Publications

Wearable cognitive assistants (WCA) are anticipated to become a widely-used application class, in conjunction with emerging network infrastructures like 5G that incorporate edge computing capabilities. While prototypical studies of such applications exist today, the relationship between infrastructure service provisioning and its implication for WCA usability is largely unexplored despite the

This position paper examines a spectrum of approaches to overcoming the limited computing power of mobile devices caused by their need to be small, lightweight and energy efficient. At one extreme is offloading of compute-intensive operations to a cloudlet nearby. At the other extreme is the use of fixed-function hardware

The emergence of edge computing introduces new complexity in the creation of distributed mobile applications. Application designers can now deploy application functionality in three or more tiers of compute infrastructure to optimize bandwidth, latency, cost, user experience and privacy for their users and their own operations. However, the diversity of

The growth of edge computing depends on large-scale deployments of edge infrastructure. Benchmarking applications are needed to compare the performance across different edge deployments and against device-only and cloud-only implementations.

Edge computing was motivated by the vision of new edge-native applications that are compute-intensive, bandwidth-hungry, and latency-sensitive.

Latency-sensitive edge-native applications may be the key to commercial success of edge infrastructure. However, success in the form of widespread deployment of such applications poses its own challenges.

We introduce the concept of "edge-native applications" that fully exploit the potential of edge computing and have a deeply symbiotic relationship with it.

This paper investigates the use of drones for live inspection in the  construction industry. The key technical challenge is the real-time  registration of the drone video feed to the architectural plan. We  present and evaluate three different approaches for registration and  propose an edge-based prototype using visual features. Our evaluations

Real-time traffic monitoring has had widespread success via  crowd-sourced GPS data. While drivers benefit from this low-level,  low-latency road information, any high-level traffic data such as road  closures and accidents currently have very high latency as such systems  rely solely on human reporting. Increasing the detail and decreasing the  latency

Many emerging mobile applications, including augmented reality (AR) and  wearable cognitive assistance (WCA), aim to provide seamless user  interaction. However, the complexity of benchmarking these  human-in-the-loop applications limits reproducibility and makes  performance evaluation difficult. In this paper, we present EdgeDroid, a  benchmarking suite designed to reproducibly evaluate these  applications. Our