Mehta et al., 2011 - Google Patents
Energy conservation in cloud infrastructuresMehta et al., 2011
View PDF- Document ID
- 6031942899733122824
- Author
- Mehta A
- Menaria M
- Dangi S
- Rao S
- Publication year
- Publication venue
- 2011 IEEE International Systems Conference
External Links
Snippet
With the growth of cloud computing, large scale data centers have become common in the computing industry, and there has been a significant increase in energy consumption at these data centers, which thus becomes a key issue to address. As most of the time a data …
- 238000004134 energy conservation 0 title abstract description 8
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for programme control, e.g. control unit
- G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
- G06F9/46—Multiprogramming arrangements
- G06F9/48—Programme initiating; Programme switching, e.g. by interrupt
- G06F9/4806—Task transfer initiation or dispatching
- G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
- G06F9/4881—Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for programme control, e.g. control unit
- G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5061—Partitioning or combining of resources
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for programme control, e.g. control unit
- G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5083—Techniques for rebalancing the load in a distributed system
- G06F9/5088—Techniques for rebalancing the load in a distributed system involving task migration
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for programme control, e.g. control unit
- G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
- G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
- G06F9/505—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals considering the load
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F1/00—Details of data-processing equipment not covered by groups G06F3/00 - G06F13/00, e.g. cooling, packaging or power supply specially adapted for computer application
- G06F1/26—Power supply means, e.g. regulation thereof
- G06F1/32—Means for saving power
- G06F1/3203—Power Management, i.e. event-based initiation of power-saving mode
- G06F1/3234—Action, measure or step performed to reduce power consumption
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for programme control, e.g. control unit
- G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5094—Allocation of resources, e.g. of the central processing unit [CPU] where the allocation takes into account power or heat criteria
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F1/00—Details of data-processing equipment not covered by groups G06F3/00 - G06F13/00, e.g. cooling, packaging or power supply specially adapted for computer application
- G06F1/26—Power supply means, e.g. regulation thereof
- G06F1/32—Means for saving power
- G06F1/3203—Power Management, i.e. event-based initiation of power-saving mode
- G06F1/3206—Monitoring a parameter, a device or an event triggering a change in power modality
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation; Recording or statistical evaluation of user activity, e.g. usability assessment
- G06F11/3409—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation; Recording or statistical evaluation of user activity, e.g. usability assessment for performance assessment
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Huang et al. | SSUR: an approach to optimizing virtual machine allocation strategy based on user requirements for cloud data center | |
| Askarizade Haghighi et al. | An energy-efficient dynamic resource management approach based on clustering and meta-heuristic algorithms in cloud computing IaaS platforms: Energy efficient dynamic cloud resource management | |
| Mastroianni et al. | Probabilistic consolidation of virtual machines in self-organizing cloud data centers | |
| Vakilinia et al. | Energy efficient resource allocation in cloud computing environments | |
| Farahnakian et al. | LiRCUP: Linear regression based CPU usage prediction algorithm for live migration of virtual machines in data centers | |
| Singh et al. | A comprehensive review of cloud computing virtual machine consolidation | |
| Li et al. | Opportunistic scheduling in clouds partially powered by green energy | |
| Gaggero et al. | Predictive control for energy-aware consolidation in cloud datacenters | |
| Sharkh et al. | An evergreen cloud: Optimizing energy efficiency in heterogeneous cloud computing architectures | |
| Rahmani et al. | Burst‐aware virtual machine migration for improving performance in the cloud | |
| Tarahomi et al. | A prediction‐based and power‐aware virtual machine allocation algorithm in three‐tier cloud data centers | |
| Garg et al. | Energy efficient virtual machine migration approach with SLA conservation in cloud computing | |
| Kulkarni et al. | Context aware VM placement optimization technique for heterogeneous IaaS cloud | |
| Zhou et al. | An experience-based scheme for energy-SLA balance in cloud data centers | |
| Farahnakian et al. | Multi-agent based architecture for dynamic VM consolidation in cloud data centers | |
| Ismaeel et al. | Energy-consumption clustering in cloud data centre | |
| Mehta et al. | Energy conservation in cloud infrastructures | |
| Canon et al. | Assessing power needs to run a workload with quality of service on green datacenters | |
| Wang et al. | In stechah: An autoscaling scheme for hadoop in the private cloud | |
| Daoud et al. | [Retracted] Cloud‐IoT Resource Management Based on Artificial Intelligence for Energy Reduction | |
| Alsadie et al. | Life: A predictive approach for vm placement in cloud environments | |
| Carrega et al. | Energy-aware consolidation scheme for data center cloud applications | |
| Raj et al. | Power aware provisioning in cloud computing environment | |
| Santana et al. | Power management by load forecasting in web server clusters | |
| Aschberger et al. | Energy efficiency in cloud computing |