987 resultados para Data center


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Virtual Machine (VM) management is an obvious need in today's data centers for various management activities and is accomplished in two phases— finding an optimal VM placement plan and implementing that placement through live VM migrations. These phases result in two research problems— VM placement problem (VMPP) and VM migration scheduling problem (VMMSP). This research proposes and develops several evolutionary algorithms and heuristic algorithms to address the VMPP and VMMSP. Experimental results show the effectiveness and scalability of the proposed algorithms. Finally, a VM management framework has been proposed and developed to automate the VM management activity in cost-efficient way.

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With data centers being the supporting infrastructure for a wide range of IT services, their efficiency has become a big concern to operators, as well as to society, for both economic and environmental reasons. The goal of this thesis is to design energy-efficient algorithms that reduce energy cost while minimizing compromise to service. We focus on the algorithmic challenges at different levels of energy optimization across the data center stack. The algorithmic challenge at the device level is to improve the energy efficiency of a single computational device via techniques such as job scheduling and speed scaling. We analyze the common speed scaling algorithms in both the worst-case model and stochastic model to answer some fundamental issues in the design of speed scaling algorithms. The algorithmic challenge at the local data center level is to dynamically allocate resources (e.g., servers) and to dispatch the workload in a data center. We develop an online algorithm to make a data center more power-proportional by dynamically adapting the number of active servers. The algorithmic challenge at the global data center level is to dispatch the workload across multiple data centers, considering the geographical diversity of electricity price, availability of renewable energy, and network propagation delay. We propose algorithms to jointly optimize routing and provisioning in an online manner. Motivated by the above online decision problems, we move on to study a general class of online problem named "smoothed online convex optimization", which seeks to minimize the sum of a sequence of convex functions when "smooth" solutions are preferred. This model allows us to bridge different research communities and help us get a more fundamental understanding of general online decision problems.

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Theoretical investigations have been carried out to analyze and compare the link power budget and power dissipation of non-return-to-zero (NRZ), pulse amplitude modulation-4 (PAM-4), carrierless amplitude and phase modulation-16 (CAP-16) and 16-quadrature amplitude modulation-orthogonal frequency division multiplexing (16-QAM-OFDM) systems for data center interconnect scenarios. It is shown that for multimode fiber (MMF) links, NRZ modulation schemes with electronic equalization offer the best link power budget margins with the least power dissipation for short transmission distances up to 200 m; while OOFDM is the only scheme which can support a distance of 300 m albeit with power dissipation as high as 4 times that of NRZ. For short single mode fiber (SMF) links, all the modulation schemes offer similar link power budget margins for fiber lengths up to 15 km, but NRZ and PAM-4 are preferable due to their system simplicity and low power consumption. For lengths of up to 30 km, CAP-16 and OOFDM are required although the schemes consume 2 and 4 times as much power respectively compared to that of NRZ. OOFDM alone allows link operation up to 35 km distances. © 1983-2012 IEEE.

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We propose a low latency optical data center top of rack switch using recirculation buffering and a hybrid MZ/SOA switch architecture to reduce the network power dissipated on future optically connected server chips by 53%. © OSA 2014.

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The US National Oceanic and Atmospheric Administration (NOAA) Fisheries Continuous Plankton Recorder (CPR) Survey has sampled four routes: Boston–Nova Scotia (1961–present), New York toward Bermuda (1976–present), Narragansett Bay–Mount Hope Bay–Rhode Island Sound (1998–present) and eastward of Chesapeake Bay (1974–1980). NOAA involvement began in 1974 when it assumed responsibility for the existing Boston–Nova Scotia route from what is now the UK's Sir Alister Hardy Foundation for Ocean Science (SAHFOS). Training, equipment and computer software were provided by SAHFOS to ensure continuity for this and standard protocols for any new routes. Data for the first 14 years of this route were provided to NOAA by SAHFOS. Comparison of collection methods; sample processing; and sample identification, staging and counting techniques revealed near-consistency between NOAA and SAHFOS. One departure involved phytoplankton counting standards. This has since been addressed and the data corrected. Within- and between-survey taxonomic and life-stage names and their consistency through time were, and continue to be, an issue. For this, a cross-reference table has been generated that contains the SAHFOS taxonomic code, NOAA taxonomic code, NOAA life-stage code, National Oceanographic Data Center (NODC) taxonomic code, Integrated Taxonomic Information System (ITIS) serial number and authority and consistent use/route. This table is available for review/use by other CPR surveys. Details of the NOAA and SAHFOS comparison and analytical techniques unique to NOAA are presented.

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Increasingly large amounts of data are stored in main memory of data center servers. However, DRAM-based memory is an important consumer of energy and is unlikely to scale in the future. Various byte-addressable non-volatile memory (NVM) technologies promise high density and near-zero static energy, however they suffer from increased latency and increased dynamic energy consumption.

This paper proposes to leverage a hybrid memory architecture, consisting of both DRAM and NVM, by novel, application-level data management policies that decide to place data on DRAM vs. NVM. We analyze modern column-oriented and key-value data stores and demonstrate the feasibility of application-level data management. Cycle-accurate simulation confirms that our methodology reduces the energy with least performance degradation as compared to the current state-of-the-art hardware or OS approaches. Moreover, we utilize our techniques to apportion DRAM and NVM memory sizes for these workloads.

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A first-stage collision database is assembled which contains electron-impact excitation, ionization, and recombination rate coefficients for Be, Be+, Be2+, and Be3+. The first-stage database is constructed using the R-matrix with pseudo-states, time-dependent close-coupling, and perturbative, distorted-wave methods. A second-stage collision database is then assembled which contains generalized collisional-radiative and radiated power loss coefficients. The second-stage database is constructed by solution of collisional-radiative equations in the quasi-static equilibrium approximation using the first-stage database. Both collision database stages reside in electronic form at the ORNL Controlled Fusion Atomic Data Center and in the ADAS database, and are easily accessed over the worldwide internet. © 2007 Elsevier Inc. All rights reserved.

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A first stage collision database is assembled which contains electron-impact effective collision strengths, and ionization and recombination rate coefficients for Li, Li+, and Li2+. The first stage database is constructed using the R-matrix with pseudo-states, time-dependent close-coupling, converged close-coupling, and perturbative distorted-wave methods. A second stage collision database is then assembled which contains generalized collisional-radiative and radiated power loss coefficients. The second stage database is constructed by solution of collisional-radiative equations in the quasi-static equilibrium approximation using the first stage database. Both collision database stages reside in electronic form at the ORNL Controlled Fusion Atomic Data Center and in the ADAS database, and are easily accessed over the worldwide internet. ?? 2006 Elsevier Inc. All rights reserved.

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The aim of this study is to evaluate the variation of solar radiation data between different data sources that will be free and available at the Solar Energy Research Center (SERC). The comparison between data sources will be carried out for two locations: Stockholm, Sweden and Athens, Greece. For the desired locations, data is gathered for different tilt angles: 0°, 30°, 45°, 60° facing south. The full dataset is available in two excel files: “Stockholm annual irradiation” and “Athens annual irradiation”. The World Radiation Data Center (WRDC) is defined as a reference for the comparison with other dtaasets, because it has the highest time span recorded for Stockholm (1964–2010) and Athens (1964–1986), in form of average monthly irradiation, expressed in kWh/m2. The indicator defined for the data comparison is the estimated standard deviation. The mean biased error (MBE) and the root mean square error (RMSE) were also used as statistical indicators for the horizontal solar irradiation data. The variation in solar irradiation data is categorized in two categories: natural or inter-annual variability, due to different data sources and lastly due to different calculation models. The inter-annual variation for Stockholm is 140.4kWh/m2 or 14.4% and 124.3kWh/m2 or 8.0% for Athens. The estimated deviation for horizontal solar irradiation is 3.7% for Stockholm and 4.4% Athens. This estimated deviation is respectively equal to 4.5% and 3.6% for Stockholm and Athens at 30° tilt, 5.2% and 4.5% at 45° tilt, 5.9% and 7.0% at 60°. NASA’s SSE, SAM and RETScreen (respectively Satel-light) exhibited the highest deviation from WRDC’s data for Stockholm (respectively Athens). The essential source for variation is notably the difference in horizontal solar irradiation. The variation increases by 1-2% per degree of tilt, using different calculation models, as used in PVSYST and Meteonorm. The location and altitude of the data source did not directly influence the variation with the WRDC data. Further examination is suggested in order to improve the methodology of selecting the location; Examining the functional dependence of ground reflected radiation with ambient temperature; variation of ambient temperature and its impact on different solar energy systems; Im pact of variation in solar irradiation and ambient temperature on system output.

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Con l'avanzare della tecnologia, i Big Data hanno assunto un ruolo importante. In questo lavoro è stato implementato, in linguaggio Java, un software volto alla analisi dei Big Data mediante R e Hadoop/MapReduce. Il software è stato utilizzato per analizzare le tracce rilasciate da Google, riguardanti il funzionamento dei suoi data center.

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