammu, Samba-181143, Jammu, (UT of J&K), India

Sachin Kumar Gupta is currently working as an Associate Professor in the Department of Electronics and Communication Engineering (under the mentorship of IIST–ISRO), Central University of Jammu, Jammu (UT of J&K), India since 8th September 2023, He has received his B. Tech in Electronics and Telecommunication Engineering from NIT Raipur, India in 2008 and M. Tech & Ph.D. with Specialization in Systems Engineering from IIT (BHU), Varanasi, India in 2011 & 2016, respectively. He was a former research fellow in the Mobile Computing and Broadband Networking Lab, Department of Computer Science, NCTU, Taiwan. He has also served as Assistant Professor in the SoECE, SMVDU, Katra, (J&K), India from 1st January 2015 to 7th September 2023. He has published 120+ research articles in reputed international/national journals and prestigious conference proceedings, and an author of many book chapters as well. He has also edited a number of books in prestigious publication houses. He has organized several FDP, STC, workshops, conferences, etc. as coordinator and organizing secretary. He is an associate editor and reviewer in various reputed journals and conferences. He is member of IEEE, and life member of IETE, ISTE, CSI, ISOC, etc.

Suhail Mohi Ul Din, Department of Electronics and Communication Engineering, Indian Institute of Technology, Bhilai, Chhattisgarh – 491002, India

Suhail Mohi Ul Din currently serves as a Project Associate at the Indian Institute of Technology (IIT) Bhilai, contributing to a COMET Foundation-funded project titled “Smart Radio Environments, Implementation and Deployment for Targeted Use-Cases.” Previously, he worked as a Junior Research Fellow at the National Institute of Technology (NIT) Jalandhar, where he played a key role in capacity-building projects for Unmanned Aircraft Systems (UAS), funded by MeitY.

Suhail Mohi Ul Din holds a Master of Technology (M.Tech) in Electronics and Communication Engineering from Shri Mata Vaishno Devi University, a Master of Arts (M.A.) in Public Administration from IGNOU, and a Bachelor of Technology (B.Tech) in Electronics and Communication Engineering from the Islamic University of Science and Technology Awantipora.

He has extensive experience in UAV technology, wireless sensor networks, and ad-hoc networks, and has organized and coordinated numerous workshops and bootcamps on drone technologies across India. His research focuses on collaborative multi-UAV systems, energy transmission in wireless sensor networks, and advanced communication systems. With several peer-reviewed publications and conference presentations, Suhail Mohi Ul Din demonstrates a deep commitment to advancing sustainable and innovative solutions in communication and automation. He is proficient in MATLAB, Python, C++, and other engineering tools.

Kamal Upreti, Department of Computer Science, Christ University, Delhi NCR-201003, India

Kamal Upreti is currently working as an Associate Professor in Department of Computer Science, CHRIST (Deemed to be University), Delhi NCR, Ghaziabad, India. He completed is B. Tech (Hons) Degree from UPTU, M. Tech (Gold Medalist), PGDM(Executive) from IMT Ghaziabad and PhD in Department of Computer Science & Engineering. He has completed Postdoc from National Taipei University of Business, TAIWAN funded by MHRD.

He has published 87+ Patents, 32+ Magazine issues and 111+ Research papers in in various reputed Journals and international Conferences. His areas of Interest such as Modern Physics, Data Analytics, Cyber Security, Machine Learning, Health Care, Embedded System and Cloud Computing. He has published more than 45+ authored and edited books under CRC Press, IGI Global, Oxford Press and Arihant Publication. He is having enriched years’ experience in corporate and teaching experience in Engineering Colleges.

He worked with HCL, NECHCL, Hindustan Times, Dehradun Institute of Technology and Delhi Institute of Advanced Studies, with more than 15+ years of enrich experience in research, Academics and Corporate. He also worked in NECHCL in Japan having project – “Hydrastore” funded by joint collaboration between HCL and NECHCL Company. He has completed project work with Joint collaboration with GB PANT & AIIMS Delhi, under funded project of ICMR Scheme on Cardiovascular diseases prediction strokes using Machine Learning Techniques from year 2017–2020 of having fund of 80 Lakhs. He got 3 Lakhs fund from DST SERB for conducting International Conference, ICSCPS-2024, 13–14 Sept 2024. Recently, he got 10 Lakhs fund from AICTE – Inter-Institutional Biomedical Innovations and Entrepreneurship Program (AICTE-IBIP) for 2024–2026. He has attended as a Session Chair Person in National, International conference and key note speaker in various platforms such as Skill based training, Corporate Trainer, Guest faculty and faculty development Programme. He awarded as best teacher, best researcher, extra academic performer and Gold Medalist in M. Tech programme.

Shubham Mahajan, Amity School of Engineering and Technology (ASET), Amity University, Gurugram, Panchgaon, Haryana-122412, India

Shubham Mahajan, a distinguished member of prestigious organizations such as IEEE, ACM, and IAENG, boasts an impressive academic and professional background. He earned his B.Tech. degree from Baba Ghulam Shah Badshah University, his M.Tech. degree from Chandigarh University, his Ph.D. degree from Shri Mata Vaishno Devi University (SMVDU) in Katra, India. Currently, he serves as an Assistant Professor at Amity University, Haryana.

Dr. Mahajan has a remarkable track record in the field of artificial intelligence and image processing, holding an impressive portfolio of seventeen Indian patents, as well as one Australian and one German patent. His contributions to the field are further evidenced by his extensive publication record, which includes over 84 articles published in peer-reviewed journals and conferences and 8 edited books. His research interests span a wide array of topics, encompassing image processing, video compression, image segmentation, fuzzy entropy, nature-inspired computing methods, optimization, data mining, machine learning, robotics, and optical communication. Notably, his dedication and expertise have earned him the ‘Best Research Paper Award’ from ICRIC 2019, published by Springer in the LNEE series.

Saroj S. Date, Department of Artificial Intelligence and Data Science, CSMSS Chh. Shahu College of Engineering, Chh. Sambhajinagar, Maharashtra, India

Saroj S. Date is an accomplished academician and researcher with over 18+ years of teaching experience in Computer Science & Engineering. Currently she is working as an Associate Professor in the Department of Artificial Intelligence and Data Science at CSMSS Chh. Shahu College of Engineering, Chh. Sambhajinagar. She has an extensive background in Computer Engineering, holding a Ph.D. from Dr. Babasaheb Ambedkar Marathwada University, Chh. Sambhajinagar. She pursued Bachelor of Engg. from SGGS College of Engg. & Tech, Swami Ramanand Teerth Marathwada University, Nanded and Master of Engg. from Dr. Babasaheb Ambedkar Marathwada University, Chh. Sambhajinagar.

Her expertise spans diverse subjects, including Machine Learning, Theory of Computation, Compiler Design, and Big Data Analytics. Dr. Date is proficient in programming languages such as Python, Java, C++. She has contributed significantly to research with publications on sentiment analysis, natural language processing, and machine learning, including Scopus-indexed journal articles, International journals/conferences and book chapters.

Her main research work focuses on Sentiment Analysis, Natural Language Processing, Data Mining, Text Mining, Artificial Intelligence, Mobile Computing, Big Data Analytics, etc.

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Published

2024-12-20

How to Cite

Gupta, S. K. ., Din, S. M. U. ., Upreti, K. ., Mahajan, S. ., & Date, S. S. . (2024). Enhancing CNN Weights for Improved Routing in UAV Networks for Catastrophe Relief with MSBO Algorithm. Journal of Mobile Multimedia, 20(05), 1117–1152. https://doi.org/10.13052/jmm1550-4646.2056

Issue

2024: Vol 20 Iss 5

Section

Articles

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