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Edge Computing @ CMU Living Edge Lab
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Edge Computing @ CMU Living Edge Lab
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Articles and Blogs from the Living Edge Lab
Tuesday, October 25, 2022
Hiding the Devilishness of Detail
As edge computing emerges, it introduces new complexity. Now, a user’s proximity to edge computing resources matter. And, edge computing economics and market structure mean that the edge computing provider and the resources it provides can be quite variable over time and space. For the edge-native application provider, finding the “right” edge computing node or cloudlet to serve a specific user for a specific session can be non-trivial. Here at the Living Edge Lab, we believe that this complexity calls for a new abstraction at the boundary between edge-native application providers and edge computing infrastructure providers. Our Sinfonia project, led by Jan Harkes in collaboration with Meta and ARM, focuses on the development and evaluation of a framework for this abstraction.
Friday, June 10, 2022
Nudging the Planets to Align
At the Living Edge Lab, we’d like to have the benefits of both remote working and serendipity and believe that technology could enable this. Our recent concept paper, Balancing Privacy and Serendipity in Cyberspace, with Nigel Davies of Lancaster University and Nina Taft of Google, from this year’s HotMobile Conference explores technology approaches to bringing serendipitous chance encounters to the virtual workplace. Our question: “Can we create technology-mediated serendipity for coworkers who are not collocated?” The specific use case we examine is generating chance encounters between coworkers who are at different physical workplaces other than at-home
Wednesday, May 25, 2022
Opening Edge Computing’s Black Box
We want a mobile network with round-trip latencies less than 20ms. The lower we can get, the more edge-native applications become feasible. In our first step toward continual improvement in round-trip latency, we launched the Network Latency Segmentation Project led by students Sophie Smith and Ishan Darwhekar. They implemented network measurement probes at various points in the network – at the user equipment (UE), between the Radio Access Network (RAN) and the Evolved Packet Core (EPC) and the between the EPC and the Cloudlet to measure the latency of the network at each segment.
Wednesday, April 27, 2022
Accelerator Calculus at the Edge
This work investigates the use of an image decoding accelerator embedded in an edge storage system used for image analytics. Edge cameras can generate massive amounts of visual data that can’t be economically stored in an uncompressed form at the edge or fully transmitted to a backend cloud. However, city-scale video analytics requires application access to decoded data from large datasets of encoded, compressed stored images or videos at the edge.
Monday, April 18, 2022
Throwing a Softball at Search and Rescue
PhD student Haithem Turki of the Carnegie Mellon University Living Edge Lab has taken the search and rescue scenario as the motivation for his research work on Neural Radiance Fields or “NeRFs”, first developed at UC Berkeley in 2020. NeRFs are the newest technique for 3D scene capture and rendering. They use a type of neural network known as a multilayer perceptron (MLP) to represent the scene as a function. Once a NeRF has been trained from the input data, it embodies the 3D information contained in the scene. The rendering stage extracts the NeRF information and displays it to the user from a specific viewpoint.
Wednesday, July 21, 2021
The Quest for Lower Latency: Announcing the New Living Edge Lab Wireless Network
Tuesday, April 27, 2021
The Waiting is the Hardest Part
Wednesday, April 14, 2021
OpenScout
Tuesday, March 02, 2021
Connecting the Dots at the Edges
Tuesday, January 19, 2021
Edge-Native App Design When You Can’t See Behind the Curtain
Wednesday, September 23, 2020
Putting It All Together With Cognitive Assistance
Wednesday, August 26, 2020
When the Trainer Can’t Be There
Articles and Blogs