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Статті в журналах з теми "Cloud data centers"
Guo, Le Jiang, Feng Zheng, Ya Hui Hu, Lei Xiao, and Liang Liu. "Analysis and Research of Cloud Computing Data Center." Applied Mechanics and Materials 427-429 (September 2013): 2184–87. http://dx.doi.org/10.4028/www.scientific.net/amm.427-429.2184.
Повний текст джерелаSpillner, Josef, and Alan Sill. "Reengineering Cloud Data Centers." IEEE Cloud Computing 5, no. 6 (November 2018): 26–27. http://dx.doi.org/10.1109/mcc.2018.064181117.
Повний текст джерелаKaramat Khan, Tehmina, Mohsin Tanveer, and Asadullah Shah. "Energy Efficiency in Virtualized Data Center." International Journal of Engineering & Technology 7, no. 4.15 (October 7, 2018): 315. http://dx.doi.org/10.14419/ijet.v7i4.15.23019.
Повний текст джерелаRajput, Ravindra Kumar Singh, Dinesh Goyal, Anjali Pant, Gajanand Sharma, Varsha Arya, and Marjan Kuchaki Rafsanjani. "Cloud Data Centre Energy Utilization Estimation." International Journal of Cloud Applications and Computing 12, no. 1 (January 1, 2022): 1–16. http://dx.doi.org/10.4018/ijcac.311035.
Повний текст джерелаDing, Jie, Hai Yun Han, and Ai Hua Zhou. "A Data Placement Strategy for Data-Intensive Cloud Storage." Advanced Materials Research 354-355 (October 2011): 896–900. http://dx.doi.org/10.4028/www.scientific.net/amr.354-355.896.
Повний текст джерелаKhajehei, Kamyab. "Green Cloud and reduction of energy consumption." Computer Engineering and Applications Journal 4, no. 1 (February 18, 2015): 51–60. http://dx.doi.org/10.18495/comengapp.v4i1.119.
Повний текст джерелаShojafar, Mohammad, Zahra Pooranian, Mehdi Sookhak, and Rajkumar Buyya. "Recent advances in cloud data centers toward fog data centers." Concurrency and Computation: Practice and Experience 31, no. 8 (January 30, 2019): e5164. http://dx.doi.org/10.1002/cpe.5164.
Повний текст джерелаLI, YANGYANG, HONGBO WANG, JIANKANG DONG, JUNBO LI, and SHIDUAN CHENG. "Differentiated Bandwidth Guarantees for Cloud Data Centers." Journal of Interconnection Networks 14, no. 03 (September 2013): 1360002. http://dx.doi.org/10.1142/s0219265913600025.
Повний текст джерелаM N, Kavyasri, and Dr Ramesh B. "Key-Cipher-Policy based ABE with Efficient Encryption of Multimedia Data at Data Centers of Cloud." International Journal of Recent Technology and Engineering (IJRTE) 11, no. 1 (May 30, 2022): 73–76. http://dx.doi.org/10.35940/ijrte.c6486.0511122.
Повний текст джерелаBao, Hao. "Homomorphic computing of encrypted data outsourcing in cloud data center." Frontiers in Computing and Intelligent Systems 2, no. 1 (November 23, 2022): 1–3. http://dx.doi.org/10.54097/fcis.v2i1.2482.
Повний текст джерелаДисертації з теми "Cloud data centers"
Mahmud, A. S. M. Hasan. "Sustainable Resource Management for Cloud Data Centers." FIU Digital Commons, 2016. http://digitalcommons.fiu.edu/etd/2634.
Повний текст джерелаJawad, Muhammad. "Energy Efficient Data Centers for On-Demand Cloud Services." Diss., North Dakota State University, 2015. http://hdl.handle.net/10365/25198.
Повний текст джерелаZhang, Gong. "Data and application migration in cloud based data centers --architectures and techniques." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/41078.
Повний текст джерелаPenumetsa, Swetha. "A comparison of energy efficient adaptation algorithms in cloud data centers." Thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-17374.
Повний текст джерелаTakouna, Ibrahim. "Energy-efficient and performance-aware virtual machine management for cloud data centers." Phd thesis, Universität Potsdam, 2014. http://opus.kobv.de/ubp/texte_eingeschraenkt_verlag/2014/7239/.
Повний текст джерелаVirtualized cloud data centers provide on-demand resources, enable agile resource provisioning, and host heterogeneous applications with different resource requirements. These data centers consume enormous amounts of energy, increasing operational expenses, inducing high thermal inside data centers, and raising carbon dioxide emissions. The increase in energy consumption can result from ineffective resource management that causes inefficient resource utilization. This dissertation presents detailed models and novel techniques and algorithms for virtual resource management in cloud data centers. The proposed techniques take into account Service Level Agreements (SLAs) and workload heterogeneity in terms of memory access demand and communication patterns of web applications and High Performance Computing (HPC) applications. To evaluate our proposed techniques, we use simulation and real workload traces of web applications and HPC applications and compare our techniques against the other recently proposed techniques using several performance metrics. The major contributions of this dissertation are the following: proactive resource provisioning technique based on robust optimization to increase the hosts' availability for hosting new VMs while minimizing the idle energy consumption. Additionally, this technique mitigates undesirable changes in the power state of the hosts by which the hosts' reliability can be enhanced in avoiding failure during a power state change. The proposed technique exploits the range-based prediction algorithm for implementing robust optimization, taking into consideration the uncertainty of demand. An adaptive range-based prediction for predicting workload with high fluctuations in the short-term. The range prediction is implemented in two ways: standard deviation and median absolute deviation. The range is changed based on an adaptive confidence window to cope with the workload fluctuations. A robust VM consolidation for efficient energy and performance management to achieve equilibrium between energy and performance trade-offs. Our technique reduces the number of VM migrations compared to recently proposed techniques. This also contributes to a reduction in energy consumption by the network infrastructure. Additionally, our technique reduces SLA violations and the number of power state changes. A generic model for the network of a data center to simulate the communication delay and its impact on VM performance, as well as network energy consumption. In addition, a generic model for a memory-bus of a server, including latency and energy consumption models for different memory frequencies. This allows simulating the memory delay and its influence on VM performance, as well as memory energy consumption. Communication-aware and energy-efficient consolidation for parallel applications to enable the dynamic discovery of communication patterns and reschedule VMs using migration based on the determined communication patterns. A novel dynamic pattern discovery technique is implemented, based on signal processing of network utilization of VMs instead of using the information from the hosts' virtual switches or initiation from VMs. The result shows that our proposed approach reduces the network's average utilization, achieves energy savings due to reducing the number of active switches, and provides better VM performance compared to CPU-based placement. Memory-aware VM consolidation for independent VMs, which exploits the diversity of VMs' memory access to balance memory-bus utilization of hosts. The proposed technique, Memory-bus Load Balancing (MLB), reactively redistributes VMs according to their utilization of a memory-bus using VM migration to improve the performance of the overall system. Furthermore, Dynamic Voltage and Frequency Scaling (DVFS) of the memory and the proposed MLB technique are combined to achieve better energy savings.
Yanggratoke, Rerngvit. "Contributions to Performance Modeling and Management of Data Centers." Licentiate thesis, KTH, Kommunikationsnät, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-129296.
Повний текст джерелаQC 20131001
Peloso, Pietro. "Possibili soluzioni per garantire qos nelle comunicazioni inter-data centers in ambienti cloud computing." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amslaurea.unibo.it/6205/.
Повний текст джерелаAtchukatla, Mahammad suhail. "Algorithms for efficient VM placement in data centers : Cloud Based Design and Performance Analysis." Thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-17221.
Повний текст джерела- Perform simulation of algorithms in CloudSim simulator. Estimate and compare the energy consumption of different packing algorithms. Design an OpenStack testbed to implement the Bin packing algorithm. Methods: We use CloudSim simulator to estimate the energy consumption of the First fit, the First fit decreasing, Best fit and Enhanced best-fit algorithms. Design a heuristic model for implementation in the OpenStack environment for optimizing the energy consumption for the physical machines. Server consolidation and live migration are used for the algorithms design in the OpenStack implementation. Our research also extended to the Nova scheduler functionality in an OpenStack environment. Results: Most of the case the enhanced best-fit algorithm gives the better results. The results are obtained from the default OpenStack VM placement algorithm as well as from the heuristic algorithm developed in this simulation work. The comparison of results indicates that the total energy consumption of the data center is reduced without affecting potential service level agreements. Conclusions: The research tells that energy consumption of the physical machines can be optimized without compromising the offered service quality. A Python wrapper was developed to implement this model in the OpenStack environment and minimize the energy consumption of the Physical machine by shutdown the unused physical machines. The results indicate that CPU Utilization does not vary much when live migration of the virtual machine is performed.
Pipkin, Everest R. "It Was Raining in the Data Center." Research Showcase @ CMU, 2018. http://repository.cmu.edu/theses/138.
Повний текст джерелаBergström, Rasmus. "Predicting Container-Level Power Consumption in Data Centers using Machine Learning Approaches." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-79416.
Повний текст джерелаКниги з теми "Cloud data centers"
K, Kokula Krishna Hari, ed. An Efficient Load Balancing Algorithm for virtualized Cloud Data Centers: ICCCEG 2014. Vietnam: Association of Scientists, Developers and Faculties, 2014.
Знайти повний текст джерелаBeard, Haley. Cloud computing best practices: For managing and measuring processes for on-demand computing, applications and data centers in the cloud with SLAs. Brisbane, Australia: Art of Service, 2008.
Знайти повний текст джерелаMalcolm, Orr, and Page Greg, eds. Cloud computing: Automating the virtualized data center. Indianapolis, IN: Cisco Press, 2012.
Знайти повний текст джерелаZhang, Lei, and Le Chen. Cloud Data Center Network Architectures and Technologies. First edition. | Boca Raton : CRC Press, 2021. | Summary: “This book has: CRC Press, 2021. http://dx.doi.org/10.1201/9781003143185.
Повний текст джерела1960-, Franklin Curtis, ed. Cloud computing: Technologies and strategies of the ubiquitous data center. New York: CRC, 2010.
Знайти повний текст джерелаTsai, Linjiun, and Wanjiun Liao. Virtualized Cloud Data Center Networks: Issues in Resource Management. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32632-0.
Повний текст джерелаChee, Brian J. S. Yun ji suan: Wu chu bu zai de shu ju zhong xin = Cloud computing ; technologies and strategies of the ubiquitous data center. Beijing: Guo fang gong ye chu ban she, 2013.
Знайти повний текст джерелаGreen computing: Tools and techniques for saving energy, money, and resources. Boca Raton: CRC Press, 2014.
Знайти повний текст джерелаCloud Data Centers and Cost Modeling. Elsevier, 2015. http://dx.doi.org/10.1016/c2013-0-23202-5.
Повний текст джерелаBugwadia, Jim, Zeeshan Naseh, and Habib Madani. Transforming Data Centers to Public and Private Cloud. Wiley & Sons, Incorporated, John, 2026.
Знайти повний текст джерелаЧастини книг з теми "Cloud data centers"
Mu, Shuai, Maomeng Su, Pin Gao, Yongwei Wu, Keqin Li, and Albert Y. Zomaya. "Cloud Storage over Multiple Data Centers." In Handbook on Data Centers, 691–725. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-2092-1_24.
Повний текст джерелаJin, Xin, and Yu-Kwong Kwok. "Cloud Resource Pricing Under Tenant Rationality." In Handbook on Data Centers, 583–605. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-2092-1_19.
Повний текст джерелаXiong, Huanhuan, Christos Filelis-Papadopoulos, Dapeng Dong, Gabriel G. Castañé, Stefan Meyer, and John P. Morrison. "Energy-Efficient Servers and Cloud." In Hardware Accelerators in Data Centers, 163–80. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92792-3_9.
Повний текст джерелаAhmed, Kishwar, Shaolei Ren, Yuxiong He, and Athanasios V. Vasilakos. "Online Resource Management for Carbon-Neutral Cloud Computing." In Handbook on Data Centers, 607–30. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-2092-1_20.
Повний текст джерелаBirman, Kenneth P. "The Structure of Cloud Data Centers." In Guide to Reliable Distributed Systems, 145–83. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2416-0_5.
Повний текст джерелаLiu, Bingwei, and Yu Chen. "Auditing for Data Integrity and Reliability in Cloud Storage." In Handbook on Data Centers, 535–59. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-2092-1_17.
Повний текст джерелаXie, Tao, and Haibao Chen. "AutoCSD: Automatic Cloud System Deployment in Data Centers." In Cloud Computing and Big Data, 72–85. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-28430-9_6.
Повний текст джерелаDe Prisco, R., A. De Santis, and M. Mannetta. "Reducing Costs in HSM-Based Data Centers." In Green, Pervasive, and Cloud Computing, 3–14. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-57186-7_1.
Повний текст джерелаKliazovich, Dzmitry, Pascal Bouvry, Fabrizio Granelli, and Nelson L. S. da Fonseca. "Energy Consumption Optimization in Cloud Data Centers." In Cloud Services, Networking, and Management, 191–215. Hoboken, NJ: John Wiley & Sons, Inc, 2015. http://dx.doi.org/10.1002/9781119042655.ch8.
Повний текст джерелаCherkaoui, Omar, and Ramesh Menon. "Virtualization, Cloud, SDN, and SDDC in Data Centers." In Data Center Handbook, 389–400. Hoboken, NJ: John Wiley & Sons, Inc, 2014. http://dx.doi.org/10.1002/9781118937563.ch20.
Повний текст джерелаТези доповідей конференцій з теми "Cloud data centers"
Xu, Jielong, Jian Tang, Kevin Kwiat, Weiyi Zhang, and Guoliang Xue. "Survivable Virtual Infrastructure Mapping in Virtualized Data Centers." In 2012 IEEE 5th International Conference on Cloud Computing (CLOUD). IEEE, 2012. http://dx.doi.org/10.1109/cloud.2012.100.
Повний текст джерелаSalehi, Mohsen Amini, P. Radha Krishna, Krishnamurty Sai Deepak, and Rajkumar Buyya. "Preemption-Aware Energy Management in Virtualized Data Centers." In 2012 IEEE 5th International Conference on Cloud Computing (CLOUD). IEEE, 2012. http://dx.doi.org/10.1109/cloud.2012.147.
Повний текст джерелаZhang, Linquan, Xunrui Yin, Zongpeng Li, and Chuan Wu. "Hierarchical Virtual Machine Placement in Modular Data Centers." In 2015 IEEE 8th International Conference on Cloud Computing (CLOUD). IEEE, 2015. http://dx.doi.org/10.1109/cloud.2015.32.
Повний текст джерелаTian, Wenhong. "Adaptive Dimensioning of Cloud Data Centers." In 2009 International Conference on Dependable, Autonomic and Secure Computing (DASC). IEEE, 2009. http://dx.doi.org/10.1109/dasc.2009.58.
Повний текст джерелаLee, Seungjoon, Manish Purohit, and Barna Saha. "Firewall placement in cloud data centers." In SOCC '13: ACM Symposium on Cloud Computing. New York, NY, USA: ACM, 2013. http://dx.doi.org/10.1145/2523616.2525960.
Повний текст джерелаKarthik, C., Mayank Sharma, Kirti Maurya, and K. Chandrasekaran. "Green intelligence for cloud data centers." In 2016 3rd International Conference on Recent Advances in Information Technology (RAIT). IEEE, 2016. http://dx.doi.org/10.1109/rait.2016.7507965.
Повний текст джерелаMaltz, David A. "Challenges in cloud scale data centers." In the ACM SIGMETRICS/international conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2465529.2465767.
Повний текст джерелаMaswood, Mirza Mohd Shahriar, and Deep Medhi. "Optimal connectivity to cloud data centers." In 2017 IEEE 6th International Conference on Cloud Networking (CloudNet). IEEE, 2017. http://dx.doi.org/10.1109/cloudnet.2017.8071542.
Повний текст джерелаSakamoto, Takumi, Hiroshi Yamada, Hikaru Horie, and Kenji Kono. "Energy-Price-Driven Request Dispatching for Cloud Data Centers." In 2012 IEEE 5th International Conference on Cloud Computing (CLOUD). IEEE, 2012. http://dx.doi.org/10.1109/cloud.2012.115.
Повний текст джерелаHans, Ronny, Ulrich Lampe, and Ralf Steinmetz. "QoS-Aware, Cost-Efficient Selection of Cloud Data Centers." In 2013 IEEE 6th International Conference on Cloud Computing (CLOUD). IEEE, 2013. http://dx.doi.org/10.1109/cloud.2013.113.
Повний текст джерелаЗвіти організацій з теми "Cloud data centers"
Gurieiev, Viktor, Yulii Kutsan, Anna Iatsyshyn, Andrii Iatsyshyn, Valeriia Kovach, Evgen Lysenko, Volodymyr Artemchuk, and Oleksandr Popov. Simulating Systems for Advanced Training and Professional Development of Energy Specialists in Power Sector. [б. в.], November 2020. http://dx.doi.org/10.31812/123456789/4456.
Повний текст джерелаDEFENSE BUSINESS BOARD WASHINGTON DC. DoD Information Technology Modernization: A Recommended Approach to Data Center Consolidation and Cloud Computing. Fort Belvoir, VA: Defense Technical Information Center, January 2012. http://dx.doi.org/10.21236/ada563977.
Повний текст джерела