Display Energy Management based on Eye Tracking

With the explosive use of personal computers or PCs, reducing computer energy consumption is paramount for sustainability. The display is the largest energy consumer in a personal computer. Current display energy management technologies ignore the attention of the PC user and therefore may either switch the display off when the user looks at the screen or lose energy by keeping the display on when nobody looks at it. This chapter discusses a new display energy management technology and outlines its implementation in a personal computer system. Unlike existing technologies, which “sense” a PC user through keyboard and/or mouse or the other sensors, this technology “watches” the user through a single camera or CMOS vision sensor. The technology tracks the user’s eyes, keeping display active only if the user looks at its screen. Otherwise, it dims the display down or even switches it off to save energy. The authors implemented the technology in software and hardware and present the results of their experimental evaluation.

Mitigating the Environmental Impact of Smartphones with Device Reuse

The rapid growth of information technology has not only brought substantial economic and societal benefit but also led to an unsustainable disposable model in which mobile devices are replaced in a matter of months. The environmental impact of this stream of handsets in terms of manufacturing energy, materials, and disposal costs is alarming. This chapter aims at raising today’s environmental issues of the increasing smartphone market, as well as providing a quantitative analysis on the environmental impact of different life-cycle stages of the smartphones, including the manufacturing stage, using stage, and recycling. To achieve sustainable computing and best utilize the energy consumed during manufacturing the large number of devices, this chapter demonstrates the methodology and techniques towards reusing smartphones by presenting a case study on reusing smartphones for elementary school education.

Reducing Design Margins by Adaptive Compensation for Thermal and Aging Variations

Corner-based design and verification are based on worst-case analysis, thus introducing over-pessimism and large area and power overhead and leading to unnecessary energy consumption. Typical case-based design and verification maximize energy efficiency through design margins reduction and adaptive computation, thus helping achieve sustainable computing. Dynamically adapting to manufacturing, environmental, and usage variations is the key to shaving unnecessary design margins, which requires on-chip modules that can sense and configure design parameters both globally and locally to maximize computation efficiency, and maintain this efficiency over the lifetime of the system. This chapter presents an adaptive threshold compensation scheme using a transimpedance amplifier and adaptive body biasing to overcome the effects of temperature variation, reliability degradation, and process variation. The effectiveness and versatility of the scheme are demonstrated with two example applications, one as a temperature aware design to maintain IONto IOFFcurrent ratio, the other as a reliability sensor for NBTI (Negative Bias Temperature Instability).

Green IT Project Management

With the constant evolution of technology and the world critical environmental status, all private and public Information Technology (IT) businesses are moving towards sustainability. Faced with influences from government regulations, market competition and constraints, as well as watchdogs, IT decision makers within organizations are forced to ride the green technology wave with a challenging and uncertain approach. This chapter defines methods to optimize Green IT projects for sustainable value creation within organizations. It only focuses on economic viability and environmental impact, but could be stretched out in the future to social aspects. The contributions of this chapter allow the project management community and decision makers to follow a framework for Green IT project success evaluation and performance follow-up throughout the project life cycle and the three levels of the organization: operational, tactical, and strategic. A macro-model is also developed to aid them in successfully selecting, prioritizing, managing, and aligning their Green IT projects with the corporate and environmental strategies.

Green Computing as an Ecological Aid in Industry

This chapter concerns the use of computing for ecological evaluation in the manufacturing industry. Here, ecological evaluation means identification and quantisation of various manufacturing process characteristics from the point of view of the environment. Manufacturing is a complex process with many different interactions between the parameters controlling the manufacturing machine tools. In the past, manufacturing planners and operators have set these parameters without understanding the consequences, leading to resource waste of energy, cutting fluid, and so on. This chapter presents a computer tool for evaluating and quantifying the effects of different manufacturing choices using chosen criteria. The tool was implemented as part of the work for a European project. It is based on an extensive analysis of machine tools to provide a way of handling the complexities of understanding the use phase of products.

The Education Part of Green Computing in Higher Education and Beyond

In order for the population as a whole to consider green computing an essential part of environmental responsibility, the average citizen must be made aware of the issues and motivated to act. Often the users of technology are not technically trained; hence, information must be presented in language suitable for a lay person in this area. This chapter addresses current efforts being made to provide this education. Resources available from the federal government, state governments, non-profit groups, trade associations, and colleges and universities are discussed. In particular, in preparation for this chapter, the websites of all 50 states were surveyed for appropriate information. The entire life cycle of computing equipment is covered so that businesses and individual households are able to obtain the information needed to make environmentally sound technology decisions.

Essential Technologies for Location-Aware Mobile, Online Map Prefetching, and Caching

Map navigation is one of the most popular applications used by mobile users. At the same time, it is also one of the time- and resource-consuming applications. Various methods such as most-recently used and first-in, first-out algorithms are used to reduce the map transmission time and delay. One of the popular methods is online mobile map prefetching and caching. However, the mobility and location features of mobile users are usually left out by these methods. Caching and prefetching maps based on a mobile user’s location would greatly reduce the transmission time and hence the battery power consumption. For example, if a user is visiting a town, prefetching the maps of nearby interesting stores and caching the maps of the visited, neighboring landmarks would help the user’s visitation experience and save the transmission time. Online mobile map prefetching or caching is useful, but is not widely employed because it involves several different subjects and developers usually are not familiar with all of them. This chapter intends to relieve the problem by introducing essential technologies for online mobile map prefetching and caching so more developers can start working on this kind of project or research. It consists of four themes: (1) green handheld computing, (2) location-based services and programming, (3) map tile system, and (4) location-aware map prefetching and caching methods. A summary is given at the end of this chapter.

Multidimensional Analysis of Supply Chain Environmental Performance

Monitoring the environmental performance of a product is recognized to be increasingly important. The most common method of measuring the environmental performance is the international standards of Life Cycle Assessment (LCA). Typically, measuring is based on estimations and average values at product category level. In this chapter, the authors present a framework for measuring environmental impact at the item level. Using Traceability Graph emissions and resources, it can be monitored from the data management perspective. The model can be mapped to any precision level of physical tracing. At the most precise level, even a single physical object and its components can be analyzed. This, of course, demands that the related objects and their components are identified and mapped to the database. From the opposite perspective, the authors’ model also supports rough level analysis of products and their histories. In terms of the Traceability Cube, multidimensional analysis can be applied for traceability data.

Energy-Aware Intelligence in Smart Spaces

The improvement of energy efficiency in our society has become an urgent issue for sustainability under global warming. The authors present research issues on sensor-based smart environments for energy-aware intelligence, and showcase a study of algorithms for monitoring human activities that provides the context awareness to the smart environments. In order to build energy-aware environments, it is desirable to embed intelligence into the environment itself so that the environment can interpret human behavior in order to adjust itself to human activities occurring in the environment. This is achievable by integrating the environment and the intelligent computing facilities. The computing facility embedded in the environment is equipped with intelligent algorithms that can monitor salient features indicative of the events and learn and recognize changes in the environment. Recent developments in sensor-based intelligent systems can provide suitable algorithms and facilities for building such energy-aware smart environments. The authors present a framework for monitoring human activities in daily living toward the energy-aware intelligence that can detect and learn inhabitants’ behavior patterns in the smart environment.

Towards a Structured Cloud ROI

Organisational Sustainability Modelling (OSM) is a new way to measure Cloud business performance quantitatively and accurately, and is a key area offered by Cloud Computing Business Framework (CCBF). OSM combines statistical computation and 3D Visualisation to present the Return on Investment (ROI) arising from the adoption of Cloud Computing by organisations, and makes use of a highly structured and organised process to review and evaluate Cloud business performance. The School of Electronics and Computer Science (ECS), University of Southampton, focusing on cost-savings, is the case study used to illustrate. In addition, i-Solutions and Corporate Planning of the University of Southampton, focusing on user confidence level and service improvement, are another two case studies to support. Data measurements have been taken in the past three years and quantitative analysis has been carefully checked and calculated by OSM to measure ROI. The University of Southampton has achieved cost saving and user confidence with service improvement offered by Cloud adoption and services, which have been deployed by several universities in the adoption of CCBF.