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Jim Blakley

The Quest for Lower Latency: Announcing the New Living Edge Lab Wireless Network

In edge computing, network latency is key. Edge-native applications often benefit from the lowest latency and the least latency variation possible. For many applications, network round trip latencies less than 50ms are necessary to provide acceptable user experience. Some applications requiring near real-time control or extremely fast response need even

The Waiting is the Hardest Part

Like so many of us, I recently needed to search online for a Covid 19 vaccine appointment. I found a site that did a particularly good job of identifying locations with open appointment slots near me and enthusiastically began a frantic cycle of refreshing, entering my information and requesting the

The Edge of Cloud

A discussion with Mahadev Satyanarayanan, the Carnegie Group University professor of computer scienceIn November 2020, the Deloitte Cloud Institute invited Mahadev Satyanarayanan, the Carnegie Group University Professor of Computer Science at Carnegie Mellon University, as the first Deloitte Cloud Institute Fellow.1 Dr. Satyanarayanan (Satya as he’s popularly known)

Impact of Delayed Response on Wearable Cognitive Assistance

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

Connecting the Dots at the Edges

Source: https://www.internetexchangemap.com/ In the 1980s, there were only a handful of places in the public internet where internet service providers could connect with the public internet to pass data between each other and with their users. These places, known as internet exchange points, were located at the

The Role of Edge Offload for Hardware-Accelerated Mobile Devices

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

Edge-Native App Design When You Can’t See Behind the Curtain

IMAGE CREDIT: Pavan Trikutam -- Unsplashed In the mid-1980s, Bell Labs conducted a human-factors study to understand how telephone users conceptualized the telephone network. Within the switching engineering division, we thought of the network as a complex collection of switching, transmission and operation systems interconnected by a web of copper

Carnegie Mellon Built a Plug-and-Play Private LTE Network

When Mahadev Satyanarayanan, group professor of computer science at Carnegie Mellon University and an expert in edge computing, needed a network to test his edge computing applications, he knew he wanted something that was low in latency, reliable and not susceptible to any performance degradation. Satyanarayanan turned to Amazon Web

Simulating Edge Computing Environments to Optimize Application Experience

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

Three Decades Of Vision For Edge

In this interview, Satya shares how he started thinking about distributed computing infrastructure for mobile devices back in 1993, how much of his vision has come true in the decades since, and his views on the future of cloud, edge, iot, and much more. https://overtheedgepodcast.com/podcasts/three-decades-of-vision-for-edge-with-mahadev-satya-satyanarayanan-of-carnegie-mellon-university/