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Towards energy-aware scheduling in data centers using machine learning

Josep Ll. Berral, Íñigo Goiri, Ramón Nou, Ferran Julià, Jordi Guitart, Ricard Gavaldà, Jordi Torres
2010 Proceedings of the 1st International Conference on Energy-Efficient Computing and Networking - e-Energy '10  
As energy-related costs have become a major economical factor for IT infrastructures and data-centers, companies and the research community are being challenged to find better and more efficient power-aware  ...  There is a growing interest in "Green" IT and there is still a big gap in this area to be covered.  ...  In order to obtain an energy-efficient data center, we propose a framework that provides an intelligent consolidation methodology using different techniques such as turning on/off machines, power-aware  ... 
doi:10.1145/1791314.1791349 dblp:conf/eenergy/BerralGNJGGT10 fatcat:wb65jkzg4fhejh3ljqcpcvmj4u

2021 Index IEEE Transactions on Parallel and Distributed Systems Vol. 32

2022 IEEE Transactions on Parallel and Distributed Systems  
., +, TPDS July 2021 1578-1590 Network-Aware Locality Scheduling for Distributed Data Operators in Data Centers.  ...  GML: Efficiently Auto-Tuning Flink's Configurations Via Guided Machine Learning. Guo, Y., +, TPDS Dec. 2021 2921-2935 Network-Aware Locality Scheduling for Distributed Data Operators in Data Centers.  ... 
doi:10.1109/tpds.2021.3107121 fatcat:e7bh2xssazdrjcpgn64mqh4hb4

Detailed author index

2007 2007 IEEE International Conference on Cluster Computing  
in Data Centers Tang, Qinghui 129 Thermal-Aware Task Scheduling for Data Centers Through Minimizing Heat Recirculation Tikotekar, Anand 303 Evaluation of Fault-Tolerant Policies Using Simulation  ...  System-Level Migration of PGAS Applications Using Xen on InfiniBand Nikolopoulos, Dimitrios S. 488 Identifying Energy-Efficient Concurrency Levels Using Machine Learning Nomura, Akihiro 194  ... 
doi:10.1109/clustr.2007.4629206 fatcat:dsvfpa7uffc75e4iotlu2vjrqe

Toward Energy-Aware Scheduling Using Machine Learning [chapter]

Josep Ll. Berral, Iñigo Goiri, Ramon Nou, Ferran Julià, Josep O. Fitó, Jordi Guitart, Ricard Gavaldá, Jordi Torres
2012 Energy-Efficient Distributed Computing Systems  
It demonstrates how turning on and off machines in a dynamic way can be used to dramatically increase the energy efficiency in a consolidated data center.  ...  There are several useful works on machine learning and data mining awaiting to be applied in cloud and data-center management situations, and there are many works in self-management awaiting to be improved  ... 
doi:10.1002/9781118342015.ch8 fatcat:mtzomhmp5rcyxol4q6zwipvt7a

2020 Index IEEE Transactions on Parallel and Distributed Systems Vol. 31

2021 IEEE Transactions on Parallel and Distributed Systems  
., +, TPDS March 2019 515-529 Distributed Bottleneck-Aware Coflow Scheduling in Data Centers.  ...  ., +, TPDS Nov. 2019 2536- 2546 Distributed Bottleneck-Aware Coflow Scheduling in Data Centers.  ... 
doi:10.1109/tpds.2020.3033655 fatcat:cpeatdjlpzhqdersvsk5nmzjkm

2019 Index IEEE Transactions on Network and Service Management Vol. 16

2019 IEEE Transactions on Network and Service Management  
., +, T-NSM Sept. 2019 965-979 Ismael: Using Machine Learning to Predict Acceptance of Virtual Clusters in Data Centers.  ...  ., +, T-NSM Sept. 2019 924-935 Ismael: Using Machine Learning to Predict Acceptance of Virtual Clusters in Data Centers.  ...  Stochastic programming Tiered Cloud Storage via Two-Stage, Latency-Aware Bidding. Zhang  ... 
doi:10.1109/tnsm.2019.2960621 fatcat:zdo7i4plobaqxp54v7624wkrxi

2020 Index IEEE Transactions on Cloud Computing Vol. 8

2021 IEEE Transactions on Cloud Computing  
-March 2020 4-16 Energy Efficient Scheduling of Servers with Multi-Sleep Modes for Cloud Data Center.  ...  -Dec. 2020 1054-1068 Online VM Auto-Scaling Algorithms for Application Hosting in a Cloud. Predicting Workflow Task Execution Time in the Cloud Using A Two-Stage Machine Learning Approach.  ...  Frequency control Performance-Based Pricing in Multi-Core Geo-Distributed Cloud Computing. Lucanin, D., +, TCC Oct.-Dec. 2020  ... 
doi:10.1109/tcc.2021.3055041 fatcat:nppinqsievad3gr42ppehwp7yi

Study of Energy Efficient Algorithms for Cloud Computing based on Virtual Machine Migration Techniques

Santanu Kumar Sen, Sharmistha Dey, Rajib Bag
2019 International Journal of Machine Learning and Networked Collaborative Engineering  
data centers.  ...  One feasible solution for achieving energy efficiency is Virtual Machine migration technique in real time or when they are in turned off condition.  ...  (May, 2014) by using DVFS technique for making energy efficiency for real time data in cloud data centers.  ... 
doi:10.30991/ijmlnce.2019v03i02.003 fatcat:sj7jwtcdgzf2haswyvg7lfsbua

2019 Index IEEE Transactions on Cloud Computing Vol. 7

2020 IEEE Transactions on Cloud Computing  
-Dec. 2019 949-963 Contracts Energy-Aware VM Consolidation in Cloud Data Centers Using Utilization Prediction Model.  ...  ., +, TCC July-Sept. 2019 733-743 Energy-Aware VM Consolidation in Cloud Data Centers Using Utilization Prediction Model.  ... 
doi:10.1109/tcc.2020.2969066 fatcat:uxhqc6ryenen7brk6qnejnciaa

Adaptive Scheduling on Power-Aware Managed Data-Centers Using Machine Learning

Josep Ll. Berral, Ricard Gavalda, Jordi Torres
2011 2011 IEEE/ACM 12th International Conference on Grid Computing  
Energy-related costs have become one of the major economic factors in IT data-centers, and companies and the research community are currently working on new efficient poweraware resource management strategies  ...  The machine learning is used to estimate the initially unknown parameters of the mathematical model.  ...  ACKNOWLEDGMENT We would like to thank toÍñigo Goiri, Ferran Julià, Ramon Nou, J.Oriol Fitó and Jordi Guitart from UPC-BSC for lending us their testbed workbench in order to evaluate our methods.  ... 
doi:10.1109/grid.2011.18 dblp:conf/grid/BerralGT11 fatcat:mwb4opxhaveythjaae7vg4l3ve

Thermal Prediction for Efficient Energy Management of Clouds using Machine Learning [article]

Shashikant Ilager, Kotagiri Ramamohanarao, Rajkumar Buyya
2020 arXiv   pre-print
Temperature estimation is a non-trivial problem due to thermal variations in the data center.  ...  However, data-driven machine learning methods for temperature prediction is a promising approach.  ...  ACKNOWLEDGMENTS We thank Bernard Meade and Justin Mammarella at Research Platform Services, The University of Melbourne for their support and providing access to the infrastructure 13 cloud and data.  ... 
arXiv:2011.03649v3 fatcat:kvyikdiisvan5kgjshdttoullu

Energy-Aware Scheduling of Distributed Systems

Pragati Agrawal, Shrisha Rao
2014 IEEE Transactions on Automation Science and Engineering  
Index Terms-Cellular automata (CA), distributed systems, energy-aware scheduling, genetic algorithms (GA), learning algorithms, machine learning, makespan.  ...  Note to Practitioners-In today's world of large systems and energy shortages, the need for energy efficiency in individual machines is complemented by the need for energy awareness in the use of the complete  ...  It is well known that energy-aware scheduling is of practical interest in data centers [9] - [11] , chip-level scheduling [12] - [14] , and grid computing [15] - [18] .  ... 
doi:10.1109/tase.2014.2308955 fatcat:jvgsqekpevh7dpi5cutabakjki

Strategies for Increased Energy Awareness in Cloud Federations [chapter]

Gabor Kecskemeti, Attila Kertesz, Attila Cs. Marosi, Zsolt Nemeth
2014 High-Performance Computing on Complex Environments  
Regarding energy efficiency in a single cloud, Cioara et al. in [2] introduced an energy-aware scheduling policy to consolidate power management by using reinforcement learning techniques to bring back  ...  [12] present a framework to address energy efficiency using an intelligent consolidation methodology, which applies various techniques such as machine learning on scheduling algorithms to improve server  ... 
doi:10.1002/9781118711897.ch19 fatcat:5bor6vbbrba2fose263aw5hfhy

RESOURCE SCHEDULING IN CLOUD ENVIRONMET: A SURVEY

Neeraj Mangla, Manpreet Singh, Sanjeev Rana
2016 Advances in Science and Technology Research Journal  
With its growing application and popularization, IT companies are rapidly deploying distributed data centers globally, posing numerous challenges in terms of scheduling of resources under different administrative  ...  A comparative analysis of various resource scheduling techniques focusing on key performance parameters like Energy efficiency, Virtual Machine allocation and migration, Cost-effectiveness and Service-Level  ...  VMs in data center nodes and maximizing the provider's profit.  ... 
doi:10.12913/22998624/62746 fatcat:dyky2j5kxbaulllhmtcidt6cjm

2020 Index IEEE Transactions on Services Computing Vol. 13

2021 IEEE Transactions on Services Computing  
., +, TSC July-Aug. 2020 602-612 Towards Service Composition Aware Virtual Machine Migration Approach in the Cloud.  ...  ., +, TSC July-Aug. 2020 745-758 Towards Service Composition Aware Virtual Machine Migration Approach in the Cloud.  ... 
doi:10.1109/tsc.2021.3055723 fatcat:eumbihmezvehxdfbmlp6ufzkwe
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