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Roch Guérin

Publications and source records attributed to Roch Guérin.

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Report on the NSF Workshop on Sustainable Computing for Sustainability (NSF WSCS 2024)

This report documents the process that led to the NSF Workshop on "Sustainable Computing for Sustainability" held in April 2024 at NSF in Alexandria, VA, and reports on its findings. The workshop's primary goals were to (i) advance the development of research initiatives along the themes of both sustainable computing and computing for sustainability, while also (ii) helping develop and sustain the interdisciplinary teams those initiatives would need. The workshop's findings are in the form of recommendations grouped in three categories: General recommendations that cut across both themes of sustainable computing and computing for sustainability, and recommendations that are specific to sustainable computing and computing for sustainability, respectively.

cs.CY

Real-Time Edge Classification: Optimal Offloading under Token Bucket Constraints

To deploy machine learning-based algorithms for real-time applications with strict latency constraints, we consider an edge-computing setting where a subset of inputs are offloaded to the edge for processing by an accurate but resource-intensive model, and the rest are processed only by a less-accurate model on the device itself. Both models have computational costs that match available compute resources, and process inputs with low-latency. But offloading incurs network delays, and to manage these delays to meet application deadlines, we use a token bucket to constrain the average rate and burst length of transmissions from the device. We introduce a Markov Decision Process-based framework to make offload decisions under these constraints, based on the local model's confidence and the token bucket state, with the goal of minimizing a specified error measure for the application. Beyond isolated decisions for individual devices, we also propose approaches to allow multiple devices connected to the same access switch to share their bursting allocation. We evaluate and analyze the policies derived using our framework on the standard ImageNet image classification benchmark.

cs.LG

Adoption of bundled services with network externalities and correlated affinities

The goal of this paper is to develop a principled understanding of when it is beneficial to bundle technologies or services whose value is heavily dependent on the size of their user base, i.e., exhibits positive exernalities. Of interest is how the joint distribution, and in particular the correlation, of the values users assign to components of a bundle affect its odds of success. The results offer insight and guidelines for deciding when bundling new Internet technologies or services can help improve their overall adoption. In particular, successful outcomes appear to require a minimum level of value correlation.

cs.NI