Smart Microgrids: Overview and Outlook

The idea of changing our energy system from a hierarchical design into a set of nearly independent microgrids becomes feasible with the availability of small renewable energy generators. The smart microgrid concept comes with several challenges in research and engineering targeting load balancing, pricing, consumer integration and home automation. In this paper we first provide an overview on these challenges and present approaches that target the problems identified. While there exist promising algorithms for the particular field, we see a missing integration which specifically targets smart microgrids. Therefore, we propose an architecture that integrates the presented approaches and defines interfaces between the identified components such as generators, storage, smart and \dq{dumb} devices.Comment: presented at the GI Informatik 2012, Braunschweig Germany, Smart Grid Worksho

The Next 700 CPU Power Models

International audienceSoftware power estimation of CPUs is a central concern for energy efficiency and resource management in data centers. Over the last few years, a dozen of ad hoc power models have been proposed to cope with the wide diversity and the growing complexity of modern CPU architectures. However, most of these CPU power models rely on a thorough expertise of the targeted architectures, thus leading to the design of hardware-specific solutions that can hardly be ported beyond the initial settings. In this article, we rather propose a novel toolkit that uses a configurable/interchangeable learning technique to automatically learn the power model of a CPU, independently of the features and the complexity it exhibits. In particular, our learning approach automatically explores the space of hardware performance counters made available by a given CPU to isolate the ones that are best correlated to the power consumption of the host, and then infers a power model from the selected counters. Based on a middleware toolkit devoted to the implementation of software-defined power meters, we implement the proposed approach to generate CPU power models for a wide diversity of CPU architectures (including Intel, ARM, and AMD processors), and using a large variety of both CPU and memory-intensive workloads. We show that the CPU power models generated by our middleware toolkit estimate the power consumption of the whole CPU or individual processes with an accuracy of 98.5% on average, thus competing with the state-of-the-art power models

How energy-efficient is your cloud app?

National audienceEnergy measurements in virtualized environments with PowerAP

Self-organizing multimedia delivery : towards emerging delivery paradigms for non-sequential media access

In this thesis the non-sequential delivery of media in dynamic networks is investigated. Consider a scenario where people participate at a social event. With the increased popularity of smart phones and tablet computers people produce more and more multimedia content. They share their content and consume it on popular web platforms. The production and the consumption of such media are, however, different from the typical sequential movie pattern: we call this non-sequential media access. If the infrastructure is not available, visitors cannot share their content with other visitors during the event. The idea is to connect the devices directly, which is further robust even if people move during the event (dynamic networks). Non-sequential media access in combination with dynamic networks brings new challenges for the whole multimedia life cycle. A formalism called Video Notation helps to define the single parts of the life-cycle with a simple and short notation. New measures for transport are needed as well. A caching technique is introduced that allows for evaluating the goodness of content for being cached based on its popularity in different user groups. However, this cache does not cope with the dynamic network requirement, because such a delivery has to be robust, adaptive and scalable. Therefore, we concentrate on self-organizing algorithms that provide these characteristics. In this thesis the implemented algorithm is inspired by the endocrine system of higher mammals. A client can express its demands by creating hormones that will be released to the network. The corresponding resources are attracted by this hormone and travel towards a higher hormone concentration. This leads to a placement of content near to the users. Furthermore, the robustness and service quality is increased by placing replicas of the traveling content along the transport path. Unused replicas are automatically removed from the nodes, to ensure storage balancing. Finally, we show with a use case that a middleware based on the hormone-based delivery including well-defined interfaces to the user and to the network can be used for content delivery other than multimedia. For such general application recommendations on possible configurations are made.Keine Zusammenfassung vorhandenAnita SobeAbweichender Titel laut Übersetzung der Verfasserin/des VerfassersKlagenfurt, Alpen-Adria-Univ., Diss., 2011KB2011 27OeBB(VLID)241229