In this project, we intend to develop the innovative data-driven techniques for application context aware smart computing and communication strategies at the edge nodes for 5th generation Internet of Things (5G IoT) and beyond communications. The use cases are important from both indoor as well as outdoor perspective, though the operating conditions, available resources, and objectives could be significantly different. Usually the smart devices/robots/sensors used in such use cases are of heterogeneous types and in large scale. Mobile communication and energy agents (e.g., unmanned aerial vehicles (UAVs)) are also deployed to undertake certain important tasks such as sensing, controlling, recharging, managing, remote diagnosing, etc.
To perform the desired tasks by the appropriate smart device and/or mobile agents and at the right time requires coordination among the devices/ mobile agents and the central control system. For this, data collected by sensors and mobile agents are to be communicated either to a central system or to set of distributed agents or nodes depending upon the use case and the architecture. Primary objective of this project is to study context-aware, sustainable communication and networking issues in deployment of smart sensors and mobile agents and to provide optimal solutions in terms of algorithms, protocols, and deployable proof-of-concepts on application aware network platform.
Some of the-problem areas in the project are:
In the project scope primary focus would be given to learning and processing intelligence at the edge. Beyond data-specific features, effects of communication network constraints, e.g., congestion-induced delay and jitter, and wireless channel induced stochastic losses would be of interest in this project. Channel induced stochastic losses will be accounted as important factors from communication protocol and algorithm design and validation viewpoints. Context-specific network communication platforms will be developed, which can be adapted to satisfy various QoS requirements in 5G IoT use cases, namely remote connectivity, smart grid, and smart city. The two application domain specific broad classification of air-to-ground (AtG) communication studies would be: (i) urban/suburban, smart city type of sensing and automation applications, (ii) rural agricultural deployments for mechanized farming. For sustainable sensor node operation via on-demand wireless energy supply, RF energy transfer and our recently-proposed multihop RF energy routing technology will be refined by incorporating multi-antenna and beamforming technologies, which have not been explored before.
Deliverables:
Strong mathematical background, strong background in Signals and Systems and in Probability and Stochastic Processes.
Interest/capability of working on hardware systems (implementation/experimentation using SDR/USRP kits and embedded hardware systems) will be advantageous.
The students are expected to have degrees in Electrical Communication/Computer Engineering or allied areas such as Applied Mathematics.
Electrical Communication Engineering, Computer Engineering/Technology, Applied Mathematics, Signal Processing.