Resource Allocation and Scheduling in Heterogeneous Cloud Environments
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Summary
A method to predict the job completion time distribution that is applicable to making sophisticated trade-off decisions in resource allocation and scheduling and shows that these methods can improve efficiency and effectiveness of cloud computing systems.
- Type
- article
- Published
- 2012-01-01
- Cited by
- 48
- References
- 86
- OpenAlex
- https://openalex.org/W63594926
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:18487233
Keywords
Cloud computing, Computer science, Resource allocation, Scheduling (production processes), Resource management (computing)
References
- Job Scheduling for Multi-User MapReduce Clusters
- Towards Optimizing Hadoop Provisioning in the Cloud
- The DiskSim Simulation Environment Version 4.0 Reference Manual (CMU-PDL-08-101)
- Delivering Energy Proportionality with Non Energy-Proportional Systems - Optimizing the Ensemble
- CLUEBOX: A Performance Log Analyzer for Automated Troubleshooting
- Black-box and Gray-box Strategies for Virtual Machine Migration
- SPAIN: COTS Data-Center Ethernet for Multipathing over Arbitrary Topologies
- SALSA: Analyzing Logs as StAte Machines
- Hadoop: The Definitive Guide
- Starfish: A Self-tuning System for Big Data Analytics
- Improving MapReduce performance in heterogeneous environments
- Dynamic matching and scheduling of a class of independent tasks onto heterogeneous computing systems
- pathChirp: Efficient available bandwidth estimation for network paths
- Analyzing Market-Based Resource Allocation Strategies for the Computational Grid
- Experimental study of large-scale computing on virtualized resources
- Communication-Aware Job Placement Policies for the KOALA Grid Scheduler
- On the Price of Heterogeneity in Parallel Systems
- An Analysis of Preemptive Multiprocessor Job Scheduling
- Service Level Agreement based Allocation of Cluster Resources: Handling Penalty to Enhance Utility
- Data Intensive and Network Aware (DIANA) Grid Scheduling
Cited by
- Improving MapReduce Performance on Clusters. (Amélioration des performances de MapReduce sur grappe de calcul)
- The Research on Data-Intensive Resource Scheduling in Intelligence Processing
- Timing of Resources in Cloud Computing by using Multi-Purpose Particles Congestion Algorithm
- Delay-Sensitive Service Request Scheduling for Cloud Computing
- The Use of Locality Information on Data Intensive Parallel File Systems
- Multiobjective Virtual Machine Placement in Cloud Environment
- System resource utilization analysis and prediction for cloud based applications under bursty workloads
- An Upgraded Algorithm of Resource Scheduling using PSO and SA in Cloud Computing
- Cost and deadline optimization along with resource allocation in cloud computing environment
- FRP: a fast resource placement algorithm in distributed cloud computing platform
- Ontology-based Cloud Services Representation
- Weight based Budget Distribution (WBD) , a budget constrained scheduling algorithm for workflows in cloud
- Job Classification in Cloud Computing: The Classification Effects on Energy Efficiency
- User Annotated Resource Allocation in Cloud Computing Environment
- Towards Solving the Problem of Virtual Machine Placement in Cloud Computing: A Job Classification Approach
- Resource Management and Scheduling in Cloud Environment
- Efficient distributed algorithm for scheduling workload-aware jobs on multi-clouds
- Scheduling Tasks in the Cloud Computing Environment with the Effect of Cuckoo Optimization Algorithm
- An approach for profiling distributed applications through network traffic analysis
- Cost performance analysis: Usage of resources in cloud using Markov-chain model
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