Relevant bibliographies by topics / Disaggregation in data centers

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Disaggregation in data centers'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Disaggregation in data centers"

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Moralis-Pegios, Miltiadis, Nikolaos Terzenidis, George Mourgias-Alexandris, and Konstantinos Vyrsokinos. "Silicon Photonics towards Disaggregation of Resources in Data Centers." Applied Sciences 8, no. 1 (2018): 83. http://dx.doi.org/10.3390/app8010083.

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Coughlin, Tom. "Data Center Disaggregation Using NVMe." IEEE Consumer Electronics Magazine 8, no. 5 (2019): 54–56. http://dx.doi.org/10.1109/mce.2019.2923932.

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Suzuki, Jun, Yoichi Hidaka, Junichi Higuchi, Yuki Hayashi, Masaki Kan, and Takashi Yoshikawa. "Disaggregation and Sharing of I/O Devices in Cloud Data Centers." IEEE Transactions on Computers 65, no. 10 (2016): 3013–26. http://dx.doi.org/10.1109/tc.2015.2513759.

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Zhang, Yiying. "Make It Real: An End-to-End Implementation of A Physically Disaggregated Data Center." ACM SIGOPS Operating Systems Review 57, no. 1 (2023): 1–9. http://dx.doi.org/10.1145/3606557.3606559.

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Resource disaggregation is an approach to separate different hardware resources into independent pools in a data center, so that these pools can be easily managed and their resources can be allocated in a tight but unbounded way. The past decade has seen research and practices in realizing the resource-disaggregation idea on regular servers. We advocate for a physically disaggregated data center, where disaggregated resource pools consist of hardware devices, not servers. Physical disaggregation could unlock another level of benefits in resource disaggregation, including further improved cost
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Zhang, Qizhen, Yifan Cai, Xinyi Chen, et al. "Understanding the effect of data center resource disaggregation on production DBMSs." Proceedings of the VLDB Endowment 13, no. 9 (2020): 1568–81. http://dx.doi.org/10.14778/3397230.3397249.

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Zhao, Matthew Y., Helen Y. Xu, Vidhi Singh, Megan R. Aaronson, Jayraan Badiee, and Folasade (Fola) P. May. "Mo1019: DISAGGREGATION OF RACE AND ETHNICITY DATA TO EXAMINE COLORECTAL CANCER SCREENING RATES AT FEDERALLY QUALIFIED HEALTH CENTERS." Gastroenterology 169, no. 1 (2025): S—981—S—982. https://doi.org/10.1016/s0016-5085(25)03180-4.

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Pagès, Albert, Rubén Serrano, Jordi Perelló, and Salvatore Spadaro. "On the benefits of resource disaggregation for virtual data centre provisioning in optical data centres." Computer Communications 107 (July 2017): 60–74. http://dx.doi.org/10.1016/j.comcom.2017.03.009.

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Rajan, Sanju, and Linda Joseph. "An Adaptable Optimal Network Topology Model for Efficient Data Centre Design in Storage Area Networks." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 2s (2023): 43–50. http://dx.doi.org/10.17762/ijritcc.v11i2s.6027.

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In this research, we look at how different network topologies affect the energy consumption of modular data centre (DC) setups. We use a combined-input directed approach to assess the benefits of rack-scale and pod-scale fragmentation across a variety of electrical, optoelectronic, and composite network architectures in comparison to a conventional DC. When the optical transport architecture is implemented and the appropriate resource components are distributed, the findings reveal fragmentation at the layer level is adequate, even compared to a pod-scale DC. Composable DCs can operate at peak
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Mishra, Vaibhawa, Joshua L. Benjamin, and Georgios Zervas. "MONet: heterogeneous Memory over Optical Network for large-scale data center resource disaggregation." Journal of Optical Communications and Networking 13, no. 5 (2021): 126. http://dx.doi.org/10.1364/jocn.419145.

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Curry-Stevens, Ann. "What Matters: Achieving Racial Equity in a Human Service Non-Profit Organization." Advances in Social Sciences Research Journal 9, no. 1 (2022): 307–38. http://dx.doi.org/10.14738/assrj.91.11552.

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Few research studies exist on the efforts and outcomes undertaken by non-profits aiming to integrate racial equity into their organization. This article, through case study research, identifies how Metropolitan Family Service (in Portland, Oregon) has make seven key gains over the last decade: staff diversification, cultural shift in the organization, board development, data systems that support disaggregation, meaningful community partnerships, high client satisfaction, and most important, more equitable service outcomes. In additional to sharing details on these gains, this article identifie
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Dissertations / Theses on the topic "Disaggregation in data centers"

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Roozbeh, Amir. "Toward Next-generation Data Centers : Principles of Software-Defined “Hardware” Infrastructures and Resource Disaggregation." Licentiate thesis, KTH, Kommunikationssystem, CoS, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-249618.

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The cloud is evolving due to additional demands introduced by new technological advancements and the wide movement toward digitalization. Therefore, next-generation data centers (DCs) and clouds are expected (and need) to become cheaper, more efficient, and capable of offering more predictable services. Aligned with this, we examine the concept of software-defined “hardware” infrastructures (SDHI) based on hardware resource disaggregation as one possible way of realizing next-generation DCs. We start with an overview of the functional architecture of a cloud based on SDHI. Following this, we d
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Kelly, Daniel. "Disaggregation of domestic smart meter energy data." Thesis, Imperial College London, 2016. http://hdl.handle.net/10044/1/49452.

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Many countries are rolling out smart electricity meters. A smart meter measures the aggregate energy consumption of an entire building. However, appliance-by-appliance energy consumption information may be more valuable than aggregate data for a variety of uses including reducing energy demand and improving load forecasting for the electricity grid. Electricity disaggregation algorithms – the focus of this thesis – estimate appliance-by-appliance electricity demand from aggregate electricity demand. This thesis has three main goals: 1) to critically evaluate the benefits of energy disaggregati
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Bayati, Léa. "Data centers energy optimization." Thesis, Paris Est, 2019. http://www.theses.fr/2019PESC0063.

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Pour garantir à la fois une bonne performance des services offerts par des centres de données, et une consommation énergétique raisonnable, une analyse détaillée du comportement de ces systèmes est essentielle pour la conception d'algorithmes d'optimisation efficaces permettant de réduire la consommation énergétique. Cette thèse, s'inscrit dans ce contexte, et notre travail principal consiste à concevoir des systèmes de gestion dynamique de l'énergie basés sur des modèles stochastiques de files d'attente contrôlées. Le but est de rechercher les politiques de contrôle optimales afin de les appl
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Wey, Karen. "Temporal Disaggregation of Daily Precipitation Data in a Changing Climate." Thesis, University of Waterloo, 2006. http://hdl.handle.net/10012/2859.

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Models for spatially interpolating hourly precipitation data and temporally disaggregating daily precipitation to hourly data are developed for application to multisite scenarios at the watershed scale. The intent is to create models to produce data which are valid input for a hydrologic rainfall-runoff model, from daily data produced by a stochastic weather generator. These models will be used to determine the potential effects of climate change on local precipitation events. A case study is presented applying these models to the Upper Thames River basin in Ontario, Canada; however, t
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Persson, Mathias. "Simultaneous Data Management in Sensor-Based Systems using Disaggregation and Processing." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-188856.

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To enable high performance data management for sensor-based systems the system components in an architecture has to be tailored to the situation at hand. Therefore, each component has to handle a massive amount of data independently, and at the same time cooperate with other components within a system. To facilitate rapid data processing between components, a model detailing the flow of information and specifying internal component structures will assist in faster and more reliable system designs. This thesis presents a model for a scalable, safe, reliable and high performing system for managi
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Sandström, Mimmi. "Modelling of organic data centers." Thesis, KTH, Kemiteknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-289173.

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I det här examensarbetet undersöks möjligheten att återvinna termisk energi genom att driva en så kallad ekologisk datorhall. Denna uppstår genom en integration mellan en storskalig högpresterande datorhall och ett växthus. Den termiska energin, eller spillvärme som den också kallas, genereras i stora mängder som en biprodukt av kylning av datahallar världen över. Avsikten är att använda spillvärme som genereras för att täcka det årliga energibehovet av ett växthus. Syftet med den ekologiska datahallen är att maximera vinsten baserat på alla tre hållbarhetspelarna; den ekonomiska, den miljömäs
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Tudoran, Radu-Marius. "High-Performance Big Data Management Across Cloud Data Centers." Electronic Thesis or Diss., Rennes, École normale supérieure, 2014. http://www.theses.fr/2014ENSR0004.

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La puissance de calcul facilement accessible offerte par les infrastructures clouds, couplés à la révolution du "Big Data", augmentent l'échelle et la vitesse auxquelles l'analyse des données est effectuée. Les ressources de cloud computing pour le calcul et le stockage sont répartis entre plusieurs centres de données de par le monde. Permettre des transferts de données rapides devient particulièrement important dans le cadre d'applications scientifiques pour lesquels déplacer le traitement proche de données est coûteux voire impossible. Les principaux objectifs de cette thèse consistent à ana
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Mahmud, A. S. M. Hasan. "Sustainable Resource Management for Cloud Data Centers." FIU Digital Commons, 2016. http://digitalcommons.fiu.edu/etd/2634.

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In recent years, the demand for data center computing has increased significantly due to the growing popularity of cloud applications and Internet-based services. Today's large data centers host hundreds of thousands of servers and the peak power rating of a single data center may even exceed 100MW. The combined electricity consumption of global data centers accounts for about 3% of worldwide production, raising serious concerns about their carbon footprint. The utility providers and governments are consistently pressuring data center operators to reduce their carbon footprint and energy consu
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Khantaphixay, Sisomphone. "Managing the cost of usable data centers." [Denver, Colo.] : Regis University, 2007. http://165.236.235.140/lib/SKhanthaphixay2008.pdf.

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Mazzucco, Michele. "Revenue maximization problems in commercial data centers." Thesis, University of Newcastle Upon Tyne, 2009. http://hdl.handle.net/10443/457.

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As IT systems are becoming more important everyday, one of the main concerns is that users may face major problems and eventually incur major costs if computing systems do not meet the expected performance requirements: customers expect reliability and performance guarantees, while underperforming systems loose revenues. Even with the adoption of data centers as the hub of IT organizations and provider of business efficiencies the problems are not over because it is extremely difficult for service providers to meet the promised performance guarantees in the face of unpredictable demand. One po
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Books on the topic "Disaggregation in data centers"

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Jayaswal, Kailash. Administering Data Centers. John Wiley & Sons, Ltd., 2005.

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Buffington, Jason. Data Protection for Virtual Data Centers. Wiley Publishing, Inc., 2010. http://dx.doi.org/10.1002/9781118255766.

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Khan, Samee U., and Albert Y. Zomaya, eds. Handbook on Data Centers. Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-2092-1.

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Klingert, Sonja, Xavier Hesselbach-Serra, Maria Perez Ortega, and Giovanni Giuliani, eds. Energy-Efficient Data Centers. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-55149-9.

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Huusko, Jyrki, Hermann de Meer, Sonja Klingert, and Andrey Somov, eds. Energy Efficient Data Centers. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33645-4.

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Klingert, Sonja, Marta Chinnici, and Milagros Rey Porto, eds. Energy Efficient Data Centers. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15786-3.

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Kachris, Christoforos, Babak Falsafi, and Dimitrios Soudris, eds. Hardware Accelerators in Data Centers. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-92792-3.

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Scriba, Albrecht, and Volker Herminghaus. Storage Management in Data Centers. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-85023-6.

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Dai, Jun, Michael M. Ohadi, Diganta Das, and Michael G. Pecht. Optimum Cooling of Data Centers. Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-5602-5.

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American Society of Heating, Refrigerating and Air-Conditioning Engineers. Green tips for data centers. American Society of Heating, Refrigerating, and Air-Conditioning Engineers Inc., 2011.

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Book chapters on the topic "Disaggregation in data centers"

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Terzenidis, Nikos, Miltiadis Moralis-Pegios, Stelios Pitris, et al. "Optics for Disaggregating Data Centers and Disintegrating Computing." In Optical Network Design and Modeling. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38085-4_24.

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Tian, Yu-Chu, and Jing Gao. "Data Centers." In Network Analysis and Architecture. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-5648-7_11.

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Robertazzi, Thomas. "Data Centers." In Basics of Computer Networking. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-2104-7_9.

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Falsafi, Babak, Samuel Midkiff, JackB Dennis, et al. "Data Centers." In Encyclopedia of Parallel Computing. Springer US, 2011. http://dx.doi.org/10.1007/978-0-387-09766-4_391.

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Eckhardt, Johannes M., and Tobias Doeker. "Data Centers." In Springer Series in Optical Sciences. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73738-2_14.

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Khazaii, Javad. "Data Centers." In Advanced Decision Making for HVAC Engineers. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33328-1_3.

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Dantas, Pierre, Waldir Sabino, and Maryana Batalha. "Energy Disaggregation via Data Mining." In Proceedings of the 4th Brazilian Technology Symposium (BTSym'18). Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16053-1_53.

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Lenhart, L., T. Heck, R. Friedrich, et al. "Temporal Disaggregation of Emission Data." In Tropospheric Modelling and Emission Estimation. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-662-03470-5_7.

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Basmadjian, Robert, Pascal Bouvry, Georges Da Costa, et al. "Green Data Centers." In Large-Scale Distributed Systems and Energy Efficiency. John Wiley & Sons, Inc, 2015. http://dx.doi.org/10.1002/9781118981122.ch6.

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Herminghaus, Volker. "Dual Data Centers." In Storage Management in Data Centers. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-85023-6_8.

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Conference papers on the topic "Disaggregation in data centers"

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Zou, Yi, Arun Raghunath, Anjaneya Chagam, Sujoy Sen, and Tushar Gohad. "Rethinking Software Defined Cloud Storage for Disaggregation." In 2019 IEEE 5th International Conference on Big Data Intelligence and Computing (DATACOM). IEEE, 2019. http://dx.doi.org/10.1109/datacom.2019.00034.

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Deveci, Şirin Azazi, and Melih Günay. "Unsupervised Pattern Extraction of Time Series Data for Energy Disaggregation." In 2024 9th International Conference on Computer Science and Engineering (UBMK). IEEE, 2024. https://doi.org/10.1109/ubmk63289.2024.10773561.

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Vilanova, Lluís, Lina Maudlej, Shai Bergman, et al. "Slashing the disaggregation tax in heterogeneous data centers with FractOS." In EuroSys '22: Seventeenth European Conference on Computer Systems. ACM, 2022. http://dx.doi.org/10.1145/3492321.3519569.

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Bachar, Yuval. "Disaggregation – the new way to build mega (and micro) data centers." In 2015 ACM/IEEE Symposium on Architectures for Networking and Communications Systems (ANCS). IEEE, 2015. http://dx.doi.org/10.1109/ancs.2015.7110114.

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Wang, Chenjiu, Ke He, Ruiqi Fan, Xiaonan Wang, Wei Wang, and Qinfen Hao. "CXL over Ethernet: A Novel FPGA-based Memory Disaggregation Design in Data Centers." In 2023 IEEE 31st Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM). IEEE, 2023. http://dx.doi.org/10.1109/fccm57271.2023.00017.

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Begin, Thomas, Alexandre Brandwajn, and Alain Tchana. "Data center disaggregation: when and how much?" In 2022 9th International Conference on Future Internet of Things and Cloud (FiCloud). IEEE, 2022. http://dx.doi.org/10.1109/ficloud57274.2022.00016.

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Cheng, Yuxin, Marilet De Andrade, Lena Wosinska, and Jiajia Chen. "Resource Disaggregation Versus Integrated Servers in Data Centers: Impact of Internal Transmission Capacity Limitation." In 2018 European Conference on Optical Communication (ECOC). IEEE, 2018. http://dx.doi.org/10.1109/ecoc.2018.8535214.

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Marwah, Manish, Martin Arlitt, Christopher Hoover, Cullen Bash, and Ratnesh K. Sharma. "Exploratory Analysis of Aggregate Power Metrics in Data Centers." In ASME 2010 International Mechanical Engineering Congress and Exposition. ASMEDC, 2010. http://dx.doi.org/10.1115/imece2010-39503.

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In recent years, climate change, depletion of conventional energy sources and rising energy costs have led to an increased focus on sustainability. Within the Information Technology (IT) sector, data centers are significant energy consumers. The first steps towards reducing power consumption in data centers are to monitor it and to determine the heavy hitters. Unfortunately, fine-grain power information is often not readily available within data center environments. In this paper, we conduct an exploratory analysis of aggregate power data in a data center. We collect data from the power infras
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Sueyoshi, Asahi, Ken Mishina, Daisuke Hisano, and Akihiro Maruta. "Flexible Data Center Interconnect Based on Optical Aggregation and Electrical Disaggregation." In Conference on Lasers and Electro-Optics/Pacific Rim. Optica Publishing Group, 2022. http://dx.doi.org/10.1364/cleopr.2022.cthp13c_03.

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Michelogiannakis, George, Madeleine Glick, John Shalf, and Keren Bergman. "Photonics as a means to implement intra-rack resource disaggregation." In Metro and Data Center Optical Networks and Short-Reach Links V, edited by Madeleine Glick, Atul K. Srivastava, Youichi Akasaka, Spiros Mikroulis, Benjamin B. Dingel, and Roberto Llorente. SPIE, 2022. http://dx.doi.org/10.1117/12.2607317.

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Reports on the topic "Disaggregation in data centers"

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Tschudi, William, Tengfang Xu, Dale Sartor, Jon Koomey, Bruce Nordman, and Osman Sezgen. Energy efficient data centers. Office of Scientific and Technical Information (OSTI), 2004. http://dx.doi.org/10.2172/841561.

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Colaço, Rajeev, and Stephanie Watson-Grant. A Global Call to Action for Gender-Inclusive Data Collection and Use. RTI Press, 2021. http://dx.doi.org/10.3768/rtipress.2021.pb.0026.2112.

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The global data community has made—and is continuing to make—enormous strides toward collecting, analyzing, and using sex-disaggregated data to improve international development programs. Historically, however, sex-disaggregation has been—and largely continues to be—a binary representation of cisgender female and cisgender male populations. This binary interpretation excludes transgender and gender-nonconforming people and further perpetuates marginalization and discrimination of these populations. In a world where disparities are increasing, it is paramount to highlight and share the experien
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Coles, Henry C., Taewon Han, Phillip N. Price, Ashok J. Gadgil, and William F. Tschudi. Air Corrosivity in U.S. Outdoor-Air-Cooled Data Centers is Similar to That in Conventional Data Centers. Office of Scientific and Technical Information (OSTI), 2011. http://dx.doi.org/10.2172/1045922.

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Tschudi, William, Tengfang Xu, Dale Sartor, and Jay Stein. High-performance data centers: A research roadmap. Office of Scientific and Technical Information (OSTI), 2004. http://dx.doi.org/10.2172/838173.

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Low, Steven, and Kevin Tang. Power Minimization techniques for Networked Data Centers. Office of Scientific and Technical Information (OSTI), 2011. http://dx.doi.org/10.2172/1025358.

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Bensley, S., D. Thaler, P. Balasubramanian, L. Eggert, and G. Judd. Data Center TCP (DCTCP): TCP Congestion Control for Data Centers. RFC Editor, 2017. http://dx.doi.org/10.17487/rfc8257.

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Berry, Jonathan W., Michael Collins, Aaron Kearns, Cynthia A. Phillips, and Jared Saia. Cyber Graph Queries for Geographically Distributed Data Centers. Office of Scientific and Technical Information (OSTI), 2015. http://dx.doi.org/10.2172/1183059.

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DoD Office of Inspector General. DoDs Efforts to Consolidate Data Centers Need Improvement. Defense Technical Information Center, 2016. http://dx.doi.org/10.21236/ad1016489.

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Mittal, Sparsh. Power Management Techniques for Data Centers: A Survey. Office of Scientific and Technical Information (OSTI), 2014. http://dx.doi.org/10.2172/1150909.

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Previdi, S., G. Dawra, E. Aries, and P. Lapukhov. BGP Prefix Segment in Large-Scale Data Centers. Edited by C. Filsfils. RFC Editor, 2019. http://dx.doi.org/10.17487/rfc8670.

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