Resource allocation in a Cloud partially powered by renewable energy sources. (Allocation de ressources dans un Cloud partiellement alimenté par des sources d'énergie renouvelable)
暂无分享,去创建一个
[1] Gang Qu,et al. Approaching the Maximum Energy Saving on Embedded Systems with Multiple Voltages , 2003, ICCAD 2003.
[2] Wolf-Dietrich Weber,et al. Power provisioning for a warehouse-sized computer , 2007, ISCA '07.
[3] Cristian Mateos,et al. Dynamic Scheduling based on Particle Swarm Optimization for Cloud-based Scientific Experiments , 2014, CLEI Electron. J..
[4] Ioannis Tomkos,et al. A Survey on Optical Interconnects for Data Centers , 2012, IEEE Communications Surveys & Tutorials.
[5] Jordi Torres,et al. GreenSlot: Scheduling energy consumption in green datacenters , 2011, 2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC).
[6] Mahadev Satyanarayanan,et al. The Emergence of Edge Computing , 2017, Computer.
[7] Laurent Lefèvre,et al. Save Watts in Your Grid: Green Strategies for Energy-Aware Framework in Large Scale Distributed Systems , 2008, 2008 14th IEEE International Conference on Parallel and Distributed Systems.
[8] Eric Bouillet,et al. Efficient resource provisioning in compute clouds via VM multiplexing , 2010, ICAC '10.
[9] Weisong Shi,et al. FlexFetch: A History-Aware Scheme for I/O Energy Saving in Mobile Computing , 2007, 2007 International Conference on Parallel Processing (ICPP 2007).
[10] Shigeo Abe DrEng. Pattern Classification , 2001, Springer London.
[11] Yuping Wang,et al. Energy-Efficient Multi-Job Scheduling Model for Cloud Computing and Its Genetic Algorithm , 2012 .
[12] Sanjeev Khanna,et al. On multi-dimensional packing problems , 2004, SODA '99.
[13] Tansu Alpcan,et al. Fog Computing May Help to Save Energy in Cloud Computing , 2016, IEEE Journal on Selected Areas in Communications.
[14] Laurent Lefèvre,et al. Towards Generalizing "Big Little" for Energy Proportional HPC and Cloud Infrastructures , 2014, 2014 IEEE Fourth International Conference on Big Data and Cloud Computing.
[15] Lachlan L. H. Andrew,et al. Dynamic Right-Sizing for Power-Proportional Data Centers , 2011, IEEE/ACM Transactions on Networking.
[16] Mohsen Guizani,et al. Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications , 2015, IEEE Communications Surveys & Tutorials.
[17] Rajkumar Buyya,et al. Adaptive threshold-based approach for energy-efficient consolidation of virtual machines in cloud data centers , 2010, MGC '10.
[18] Yoram Singer,et al. Improved Boosting Algorithms Using Confidence-rated Predictions , 1998, COLT' 98.
[19] Manish Parashar,et al. Enabling autonomic computing on federated advanced cyberinfrastructures , 2013, CAC.
[20] Christopher Stewart,et al. Some Joules Are More Precious Than Others: Managing Renewable Energy in the Datacenter∗ , 2009 .
[21] Jordi Torres,et al. GreenHadoop: leveraging green energy in data-processing frameworks , 2012, EuroSys '12.
[22] Arif Merchant,et al. Flash Reliability in Production: The Expected and the Unexpected , 2016, FAST.
[23] Jean-Marc Menaud,et al. Estimating the Power Consumption of an Idle Virtual Machine , 2013, 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing.
[24] Lachlan L. H. Andrew,et al. Greening Geographical Load Balancing , 2015, IEEE/ACM Transactions on Networking.
[25] Jean-Marc Pierson,et al. Spatio-temporal thermal-aware scheduling for homogeneous high-performance computing datacenters , 2017, Future Gener. Comput. Syst..
[26] Albert Y. Zomaya,et al. A Taxonomy and Survey of Energy-Efficient Data Centers and Cloud Computing Systems , 2010, Adv. Comput..
[27] THE CARBON EMISSIONS OF SERVER COMPUTING FOR SMALL- TO MEDIUM-SIZED ORGANIZATIONS , 2012 .
[28] Yacine Rezgui,et al. In-Transit Data Analysis and Distribution in a Multi-cloud Environment Using CometCloud , 2014, 2014 International Conference on Future Internet of Things and Cloud.
[29] Mahadev Satyanarayanan,et al. Scalable crowd-sourcing of video from mobile devices , 2013, MobiSys '13.
[30] M. Yue. A simple proof of the inequality FFD (L) ≤ 11/9 OPT (L) + 1, ∀L for the FFD bin-packing algorithm , 1991 .
[31] Laurent Lefèvre,et al. "Big, Medium, Little": Reaching Energy Proportionality with Heterogeneous Computing Scheduler , 2015, Parallel Process. Lett..
[32] Barry O'Sullivan,et al. Trends in Constraint Programming , 2007 .
[33] Thu D. Nguyen,et al. Providing green SLAs in High Performance Computing clouds , 2013, 2013 International Green Computing Conference Proceedings.
[34] TangMaolin,et al. A Hybrid Genetic Algorithm for the Energy-Efficient Virtual Machine Placement Problem in Data Centers , 2015 .
[35] Florin Ciucu,et al. A Stochastic Power Network Calculus for Integrating Renewable Energy Sources into the Power Grid , 2012, IEEE Journal on Selected Areas in Communications.
[36] Hiroto Yasuura,et al. Voltage scheduling problem for dynamically variable voltage processors , 1998, Proceedings. 1998 International Symposium on Low Power Electronics and Design (IEEE Cat. No.98TH8379).
[37] Martin Bichler,et al. A Mathematical Programming Approach for Server Consolidation Problems in Virtualized Data Centers , 2010, IEEE Transactions on Services Computing.
[38] Toyotaro Suzumura,et al. Elastic Stream Computing with Clouds , 2011, 2011 IEEE 4th International Conference on Cloud Computing.
[39] Giuseppe Serazzi,et al. Stochastic Analysis of Energy Consumption in Pool Depletion Systems , 2016, MMB/DFT.
[40] Peter Kilpatrick,et al. Challenges and Opportunities in Edge Computing , 2016, 2016 IEEE International Conference on Smart Cloud (SmartCloud).
[41] Thomas Ledoux,et al. Towards energy-proportional clouds partially powered by renewable energy , 2016, Computing.
[42] Shangguang Wang,et al. An overview of Internet of Vehicles , 2014, China Communications.
[43] Wentong Cai,et al. Dynamic Bin Packing for On-Demand Cloud Resource Allocation , 2016, IEEE Transactions on Parallel and Distributed Systems.
[44] Philippe Gravey,et al. 112-Gbit/s Passive Optical Pod Interconnect for small data centers using Pulse Amplitude Modulation , 2016, 2016 International Conference on Optical Network Design and Modeling (ONDM).
[45] Dan Xu,et al. Geographic trough filling for internet datacenters , 2011, 2012 Proceedings IEEE INFOCOM.
[46] Christian Belady,et al. GREEN GRID DATA CENTER POWER EFFICIENCY METRICS: PUE AND DCIE , 2008 .
[47] M. Savoie,et al. Converged Optical Network Infrastructures in Support of Future Internet and Grid Services Using IaaS to Reduce GHG Emissions , 2009, Journal of Lightwave Technology.
[48] Luis Rodero-Merino,et al. Finding your Way in the Fog: Towards a Comprehensive Definition of Fog Computing , 2014, CCRV.
[49] Gang Quan,et al. Energy efficient fixed-priority scheduling for real-time systems on variable voltage processors , 2001, DAC '01.
[50] Martin Bichler,et al. Capacity Planning for Virtualized Servers , 2007 .
[51] Mohsen Guizani,et al. Toward energy-efficient cloud computing: Prediction, consolidation, and overcommitment , 2015, IEEE Network.
[52] Bu-Sung Lee,et al. Optimal Power Management for Server Farm to Support Green Computing , 2009, 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid.
[53] Ohad Shamir,et al. On-demand, Spot, or Both: Dynamic Resource Allocation for Executing Batch Jobs in the Cloud , 2014, ICAC.
[54] Emmanuel Jeannot,et al. Adding Virtualization Capabilities to the Grid'5000 Testbed , 2012, CLOSER.
[55] Gargi Dasgupta,et al. Server Workload Analysis for Power Minimization using Consolidation , 2009, USENIX Annual Technical Conference.
[56] Athanasios V. Vasilakos,et al. Thermal-Aware Scheduling of Batch Jobs in Geographically Distributed Data Centers , 2014, IEEE Transactions on Cloud Computing.
[57] Yuan Yao,et al. Data centers power reduction: A two time scale approach for delay tolerant workloads , 2012, 2012 Proceedings IEEE INFOCOM.
[58] L. Benini,et al. System-level dynamic power management , 1999, Proceedings IEEE Alessandro Volta Memorial Workshop on Low-Power Design.
[59] Bu-Sung Lee,et al. Optimal virtual machine placement across multiple cloud providers , 2009, 2009 IEEE Asia-Pacific Services Computing Conference (APSCC).
[60] Yanpei Chen,et al. Integrating Renewable Energy Using Data Analytics Systems: Challenges and Opportunities , 2011, IEEE Data Eng. Bull..
[61] Yanpei Chen,et al. An information-centric energy infrastructure: The Berkeley view , 2011, Sustain. Comput. Informatics Syst..
[62] Toby Walsh,et al. Handbook of Constraint Programming , 2006, Handbook of Constraint Programming.
[63] Jean-Marc Menaud,et al. Leveraging Renewable Energy in Edge Clouds for Data Stream Analysis in IoT , 2017, 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID).
[64] Sergiu Nedevschi,et al. Reducing Network Energy Consumption via Sleeping and Rate-Adaptation , 2008, NSDI.
[65] Laurent Lefèvre,et al. A survey on techniques for improving the energy efficiency of large-scale distributed systems , 2014, ACM Comput. Surv..
[66] Rajkumar Buyya,et al. Energy and Carbon-Efficient Placement of Virtual Machines in Distributed Cloud Data Centers , 2013, Euro-Par.
[67] Albert Y. Zomaya,et al. Some observations on optimal frequency selection in DVFS-based energy consumption minimization , 2011, J. Parallel Distributed Comput..
[68] Vijay K. Naik,et al. Biting Off Safely More Than You Can Chew: Predictive Analytics for Resource Over-Commit in IaaS Cloud , 2012, 2012 IEEE Fifth International Conference on Cloud Computing.
[69] Samuli Aalto,et al. Energy-Aware Server with SRPT Scheduling: Analysis and Optimization , 2016, QEST.
[70] Xiangliang Zhang,et al. Virtual machine migration in an over-committed cloud , 2012, 2012 IEEE Network Operations and Management Symposium.
[71] F. Frances Yao,et al. A scheduling model for reduced CPU energy , 1995, Proceedings of IEEE 36th Annual Foundations of Computer Science.
[72] Luiz André Barroso,et al. The Case for Energy-Proportional Computing , 2007, Computer.
[73] Anand Sivasubramaniam,et al. Energy storage in datacenters: what, where, and how much? , 2012, SIGMETRICS '12.
[74] Marvin Theimer,et al. Preemptable remote execution facilities for the V-system , 1985, SOSP '85.
[75] Catherine Rosenberg,et al. Toward a Realistic Performance Analysis of Storage Systems in Smart Grids , 2015, IEEE Transactions on Smart Grid.
[76] Wei Li,et al. Energy-Efficient Virtual Machine Placement in Data Centers by Genetic Algorithm , 2012, ICONIP.
[77] Haisheng Chen,et al. Progress in electrical energy storage system: A critical review , 2009 .
[78] Rajkumar Buyya,et al. Energy Efficient Resource Management in Virtualized Cloud Data Centers , 2010, 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing.
[79] Muli Ben-Yehuda,et al. Ginkgo : Automated , Application-Driven Memory Overcommitment for Cloud Computing , 2011 .
[80] Bill Tschudi,et al. ERE: A METRIC FOR MEASURING THE BENEFIT OF REUSE ENERGY FROM A DATA CENTER , 2010 .
[81] Chia-Ming Wu,et al. A green energy-efficient scheduling algorithm using the DVFS technique for cloud datacenters , 2014, Future Gener. Comput. Syst..
[82] Xue Liu,et al. Coordinated Energy Cost Management of Distributed Internet Data Centers in Smart Grid , 2012, IEEE Transactions on Smart Grid.
[83] Andrew Warfield,et al. Live migration of virtual machines , 2005, NSDI.
[84] Xavier Lorca,et al. Entropy: a consolidation manager for clusters , 2009, VEE '09.
[85] Khaled Ben Letaief,et al. Dynamic Computation Offloading for Mobile-Edge Computing With Energy Harvesting Devices , 2016, IEEE Journal on Selected Areas in Communications.
[86] Mohsen Guizani,et al. Efficient datacenter resource utilization through cloud resource overcommitment , 2015, 2015 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).
[87] Antonio Luque,et al. Handbook of photovoltaic science and engineering , 2011 .
[88] Albert Y. Zomaya,et al. Linear Combinations of DVFS-Enabled Processor Frequencies to Modify the Energy-Aware Scheduling Algorithms , 2010, 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing.
[89] Richard E. Brown,et al. United States Data Center Energy Usage Report , 2016 .
[90] Thomas F. Wenisch,et al. PowerNap: eliminating server idle power , 2009, ASPLOS.
[91] Thu D. Nguyen,et al. Parasol and GreenSwitch: managing datacenters powered by renewable energy , 2013, ASPLOS '13.
[92] Jean-Marc Menaud,et al. Balancing the Use of Batteries and Opportunistic Scheduling Policies for Maximizing Renewable Energy Consumption in a Cloud Data Center , 2017, 2017 25th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP).
[93] Allan Borodin,et al. Online computation and competitive analysis , 1998 .
[94] Umesh Deshpande,et al. Inter-rack live migration of multiple virtual machines , 2012, VTDC '12.
[95] Xiaorui Wang,et al. Server-Level Power Control , 2007, Fourth International Conference on Autonomic Computing (ICAC'07).
[96] Martin Suchara,et al. Greening backbone networks: reducing energy consumption by shutting off cables in bundled links , 2010, Green Networking '10.
[97] Yuguang Fang,et al. Cutting Down Electricity Cost in Internet Data Centers by Using Energy Storage , 2011, 2011 IEEE Global Telecommunications Conference - GLOBECOM 2011.
[98] Ravi Sunil,et al. ENABLING SMART CLOUD SERVICES THROUGH REMOTE SENSING: AN INTERNET OF EVERYTHING ENABLER , 2015 .
[99] Wentong Cai,et al. On dynamic bin packing for resource allocation in the cloud , 2014, SPAA.
[100] Jihong Kim,et al. Power-Aware Resource Management Techniques for Low-Power Embedded Systems , 2007, Handbook of Real-Time and Embedded Systems.
[101] Mor Harchol-Balter,et al. Optimal power allocation in server farms , 2009, SIGMETRICS '09.
[102] Yefu Wang,et al. GreenWare: Greening Cloud-Scale Data Centers to Maximize the Use of Renewable Energy , 2011, Middleware.
[103] Enzo Baccarelli,et al. Energy-efficient dynamic traffic offloading and reconfiguration of networked data centers for big data stream mobile computing: review, challenges, and a case study , 2016, IEEE Network.
[104] Nick Antonopoulos,et al. Video Stream Analysis in Clouds: An Object Detection and Classification Framework for High Performance Video Analytics , 2019, IEEE Transactions on Cloud Computing.
[105] Roi Blanco,et al. Exploiting Green Energy to Reduce the Operational Costs of Multi-Center Web Search Engines , 2016, WWW.
[106] Jaume Salom,et al. Energy-efficient, thermal-aware modeling and simulation of data centers: The CoolEmAll approach and evaluation results , 2015, Ad Hoc Networks.
[107] Alec Brooks,et al. Demand Dispatch - Using Real-Time Control of Demand to help Balance Generation and Load , 2010 .
[108] Christine Morin,et al. Energy-Aware Ant Colony Based Workload Placement in Clouds , 2011, 2011 IEEE/ACM 12th International Conference on Grid Computing.
[109] Wentong Cai,et al. Competitiveness of Dynamic Bin Packing for Online Cloud Server Allocation , 2017, IEEE/ACM Transactions on Networking.
[110] Meeta Sharma Gupta,et al. System level analysis of fast, per-core DVFS using on-chip switching regulators , 2008, 2008 IEEE 14th International Symposium on High Performance Computer Architecture.
[111] Prashant J. Shenoy,et al. Cloudy Computing: Leveraging Weather Forecasts in Energy Harvesting Sensor Systems , 2010, 2010 7th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON).
[112] Paul A. Viola,et al. Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.
[113] Gilles Fedak,et al. Beyond The Cloud, How Should Next Generation Utility Computing Infrastructures Be Designed? , 2013 .
[114] Bingsheng He,et al. Green-aware workload scheduling in geographically distributed data centers , 2012, 4th IEEE International Conference on Cloud Computing Technology and Science Proceedings.
[115] K. C. Divya,et al. Battery Energy Storage Technology for power systems-An overview , 2009 .
[116] Chong Luo,et al. Multimedia Cloud Computing , 2011, IEEE Signal Processing Magazine.
[117] Jean-Marc Menaud,et al. Opportunistic Scheduling in Clouds Partially Powered by Green Energy , 2015, 2015 IEEE International Conference on Data Science and Data Intensive Systems.
[118] Qiang Huang,et al. Power Consumption of Virtual Machine Live Migration in Clouds , 2011, 2011 Third International Conference on Communications and Mobile Computing.