Machine Learning, Wireless Communications

About the Project

This proposed work will target an improved multicasting approach that can adapt to changes in the topology of the M2M mesh network and on links to speed up the transmission of security information. The first step will be to develop multicasting optimization techniques (channel selection, route selection, and transmission scheduling). In the second step, we will leverage ML approaches to find a mapping between the context (link properties, route properties, and node positions/distances) and the achievable performance. Simulations and experiments have to be done as part of validation.

Department & Campus

Department of Computer Science Engineering (Cybersecurity) ,Chennai

Any Specific Skillsets Required by Applicants

Prior experience with Networks and their layers will be an added advantage. Full-time scholars preferred.