Participants from XMUM School of Computing and Data Science Win Best Presentation Award at ICECC 2023

2023-03-28

The School of Computing and Data Science congratulates Dr. Burra Venkata Durga Kumar and Ong Yi Jun, both from Software Engineering programme, for receiving the best presentation award at the 6th International Conference on Electronics, Communications and Control Engineering (ICECC 2023).

Launched in 2018, ICECC is an annual conference aiming to publish the latest & high-quality research works on Electronics, Communications and Control Engineering in theoretical and practical aspects. This year, the conference was held at Fukuoka Institute of Technology, Japan during March 24-26, 2023.

 

The current emerging fifth-generation (5G) system has a significant impact on the usage of Internet of Things (IoT) devices. Load balancing plays an important role in the distributed system, as it is directly associated with the performance of the whole system. Entitled Distributed Internet of Things Load Balancing using Deep Reinforcement Learning, the paper put forward a load-balancing method for distributed IoT systems based on deep reinforcement learning (DRL), which is capable of dealing with dynamic and large-scale network situations.

Specifically, the author recommended implementing a two-layer load-balancing architecture. The top layer uses the long short-term memory (LSTM) based Dueling Double Deep Q-Learning Network (D3QN) model for clustering the IoT devices. The bottom layer uses the plain DRL with more than one behaviour policy on joint exploration.

The key objective of this paper is to improve load balancing by using the technique mentioned above, as the data source and the infrastructure of the distributed IoT system can be dynamic. Experiments were conducted by using real-world datasets for evaluating the implementation. The outcome showed that compared to other simplified DRL models and static clustering methods. the implementation of DRL on load balancing has indeed achieved a significant improvement in the performance of the distributed IoT system.

The award-winning paper will be published in the International Conference Proceedings Series by ACM (ISBN: 979-8-4007-0000-2), which will be archived in the ACM Digital Library, and indexed by Ei Compendex, Scopus.

News & Events

A Glance at XMUM