Energy Aware Software-Engineering and Development (EASED@BUIS)
The EASED workshop will be held in conjunction with the 5th BUIS-Days: IT-based resource and energy management .
Utilization of mobile and embedded devices, and thus their induced energy consumption, is constantly increasing. Reducing the energy consumption of such devices will not only improve the carbon footprint of contemporary mobile IT usage, but will also extend the device lifetime, improve user acceptance and reduce operational costs.
Next to serious and ongoing efforts in hardware design and on operating system level, software engineering techniques will also contribute to optimize energy consumption by improving software design and software quality. The EASED@BUIS workshop, which follows up the Workshop on Developing Energy Aware Software Systems (EEbS 2012) , held at the annual GI Conference in September 2012, provides a broad forum for researchers and practitioners to discuss ongoing works, latest results, and common topics of interest regarding the improvement of software induced energy consumption.
Intensive discussions at the first workshop identified a major challenge in optimizing energy efficiency, which is to precisely measure energy consumption of software regarding user behavior. Thus, the follow workshop EASED@BUIS will focus on the following topics:
- approaches and techniques to estimate or measure the energy consumption of software components,
- approaches to define standardized usage scenarios of applications on mobile devices to provide repeatable measurement of energy consumption in concrete application settings,
- approaches to model the energy consumption of software components, and
- experiences on measuring and improving the energy consumption of software components.
Well elaborated and standardized measurement means will provide an important foundation to detecting sources of wasting energy caused by software systems and will enable validation means to verify energy savings by software improvements.
EASED@BUIS will be organized as a one day discussion-intensive workshop to provoke intensive collaborations among the participants. It is intended to initiate collaborative works on standardizing (static and dynamic) measuring techniques for energy consumption.
To further stimulate these discussions, authors are invited to submit position papers one on the workshop´s topics. Accepted papers will be presented at the workshop and will be published in Softwaretechnik-Trends.
EASED@BUIS is supported by the GI special Interest groups:
- Software Technology
- Environmental Informatics
Submissions and important Dates
Authors are encouraged to submit their position papers (2 pages in two column form [style , template]) not later than March 15, 2013 through easychair.
paper submission deadline: March 15, 2013
author notification: March 25, 2013
camera-ready deadline: April 1, 2013
Christian Bunse (University of the Applied Sciences Stralsund)
Stefan Naumann (University of the Applied Sciences Trier, Environmental Campus Birkenfeld)
Andreas Winter (Carl von Ossietzky University, Oldenburg)
Colin Atkinson (University Mannheim)
Paris Avgeriou (University of Groningen)
Holger Eichelberger (University Hildesheim)
Sebastian Götz (TU Dresden)
Theo Härder (TU Kaiserslautern)
Mirco Josefiok (OFFIS, Oldenburg)
Ákos Kiss (University of Szeged)
Sonja Klingert (University Mannheim)
Patricia Lago (VU University Amsterdam)
Thierry Leboucq (KaliTerre, Nantes)
Birgit Penzenstadler (TU München)
Giuseppe Scanniello (University of Basilicata)
Maximilian Schirmer (Bauhaus-University Weimar)
Gunnar Schomaker (OFFIS Oldenburg)
Joost Visser (Software Improvement Group, Amsterdam)
Claas Wilke (TU Dresden)
Alexandru Telea (University of Groningen)
Marion Gottschalk (Carl von Ossietzky University, Oldenburg)
Andreas Winter (Carl von Ossietzky University, Oldenburg)
2nd Workshop EASED@BUIS 2013
9:00 - 9:45
- Opening Session (with BUIS)
- Andreas F. L. Heydemann (CeWe Color)
Keynote (with BUIS)
9:45 - 10:00
10:00 - 12:15 Energy Aware Programming and Optimization
- Christian Bunse, Sebastian Stiemer
On the Energy Consumption of Design PatternsIn this paper, we compare the impact of design patterns application onto the energy consumption of mobile (i.e., smartphone applications (Apps)). Therefore, small apps for the Android platform were developed in dierent variants by using or not using a specific pattern. The energy consumption of these apps was measured by using the PowerTutor-App, developed at the University of Michigan. The results regarding the selected pattern subset (facade, abstract factory, observer, decorator, prototype, and template method) are widely unremarkable. However, results regarding the decorator pattern show a signicant negative impact onto energy consumption. Further investigation conrmed the results for further apps.
- Timo Hönig, Christopher Eibel, Wolfgang Schröder-Preikschat, Björn Cassens, Rüdiger Kapitza
Proactive Energy-Aware System Software Design with SEEPDown to the present day, program code is commonly not optimized for energy-efficiency. As developers improve their program code merely with regards to speed and correctness, it leads to the situation that system software components needlessly waste energy resources. To address this, we are convinced that new concepts for energy-aware programming need to be established. Most of all it is required to provide strong tooling support for developers to ease the task of increasing the energy-efficiency of software. Such tooling support relieves developers from manually examining software for energy hotspots by providing a high degree of automation. This is a challenging endeavor as the diversification of hardware platforms steadily increases and analyzing program code asks for high analysis efforts. In this paper, we propose a proactive approach which addresses these challenges in order to propagate energy-aware programming. We exploit symbolic execution techniques for automatic code path exploration and provide energy estimates for program code by means of platform-specific energy profiles.
- Sebastian Götz, Renè Schöne, Claas Wilke, Julian Mendez, Uwe Assmann
Towards Predictive Self-optimization by Situation RecognitionEnergy efficiency of software is an increasingly important topic. To achieve energy efficiency, a system should automatically optimize itself to provide the best possible utility to the user for the least possible cost in terms of energy consumption. To reach this goal, the system has to continuously decide whether and how to adapt itself, which takes time and consumes energy by itself. During this time, the system could be in an inefficient state and waste energy. We envision the application of predictive situation recognition to initiate decision making before it is actually needed. Thus, the time of the system being in an inefficient state is reduced, leading to a more energy efficient reconfiguration.
- Stefan Naumann, Eva Kern, Markus Dick
Classifying Green Software Engineering - The GREENSOFT ModelUp to now several relationships between Information and Communication Technology (ICT) and Sustainable Development (SD) are published. However, especially in the field of energy aware or green software there is a lack of detailed descriptions. Since this field is rising, it is useful to formulate some definitions. These classifications can also help to develop a research agenda for energy aware software and its development.
12:15 - 13:15
13:15 - 15:15 Measuring and Estimating Energy Consumption
- Kay Grosskop
PUE for end users - Are you interested in more than bread toasting?The Power Usage Effectiveness (PUE) indicator for efficiency of data center infrastructure has been very successful. But focusing solely on PUE tends to restrict action to data center infrastructure management and in some situations even gives a perverse stimulus against optimization at the IT equipment and software levels. Despite the high relevance, no accepted metric has emerged to support optimization and allow the rating of the energy efficiency of the whole stack. This paper presents a metric, the Consumption Near Sweetspot(CNS), that for a part can fill this gap. It captures how well the system-relative energy efficiency optimum and its utilization are aligned. A key advantage is that it allows comparison of functionally very different services. The metric is compared to the Fixed to Variable Energy Ratio (FVER) metric for data centers recently proposed by the British Computer Society and to Digital Service Efficiency (DSE), a service level energy indicator presented by Ebay.
- Mirco Josefiok, Marcel Schröder, Andreas Winter
An Energy Abstraction Layer for Mobile Computing DevicesSince the growing popularity of smartphones and tablet devices, energy-efficiency in mobile computing is an increasingly interesting topic. But in case of software development engineering energy-efficiency is widely neglected, even clear and simply applicable means to measure and visualize energy consumption caused by software usage is still in its infancy. This work provides basic research in the field of measuring energy and power related information on mobile computing devices and proposes an abstract specification for implementing a measurement infrastructure on different mobile computing devices.
- Patrick Heinrich
Towards Network-Wide Energy Estimation for Adaptive Embedded SystemsThis paper discusses the next steps towards how system developers can easily and accurately evaluate the impact of their system design choices on energy consumption during the early stages of the design process. To do this, energy estimations in every phase of system development are necessary. Our research focuses on adaptive systems, where applications are activated according to the actual need. In this paper we present an approach which derives the energy consumption per application using a combination of energy relevant software and hardware parameters. The aim is to create energy building blocks for applications to estimate the energy consumption of a system with multiple applications running on it. This approach utilizes the high environmental interaction of embedded systems where sensors and actors consume more energy than CPUs. The granularity of the energy estimation is the application level, due to focusing on adaptive systems.
- Dmitriy Shorin, Armin Zimmermann
Evaluation of Embedded System Energy Usage with Extended UML ModelsEnergy consumption as an increasingly important decision criterion has to be included in the search for good architectural and design alternatives to make an embedded system as energy-efficient as possible. The proposed method describes a system with dedicated extended UML models for applications and hardware components and evaluates the energy use via a transformation into an analyzable stochastic Petri net.