Fast runtime block cyclic data redistribution on multiprocessors
Journal of Parallel and Distributed Computing
A Generalized Basic-Cycle Calculation Method for Efficient Array Redistribution
IEEE Transactions on Parallel and Distributed Systems
Optimal Placement of Replicas in Trees with Read, Write, and Storage Costs
IEEE Transactions on Parallel and Distributed Systems
Scheduling GEN_BLOCK Array Redistribution
The Journal of Supercomputing
Symbolic Communication Set Generation for Irregular Parallel Applications
The Journal of Supercomputing
A Divide-and-Conquer Algorithm for Irregular Redistribution in Parallelizing Compilers
The Journal of Supercomputing
On the Optimal Placement of Secure Data Objects over Internet
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
An MPI prototype for compiled communication on Ethernet switched clusters
Journal of Parallel and Distributed Computing - Special issue: Design and performance of networks for super-, cluster-, and grid-computing: Part I
Messages Scheduling for Parallel Data Redistribution between Clusters
IEEE Transactions on Parallel and Distributed Systems
IEEE Transactions on Parallel and Distributed Systems
Message Scheduling for Irregular Data Redistribution in Parallelizing Compilers
IEICE - Transactions on Information and Systems
MJSA: Markov job scheduler based on availability in desktop grid computing environment
Future Generation Computer Systems
The complexity of mean flow time scheduling problems with release times
Journal of Scheduling
Scheduling contention-free irregular redistributions in parallelizing compilers
The Journal of Supercomputing
Scheduling Messages For Data Redistribution: An Experimental Study
International Journal of High Performance Computing Applications
GridBatch: Cloud Computing for Large-Scale Data-Intensive Batch Applications
CCGRID '08 Proceedings of the 2008 Eighth IEEE International Symposium on Cluster Computing and the Grid
A flexible processor mapping technique toward data localization for block-cyclic data redistribution
The Journal of Supercomputing
An ant algorithm for balanced job scheduling in grids
Future Generation Computer Systems
Optimal replica placement in hierarchical Data Grids with locality assurance
Journal of Parallel and Distributed Computing
An Algorithm in SwinDeW-C for Scheduling Transaction-Intensive Cost-Constrained Cloud Workflows
ESCIENCE '08 Proceedings of the 2008 Fourth IEEE International Conference on eScience
Evaluating the cost-benefit of using cloud computing to extend the capacity of clusters
Proceedings of the 18th ACM international symposium on High performance distributed computing
QoS-aware, access-efficient, and storage-efficient replica placement in grid environments
The Journal of Supercomputing
Cost-Minimizing Scheduling of Workflows on a Cloud of Memory Managed Multicore Machines
CloudCom '09 Proceedings of the 1st International Conference on Cloud Computing
Client-side load balancer using cloud
Proceedings of the 2010 ACM Symposium on Applied Computing
Job scheduling techniques for distributed systems with temporal constraints
GPC'10 Proceedings of the 5th international conference on Advances in Grid and Pervasive Computing
Efficient multidimensional data redistribution for resizable parallel computations
ISPA'07 Proceedings of the 5th international conference on Parallel and Distributed Processing and Applications
p-PIC: Parallel power iteration clustering for big data
Journal of Parallel and Distributed Computing
MPaaS: Mobility prediction as a service in telecom cloud
Information Systems Frontiers
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Data management and migration are important research challenges of novel Cloud environments. While moving data among different geographical domains, it is important to lower the transmission cost for performance purposes. Efficient scheduling methods allow us to manage data transmissions with lower number of steps and shorter transmission time. In previous research efforts, several methods have been proposed in literature in order to manage data and minimize transmission cost for the case of Single Cluster environments. Unfortunately, these methods are not suitable to large-scale and complicated environments such as Clouds, with particular regard to the case of scheduling policies. Starting from these motivations, in this paper we propose an efficient data transmission method for data-intensive scientific applications over Clouds, called Cloud Adaptive Dispatching (CAD). This method adapts to specialized characteristics of Cloud systems and successfully shortens the transmission cost, while also avoiding node contention during moving data from sites to sites. We conduct an extensive campaign of experiments focused to test the effective performance of CAD. Results clearly demonstrate the improvements offered by CAD in supporting data transmissions across Clouds for data-intensive scientific applications.