Dynamically tuning level of parallelism in wide area data transfers
DADC '08 Proceedings of the 2008 international workshop on Data-aware distributed computing
Dynamic Multi-stream Transport Protocol
APNOMS '08 Proceedings of the 11th Asia-Pacific Symposium on Network Operations and Management: Challenges for Next Generation Network Operations and Service Management
Balancing TCP buffer vs parallel streams in application level throughput optimization
Proceedings of the second international workshop on Data-aware distributed computing
A data throughput prediction and optimization service for widely distributed many-task computing
Proceedings of the 2nd Workshop on Many-Task Computing on Grids and Supercomputers
Minimizing the Data Transfer Time Using Multicore End-System Aware Flow Bifurcation
CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
StorkCloud: data transfer scheduling and optimization as a service
Proceedings of the 4th ACM workshop on Scientific cloud computing
Dynamic protocol tuning algorithms for high performance data transfers
Euro-Par'13 Proceedings of the 19th international conference on Parallel Processing
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Applications that use parallel TCP streams to increase throughput must multiplex and demultiplex data blocks over a set of TCP streams transmitting on one or more network paths. When applications use the obvious round robin scheduling algorithm for multiplexing data blocks, differences in transmission rate between individual TCP streams can lead to significant data block reordering. This forces the demultiplexing receiver to buffer out-of-order data blocks, consuming memory and potentially causing the receiving application to stall. This paper describes a new adaptive weighted scheduling approach for multiplexing data blocks over a set of parallel TCP streams. Our new scheduling approach, compared with the scheduling approached used by GridFTP, reduces reordering of data blocks between individual TCP streams, maintains the aggregate throughput gains of parallel TCP, consumes less receiver memory for buffering out-of-order packets, and delivers smoother application goodput. We demonstrate the improved characteristics of our new scheduling approach using data transmission experiments over real and emulated wide-area networks.