Channel Encoder Caching Decoder Channel Decoder Encoding Decoding

The emerging technology of Internet of Things (IoT) has raised fundamental challenges in the design of practical and high performance data transmission and storage systems. Current network architectures and communication schemes are incapable of supporting the massive data, high rate, low latency, and large number of users that are envisioned in the applications of IoT. I am interested in novel cloud-based and cache-aided network architectures, and the opportunities they can provide to fundamentally boost the performance of communication networks. In particular, I seek to answer questions such as: How much coordination is needed in a network to support a desired rate and how to establish this coordination among the network nodes? How to utilize local storage units at network nodes to improve rate and latency? What is the tradeoff between communication and computation in distributed systems? How to compress data using minimum storage cost such that the important features of the data are preserved in the compressed domain? To approach these questions, I use tools from information theory, network theory, optimization, and algorithms to develop coding strategies that are efficient with respect to rate, energy, memory, complexity, latency, and cost. In the long term, I aim to develop a mathematical understanding of information extraction, storage and communication for data analysis, where the challenge is to learn certain information, rather than to reconstruct the entire data exactly. In the following, I present some of my past research contributions and future research directions.