Welcome to Network Research Lab

The Network Research Lab (NRL) at IIIT-Delhi works at the intersection of computer networks, Internet of Things (IoT) and machine learning. The lab is managed by two full-time faculty Mukulika Maity and Arani Bhattacharya at IIIT-Delhi. The recent work of the lab’s members has led to collaborations with renowned labs both in India and abroad, as well as publications in reputed conferences and journals.

Recently, the major focus of the lab has been on satisfying the ever-increasing demand for data from users and on enabling more complex IoT applications. The research work involves both using machine learning and algorithmic techniques to design better network protocols and applications. Major directions of research pursued by the lab members include:

• Optimization of WiFi 6 Protocols: With increasing new protocols such as 802.11ax and 802.11be being introduced, there is a need for much better utilization of the channels reserved for these protocols. NRL’s work in this domain includes designing more intelligent algorithms to schedule transmissions and allocate resources. Some of these works have been published in venues like IEEE COMSNETS 2019, IEEE PIMRC 2020 and IEEE MASS 2020.
• Edge Computing: With low-latency applications becoming increasingly relevant, it has become essential to understand how compute resources can be brought closer to the user. However, a number of questions related to handling of mobility, handling of congestion and satisfying the reliability constraints remain unsolved. NRL’s work in this domain has led to collaborations with numerous universities in India, and one publication at ICSOC 2020 so far.
• Resource-efficient Monitoring of RF Spectrum: With the rising demand of data, there has been an increase in the value of radio-frequency spectrum. However, this can lead to its misuse by unauthorized users. NRL’s work has focused on identifying such unauthorized users by crowdsourcing in a resource-efficient way. The key technique involves numerous machine learning algorithm to utilize such crowdsourced data. Some of these works have been published in venues like IEEE Infocom 2020 and IEEE Transactions on Cognitive Communications 2020.