By Steve Easterbrook, University of Toronto, Canada

Well, I cheated with this – it’s the short version of the talk I gave last year at ICSE. I thought it would be useful to include here, as it was this session that kicked off the idea for a workshop series. Slides and other material from last year are available here.

(click image to see the video)

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By Robina Hetherington, Stephen Peake and Robin Laney, The Open University, UK

(click the image to see the video)

By He Zhang, Lin Liu (Tsinghua University, Beijing, China), Sheikh Iqbal Ahamed, and Farzana Rahman (Marquette University, WI, USA)

Excerpt: As climate change becoming an important global issue, more and more people begin to pay attention to reduce greenhouse gas emissions. Reducing GHG emissions needs to measure the emissions in specific areas, and to identify the major GHG emitting activities. Based on the knowledge of the major emitting activities and their impact on the environment, domain experts could build quantitative models and propose solid mitigation strategies and plans. To measure personal or household carbon dioxide emission, there are already plenty of carbon footprint calculators available on-line. Most of these calculators use quantitative models to estimate carbon emission caused by the user’s activities. Although the calculators can promote public awareness of the carbon emission from individual behavior, there are also concerns about the consistency and transparency of the existing carbon calculators [Padgett,1997]. Apart from a small group of smart phone carbon footprint calculation applications, most of the existing carbon calculators require users to input the data manually. This not only provides poor user experience, but also makes the calculation less accurate. In this paper we are going to propose our approach to design of an open calculation platform for individual users. The platform maintains a model registry for quantitative human activity-carbon emission models used for calculation, and it uses on-line data services and sensor data as major source of input. In the following section, we’ll introduce the data structure of the model repository and the carbon footprint calculation mechanism.

By Justyna Zander, Harvard University, Cambridge, MA, and Fraunhofer Institute FOKUS, Berlin, Germany

Excerpt: Recently, the attention around climate change and global warming has been raised in the context of the models capabilities, their predictive power, and the reliability of the results. In the proceedings, a few examples of failures in climate models and their execution are pointed out, main reasons of the problems are discussed, and a novel perspective on analysis of those issues is proposed. The sources of information are extensively referenced to the multimedia publications elsewhere.

Full paper here

By Herna L Viktor, University of Ottawa, Canada

Excerpt: Increasingly, the findings of climate change research have come under attack by skeptics. Such attacks usually focus on inconsistencies between the findings of different studies and then aim to convince that the changes in climate have been overrated, or are non-existent. This is especially evident in the popular media, where discrepancies are often highlighted and opinions are being biased. It is therefore not surprising that a 2007 study of Ipsos Mori in the UK indicated that 56% of adults were not convinced that climate change is real.  Furthermore, 2006 polls showed that about half of the populations of the USA (53%), France (51%) and Spain (44%) expressed little or no concern about climate change.  In addition, 2009 polls in the USA and China concluded that the general public does not believe that the earth is getting warmer because of human activity, such as burning fossil fuels. This disbelief stands in stark contrast with the scientific findings, as the science academies of all major industrialized countries have now agreed that human activities are, indeed, a major cause of concern.

Full paper here

Update (20/4/2010) Version 2 here

By Hasan Sözer, Arjan De Roo, and Mehmet Akşit, University of Twente, Enschede, The Netherlands

Abstract: Energy consumption has become one of the important system properties that should be controlled by embedded control software. There is usually an inherent trade-off between energy consumption and several system qualities. As such, optimization techniques should be adopted for making the desired trade-off among quality attributes. Implementations of these techniques are usually ad-hoc and system-specific, leading to implicit design decisions distributed over several software components. We propose an architectural framework for custom synthesis of control software from reusable and programmable elements. The goal is to facilitate systematic reuse of knowledge in the optimization domain and explicit management of quality trade-offs for energy optimization of embedded systems.

Full paper here

By Ian Sommerville, St Andrews University, Scotland

Preamble: I will not be attending the workshop (or ICSE) in person as I have made a personal commitment to reduce my own business travel significantly (alas, the 90% target is not yet realisable). While I understand the rationale for organising this workshop, I think that, as a community, we will not be listened to unless we set an example and that flying many thousands of kilometres to discuss methods of reducing carbon emissions is something that really has to stop.

Full paper here

By Govindaraj Rangaraj and Rami Bahsoon, The University of Birmingham, Birmingham, United Kingdom

Excerpt: Software systems architects are continually faced with the challenge of scaling up software systems architectures to support constantly growing load of users’ processing needs and data. Scaling up the architectures to meet these needs does certainly introduce additional energy cost.   For  example, to meet  the scalability requirements,  additional  hardware and  software resources  may  need  to  be  deployed.    Reducing the energy demands in  such  architectures while  meeting the  scalability requirements, are always  challenging. We explicate the attention to power  as  an  architectural  constraint/property that need  to  be analyzed in relation with scalability. Current research and practice to distributed software architecture approaches are green-unaware. They don’t provide the primitives for reasoning and managing power consumption. We  argue  that the software  engineering should  be green aware,  where  the  software  engineering and design  activities should  not only  be  judged  by  their  technical merits,  but also by their  contributions to energy  savings.  In particular, the software system architecture appears to be the appropriate level of abstraction to address green-aware concerns. Software architectures should be green-aware, providing power management mechanisms as part of the architecture primitives. Furthermore, it looks plausible to leverage on advances in self-management software architectures [2], where self-managing power  could  be separated from  the core system functionalities. We  argue  that there  is a pragmatic need  for new  software architectural layer,  which  could  be  easily  integrated with existing  styles for self-managing the trade-offs between  scalability and  power. The power consumption can be minimized by only provisioning the required amount of resource at any given point of time. For example, architecture can be scaled only when the demand for the resource increases. Classical market-based economic theory is appealing for addressing this problem effectively in the context of supply/demand.

Full paper here

By Jon Pipitone, Jorge Aranda and Valeria Cortés, University of Toronto, Canada

Abstract: Climate change poses great challenges to the viability of our civilization, and if we are to overcome these challenges we need to bring the best of our abilities to the table. In this paper we propose a set of guidelines for software researchers concerned about doing the right thing for the planet.

By Maurizio Morisio, Marco Torchiano and Antonio Vetro, Politecnico di Torino, Italy

Abstract: Energy efficiency is finally becoming a mainstream goal in a limited world where consumption of resources cannot grow forever. ICT is both a key player in energy efficiency, and a power drainer (10% of energy demand in 2009 – http://www.smart2020.org/). To reduce the power consumption of both installed ICT equipment, and to design future energy efficient equipment it is essential to have precise figures of the current consumption. Today these figures are incomplete and not precise. The goal of this proposal is to build a software framework capable of collecting power consumption data from fixed and mobile terminals in a network (PCs, servers, mobile phones, etc). The framework should be easy to install and operate, scalable and – of course – energy efficient. Data collection on power consumption is made on three levels: global, per hardware component (CPU, disk drive, peripherals, RF devices), per software function (OS, services, applications). The framework offers (software) power gauges to be installed seamlessly on terminals, an XML data format to represent power consumption, and repositories to store the data collected. The goal of our idea is to understand:

  • Real measurements on systems’ power consumption,
  • Relationships between power consumption and usage/characteristics of applications,
  • Relationships between power consumption and user characteristics,
  • Systems/applications that need improvements in order to be more efficient,
  • The effect of machine based power reduction techniques,
  • The effect of human based power reduction techniques.

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