Lecture

Digital Sustainability: Challenges and Solutions

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Description

This lecture discusses the importance of digital sustainability in the context of information technology, focusing on multi-scale computing, edge computing, and the need for sustainability-driven IT growth. It also presents EPFL's efforts in developing energy-efficient cloud systems and innovative solutions for data center energy consumption.

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Related concepts (32)

Efficient energy use

Efficient energy use, sometimes simply called energy efficiency, is the process of reducing the amount of energy required to provide products and services. For example, insulating a building allows it to use less heating and cooling energy to achieve and maintain a thermal comfort. Installing light-emitting diode bulbs, fluorescent lighting, or natural skylight windows reduces the amount of energy required to attain the same level of illumination compared to using traditional incandescent light bulbs.

Edge computing

Edge computing is a distributed computing paradigm that brings computation and data storage closer to the sources of data. This is expected to improve response times and save bandwidth. Edge computing is an architecture rather than a specific technology, and a topology- and location-sensitive form of distributed computing. The origins of edge computing lie in content distributed networks that were created in the late 1990s to serve web and video content from edge servers that were deployed close to users.

Scale space

Scale-space theory is a framework for multi-scale signal representation developed by the computer vision, and signal processing communities with complementary motivations from physics and biological vision. It is a formal theory for handling image structures at different scales, by representing an image as a one-parameter family of smoothed images, the scale-space representation, parametrized by the size of the smoothing kernel used for suppressing fine-scale structures.

Edge detection

Edge detection includes a variety of mathematical methods that aim at identifying edges, curves in a at which the image brightness changes sharply or, more formally, has discontinuities. The same problem of finding discontinuities in one-dimensional signals is known as step detection and the problem of finding signal discontinuities over time is known as change detection. Edge detection is a fundamental tool in , machine vision and computer vision, particularly in the areas of feature detection and feature extraction.

Fog computing

Fog computing or fog networking, also known as fogging, is an architecture that uses edge devices to carry out a substantial amount of computation (edge computing), storage, and communication locally and routed over the Internet backbone. In 2011, the need to extend cloud computing with fog computing emerged, in order to cope with huge number of IoT devices and big data volumes for real-time low-latency applications. Fog computing, also called edge computing, is intended for distributed computing where numerous "peripheral" devices connect to a cloud.

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