All Projects

Background Most edge computing research assumes a fixed topology of static servers. In reality, cities are in constant motion. Buses, trams, and trains carry passengers — and the devices they depend on — through coverage gaps, congestion hotspots, and unpredictable handoff zones. This project introduces Mobile Edge (ME) servers installed on public transport vehicles as … Read more

Background Centralised placement controllers are simple to reason about but brittle in practice: a single point of failure, limited scalability, and high communication overhead as the network grows. Decentralised approaches — where each edge node makes its own decisions — are more resilient, but risk sub-optimal global outcomes when nodes act purely in self-interest. Multi-Agent … Read more

Background Training a reinforcement learning agent from scratch for each new edge environment is expensive — in time, data, and compute. Yet edge networks vary enormously: a placement policy tuned for a dense urban deployment may perform poorly in a suburban network with different server topologies, user mobility patterns, and service mixes. Transfer Reinforcement Learning … Read more

Integer division and remainder are relatively complicated, expensive operations. Most modern processors have at least one integer multiplier unit that has both low latency (typically between 3 and 5 cycles) and high throughput (typically the unit can complete a multiply operation every cycle). In contrast, most modern processors do not have a fast integer division … Read more

Almost all modern processors provide special-purpose instructions for integer multiplication. However, some applications require integer values that are larger than fit in a single machine word, such as 256 bit integers. We can multiply these big integer values using a sequence of smaller multiplies. For example, multiplying two 256-bit integer values might be completed with … Read more

In some applications, such as many cryptography algorithms, multiplication by a known integer constant is a common operation. It’s well known that integer multiplication with a constant can be computed with a sequence of shifts and adds. Most modern processors already have fast integer multiplication units, so in software it is usually faster to use … Read more

Matrix multiplication is one of the commonly-used computations across a wide range of applications. For example, most implementations of neural networks implement very large numbers of matrix multiplications. Almost all processor and GPU manufacturers provide libraries with carefully hand-tuned fast matrix multiplication routines. All the best-known algorithms matrix multiplication are out-of-place; that is, the result … Read more

Taken- This project involves exploring the role Provenance standards can play to address issues of data linkage in health research data. The project will specifically focus on health research for the disease of Multiple Sclerosis.