Novel Deep Learning Approach to Support Optimal Resource Allocation in 5G Environment

Authors

  • Raja Varma Pamba LBS Institute of Technology for Women, Poojapura, Trivandrum, India
  • Rahul Bhandari Department of Computer Science and Engineering, Chandigarh University, Mohali, Punjab, India
  • A. Asha Rajalakshmi Engineering College, Rajalakshmi Nagar, Thandalam, Chennai, India
  • Rahul Neware Department of Computing, Mathematics and Physics, Høgskulen på Vestlandet, Bergen, Norway
  • Ankur Singh Bist Graphic Era Hill University Bhimtal Campus, Uttarakhand, India

DOI:

https://doi.org/10.13052/jmm1550-4646.1935

Keywords:

Resource Allocation, 5G Networks, QoS, web traffic, deep learning

Abstract

In recent times, the advancement in network devices has focused entirely on the miniaturisation of services that should ensure better connectivity between them via fifth generation (5G) technology. The 5G network communication aims to improve Quality of Service (QoS). However, the allocation of resources is a core problem that increases the complexity of packet scheduling. In this paper, we develop a resource allocation model using a novel deep learning algorithm for optimal resource allocation. The novel deep learning is formulated using the constraints associated with optimal radio resource allocation. The objective function design aims at reducing the system delay. The study predicts the traffic in a complex environment and allocates resources accordingly. The simulation was conducted to test the scheduling efficacy and the results showed an improved rate of allocation than the other methods.

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Author Biographies

Raja Varma Pamba, LBS Institute of Technology for Women, Poojapura, Trivandrum, India

Raja Varma Pamba is an Assistant Professor working in LBS Institute of Technology for Women, Poojapura, Trivandrum, Kerala, India. She has over 13 years of experience in teaching and 3 years of industrial experience. She completed her B. Tech from Govt Rajiv Gandhi Institute of Technology, Kottayam and M. Tech from Visveswaraya National Institute of Technology, Nagpur, Maharashtra. She received her PhD in CSE from Mahatma Gandhi University, Kottayam, Kerala with a specialization in Machine Learning. She has over 10 paper publications to her credit and participated in many national and international conferences.

Rahul Bhandari, Department of Computer Science and Engineering, Chandigarh University, Mohali, Punjab, India

Rahul Bhandari is working as Associate Professor in Chandigarh University, Punjab, India. He has over 12 years of experience in teaching. He is completed their B.E. and M.Tech. from Jodhpur Institute of Engineering Technology, Jodhpur. He received Ph.D. degree from Career Point University, Kota. There are 9 papers published in international journal and actively participate in FDP as well as STTP.

A. Asha, Rajalakshmi Engineering College, Rajalakshmi Nagar, Thandalam, Chennai, India

A. Asha is currently working as an Associate Professor in the Department of Electronics and Communication Engineering, Rajalakshmi Engineering College, Chennai. She received her B. E. degree from M.S. University in 2000 and Master’s Degree in Communication Systems from SASTRA University in 2002 and PhD in Information and communication engineering from Anna University Chennai, in 2019. She has a teaching experience of 18 years and her research interests are Wireless Sensor Networks, Cloud computing and Internet of Things.

Rahul Neware, Department of Computing, Mathematics and Physics, Høgskulen på Vestlandet, Bergen, Norway

Rahul Neware received the B.E. degree in Information Technology from the RTM Nagpur University India in 2015 and the MTech. in Computer Science and Engineering from G. H. Raisoni College of Engineering Nagpur India, in 2018. He is currently pursuing a Ph.D. degree in Computing from Western Norway University of Applied Sciences, Bergen campus, Norway. His area of interest includes Cybersecurity, Cloud and Fog Computing, Advanced Image Processing, Remote Sensing. He is a member of various professional bodies like IEEE, ASR, CSI, IAENG, and Internet Society.

Ankur Singh Bist, Graphic Era Hill University Bhimtal Campus, Uttarakhand, India

Ankur Singh Bist is currently working as Associate Professor at Graphic Era Hill University Bhimtal, India. His area of research is computer virology and Machine Learning. He has written more than 100 research papers. He has worked as reviewer/editor in more than 350 conferences/journals. He is active member of various research societies and educational group which covers more than 50 countries of world. He has received 5 international awards and medals of honors by renowned societies.

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Published

2023-02-15

How to Cite

Pamba, R. V. ., Bhandari, R. ., Asha, A. ., Neware, R. ., & Bist, A. S. . (2023). Novel Deep Learning Approach to Support Optimal Resource Allocation in 5G Environment. Journal of Mobile Multimedia, 19(03), 739–764. https://doi.org/10.13052/jmm1550-4646.1935

Issue

2023: Vol 19 Iss 3

Section

Articles