21 citations · 44 across the 8 of their papers we have counts for
8 papers
An Architecture for Spatial Networking
Josh Millar, Ryan Gibb, Roy Ang +2
Physical spaces are increasingly dense with networked devices, promising seamless coordination and ambient intelligence. Yet today, cloud-first architectures force all communicatio…
Steps towards an Ecology for the Internet
Anil Madhavapeddy, Sam Reynolds, Alec P. Christie +10
The Internet has grown from a humble set of protocols for end-to-end connectivity into a critical global system with no builtin "immune system". In the next decade the Internet wil…
Energy-Aware Deep Learning on Resource-Constrained Hardware
Josh Millar, Hamed Haddadi, Anil Madhavapeddy
The use of deep learning (DL) on Internet of Things (IoT) and mobile devices offers numerous advantages over cloud-based processing. However, such devices face substantial energy c…
Benchmarking Ultra-Low-Power NPUs
Josh Millar, Yushan Huang, Sarab Sethi +2
Efficient on-device neural network (NN) inference offers predictable latency, improved privacy and reliability, and lower operating costs for vendors than cloud-based inference. Th…
Terracorder: Sense Long and Prosper
Josh Millar, Sarab Sethi, Hamed Haddadi +1
In-situ sensing devices need to be deployed in remote environments for long periods of time; minimizing their power consumption is vital for maximising both their operational lifet…
Towards Low-Energy Adaptive Personalization for Resource-Constrained Devices
Yushan Huang, Josh Millar, Yuxuan Long +2
The personalization of machine learning (ML) models to address data drift is a significant challenge in the context of Internet of Things (IoT) applications. Presently, most approa…
Low-Energy On-Device Personalization for MCUs
Yushan Huang, Ranya Aloufi, Xavier Cadet +3
Microcontroller Units (MCUs) are ideal platforms for edge applications due to their low cost and energy consumption, and are widely used in various applications, including personal…
Effective Abnormal Activity Detection on Multivariate Time Series Healthcare Data
Mengjia Niu, Yuchen Zhao, Hamed Haddadi
Multivariate time series (MTS) data collected from multiple sensors provide the potential for accurate abnormal activity detection in smart healthcare scenarios. However, anomalies…