PVFS: a parallel file system for linux clusters
ALS'00 Proceedings of the 4th annual Linux Showcase & Conference - Volume 4
Grid'5000: A Large Scale And Highly Reconfigurable Experimental Grid Testbed
International Journal of High Performance Computing Applications
Dynamo: amazon's highly available key-value store
Proceedings of twenty-first ACM SIGOPS symposium on Operating systems principles
Ceph: a scalable, high-performance distributed file system
OSDI '06 Proceedings of the 7th symposium on Operating systems design and implementation
Adaptive prefetching algorithm in disk controllers
Performance Evaluation
HPCC '08 Proceedings of the 2008 10th IEEE International Conference on High Performance Computing and Communications
Communications of the ACM
Decision Model for Cloud Computing under SLA Constraints
MASCOTS '10 Proceedings of the 2010 IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems
BlobSeer: Next-generation data management for large scale infrastructures
Journal of Parallel and Distributed Computing
Image Distribution Mechanisms in Large Scale Cloud Providers
CLOUDCOM '10 Proceedings of the 2010 IEEE Second International Conference on Cloud Computing Technology and Science
GPFS: a shared-disk file system for large computing clusters
FAST'02 Proceedings of the 1st USENIX conference on File and storage technologies
Going back and forth: efficient multideployment and multisnapshotting on clouds
Proceedings of the 20th international symposium on High performance distributed computing
BlobCR: Virtual disk based checkpoint-restart for HPC applications on IaaS clouds
Journal of Parallel and Distributed Computing
Scalable virtual machine deployment using VM image caches
SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
Scheduling jobs in the cloud using on-demand and reserved instances
Euro-Par'13 Proceedings of the 19th international conference on Parallel Processing
Leveraging collaborative content exchange for on-demand VM multi-deployments in iaas clouds
Euro-Par'13 Proceedings of the 19th international conference on Parallel Processing
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With Infrastructure-as-a-Service (IaaS) cloud economics getting increasingly complex and dynamic, resource costs can vary greatly over short periods of time. Therefore, a critical issue is the ability to deploy, boot and terminate VMs very quickly, which enables cloud users to exploit elasticity to find the optimal trade-off between the computational needs (number of resources, usage time) and budget constraints. This paper proposes an adaptive prefetching mechanism aiming to reduce the time required to simultaneously boot a large number of VM instances on clouds from the same initial VM image (multi-deployment). Our proposal does not require any foreknowledge of the exact access pattern. It dynamically adapts to it at run time, enabling the slower instances to learn from the experience of the faster ones. Since all booting instances typically access only a small part of the virtual image along almost the same pattern, the required data can be pre-fetched in the background. Large scale experiments under concurrency on hundreds of nodes show that introducing such a prefetching mechanism can achieve a speed-up of up to 35% when compared to simple on-demand fetching.