AR need for the edge computing

I have come across an interesting example of AR developer's experience in the context of edge computing. Please see following publication of Seong-Jik Kim from KBS. https://www.linkedin.com/feed/update/urn:li:activity:6555928782660825088/ On the one hand Kim has shown how capable new phones can be, on

ConnectX 2019

The Open Edge Computing Initiative was present at this year's ConnectX Expo in Orlando, FL. Initiative members Carnegie Mellon University and Crown Castle partnered with MobiledgeX to form part of the 5G Connected Community space. The video below highlights the space sponsored by Crown Castle. To the left was the

Towards a Distraction-free Waze

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

EdgeDroid: An Experimental Approach to Benchmarking Human-in-the-Loop Applications

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

The Computing Landscape of the 21st Century

This paper shows how today's complex computing landscape can be  understood in simple terms through a 4-tier model. Each tier represents a  distinct and stable set of design constraints that dominate attention  at that tier. There are typically many alternative implementations of  hardware and software at each tier, but all

How we created edge computing

Edge computing processes data on infrastructure that is located close to the point of data creation. Mahadev Satyanarayanan recounts how recognition of the potential limitations of centralized, cloud-based processing led to this new approach to computing. Satyanarayanan, M. Nature Electronics, 2(1), January 2019