In modern networks, implementations of services and protocols for resource discovery, equipment configuration and network management are complex and error-prone. Implementation bugs in network protocols are hard to detect because they are often triggered by complex sequences of events that occur only after deployment and prolonged operation.

SymNV explores how future networks can exploit runtime verification techniques. The goal is to develop an architecture for runtime verification in networks based on bounded model-checking and symbolic execution of network services.

Ukairo (うかいろ) 1. (noun) detour; diversion; alternative route, in Japanese

Mobile devices are becoming pervasive, yet a persistent gap in hardware capabilities still separates them from desktop machines. To bridge this gap, recent research has turned to cloud-assisted execution as a way of leveraging remote resources to enhance application performance. Code-offloading systems automatically partition applications across resource-constrained devices and more powerful remote nodes to improve execution. Existing approaches, however, only focus on compute resources, ignoring memory and network limitations in mobile environments.

This project is focused on networking in the datacentre.  It aims to optimse network traffic based upon knowledge about the applications creating that traffic. This allows sophisticated mechanisms to be implemented in the network, for example custom routing protocols, traffic filtering, streaming processing of data and key-value stores. We term this approach as “Network-as-a-Service”. By modifying the content of packets on-path, they can efficiently implement advanced, application-specific network services, such as in-network data aggregation and smart caching.

The ITA-DSM project investigates the design of data stream management systems (DSMSs) for real-time data intensive applications in non-traditional environments such as mobile ad-hoc and wireless sensor networks. In these environments, connectivity to backend cloud infrastructure can be intermittent, bandwidth-constrained or in the worst case unavailable. Instead of offloading DSM to a cloud backend, the project seeks to exploit the growing computational capabilities of modern mobile phones and IoT devices by performing DSM in-situ using the combined resources of multiple devices.