Low-Latency and private edge computing in random-access networks
We are living in a world where connected devices outnumber human population, and this trend keeps growing: around 24.6 billion connections are forecasted in 2025—more than three times the estimated population. This gives rise to the Internet of Things (IoT) in which virtually all devices are interconnected and continuously share data. The IoT is a key enabler for a host of applications, such as intelligent transportation systems, smart cities, and smart grids. Thus it promises to transform the way we live. To realize the IoT, it is crucial and timely to develop a communication and computation infrastructure that is able to support the processing of a vast amount of time-sensitive data, for which a centralized computation is inadequate. Edge computing has emerged as a novel paradigm to guarantee very low-latency and high-bandwidth computing services. It involves moving the computation power from the cloud to where data is generated, by pooling the available resources at the network edge.

In this project, we investigate how low-latency and private edge computing protocols can be developed in wireless random-access networks. Relying on tools from information theory and coding theory, we will tackle the two following challenging objectives: i) to establish a foundation for privacy and reliability in latency-critical, multi-client and multi-server edge computing in random-access networks; and ii) to devise resilient coding schemes together with energy-efficient and scalable wireless random-access protocols to achieve low latency and preserve privacy in distributed edge computing. The results of this project will help paving the way to the full realization of the IoT in the near future.