Integrated Green Cloud Computing Architecture

Arbitrary usage of cloud computing, either private or public, can lead to uneconomical energy consumption in data processing, storage and communication. Hence, green cloud computing solutions aim not only to save energy but also reduce operational costs and carbon footprints on the environment. In this paper, an Integrated Green Cloud Architecture (IGCA) is proposed that comprises of a client-oriented Green Cloud Middleware to assist managers in better overseeing and configuring their overall access to cloud services in the greenest or most energy-efficient way. Decision making, whether to use local machine processing, private or public clouds, is smartly handled by the middleware using predefined system specifications such as service level agreement (SLA), Quality of service (QoS), equipment specifications and job description provided by IT department. Analytical model is used to show the feasibility to achieve efficient energy consumption while choosing between local, private and public Cloud service provider (CSP).Comment: 6 pages, International Conference on Advanced Computer Science Applications and Technologies, ACSAT 201

Air Force Institute of Technology Research Report 2009

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

Radiological Society of North America (RSNA) 3D printing Special Interest Group (SIG): Guidelines for medical 3D printing and appropriateness for clinical scenarios

Este número da revista Cadernos de Estudos Sociais estava em organização quando fomos colhidos pela morte do sociólogo Ernesto Laclau. Seu falecimento em 13 de abril de 2014 surpreendeu a todos, e particularmente ao editor Joanildo Burity, que foi seu orientando de doutorado na University of Essex, Inglaterra, e que recentemente o trouxe à Fundação Joaquim Nabuco para uma palestra, permitindo que muitos pudessem dialogar com um dos grandes intelectuais latinoamericanos contemporâneos. Assim, buscamos fazer uma homenagem ao sociólogo argentino publicando uma entrevista inédita concedida durante a sua passagem pelo Recife, em 2013, encerrando essa revista com uma sessão especial sobre a sua trajetória

Ordonnancement de l'activité des noeuds dans les réseaux ad hoc et les réseaux de capteurs sans fil

National audienceL'efficacité énergétique est une exigence majeure pour les réseaux sans fil où certains noeuds opèrent sur batterie. L'ordonnancement de l'activité des noeuds permet de distinguer périodes actives où la communication radio est possible et périodes inactives où la radio est arrêtée. Cet ordonnancement contribue largement à améliorer l'efficacité énergétique : d'une part en évitant les collisions entre transmissions conflictuelles et donc les retransmissions associées et d'autre part en permettant aux noeuds non concernés par la transmission de dormir pour économiser leur énergie. Parmi les solutions possibles, nous étudierons plus particulièrement le coloriage des noeuds. Après avoir défini le problème et ses différentes déclinaisons, nous donnerons sa complexité et proposerons SERENA, un algorithme de coloriage distribué qui s'adapte à la collecte de données. Nous présenterons OSERENA, l'optimisation de SERENA pour les réseaux denses et son utilisation dans le réseau de capteurs sans fil OCARI. Lorsque les noeuds ont des charges de trafic fortement hétérogènes, il devient plus intéressant d'effectuer une assignation de slots. Disposer d'un accès au médium multicanal et d'un puits multi-interfaces permet de gagner en nombre de slots nécessaires à la collecte de données, de réduire les interférences et d'améliorer la résistance aux perturbations. Nous présenterons une formalisation en ILP (Integer Linear Programming) du problème d'assignation de slots visant à minimiser le nombre de slots en profitant d'un environnement mono ou multicanal et d'un puits mono ou multi-interfaces. Nous donnerons des bornes théoriques sur le nombre optimal de slots dans diverses configurations et divers environnements (mono ou multicanal, puits mono ou multi-interfaces). Nous présenterons MODESA un algorithme centralisé d'allocatoion conjointe de canaux et slots temporels. Nous terminerons par quelques questions ouvertes

Performance Evaluation of Communication Technologies and Network Structure for Smart Grid Applications

The design of an effective and reliable communication network supporting smart grid applications requires the selection of appropriate communication technologies and protocols. The objective of this study is to study and quantify the capabilities of an advanced metring infrastructure (AMI) to support the simultaneous operation of major smart grid functions. These include smart metring, price-induced controls, distribution automation, demand response, and electric vehicle charging/discharging applications in terms of throughput and latency. OPNET is used to simulate the performance of selected communication technologies and protocols. Research findings indicate that smart grid applications can operate simultaneously by piggybacking on an existing AMI infrastructure and still achieve their latency requirements

Parallel Model Counting with CUDA: Algorithm Engineering for Efficient Hardware Utilization

Propositional model counting (MC) and its extensions as well as applications in the area of probabilistic reasoning have received renewed attention in recent years. As a result, also the need for quickly solving counting-based problems with automated solvers is critical for certain areas. In this paper, we present experiments evaluating various techniques in order to improve the performance of parallel model counting on general purpose graphics processing units (GPGPUs). Thereby, we mainly consider engineering efficient algorithms for model counting on GPGPUs that utilize the treewidth of a propositional formula by means of dynamic programming. The combination of our techniques results in the solver GPUSAT3, which is based on the programming framework Cuda that -compared to other frameworks- shows superior extensibility and driver support. When combining all findings of this work, we show that GPUSAT3 not only solves more instances of the recent Model Counting Competition 2020 (MCC 2020) than existing GPGPU-based systems, but also solves those significantly faster. A portfolio with one of the best solvers of MCC 2020 and GPUSAT3 solves 19% more instances than the former alone in less than half of the runtime

Energy Disaggregation using Two-Stage Fusion of Binary Device Detectors

A data-driven methodology to improve the energy disaggregation accuracy during Non-Intrusive Load Monitoring is proposed. In detail, the method is using a two-stage classification scheme, with the first stage consisting of classification models processing the aggregated signal in parallel and each of them producing a binary device detection score, and the second stage consisting of fusion regression models for estimating the power consumption for each of the electrical appliances. The accuracy of the proposed approach was tested on three datasets (ECO, REDD and iAWE), which are available online, using four different classifiers. The presented approach improves the estimation accuracy by up to 4.1% with respect to a basic energy disaggregation architecture, while the improvement on device level was up to 10.1%. Analysis on device level showed significant improvement of power consumption estimation accuracy especially for continuous and non-linear appliances across all evaluated datasets