Static scheduling algorithms for allocating directed task graphs to multiprocessors
ACM Computing Surveys (CSUR)
Complexity and Approximation: Combinatorial Optimization Problems and Their Approximability Properties
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Scheduling Dags to Minimize Time and Communication
AWOC '88 Proceedings of the 3rd Aegean Workshop on Computing: VLSI Algorithms and Architectures
A Dynamic Critical Path Algorithm for Scheduling Scientific Workflow Applications on Global Grids
E-SCIENCE '07 Proceedings of the Third IEEE International Conference on e-Science and Grid Computing
Overlay Networks with Linear Capacity Constraints
IEEE Transactions on Parallel and Distributed Systems
Mapping Pipeline Skeletons onto Heterogeneous Platforms
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007
System Design and Algorithmic Development for Computational Steering in Distributed Environments
IEEE Transactions on Parallel and Distributed Systems
IWDC'05 Proceedings of the 7th international conference on Distributed Computing
| Hi-index | 0.01 |
Next-generation computation-intensive applications in various science and engineering fields feature large-scale computing workflows. Supporting such computing workflows and optimizing their network performance in terms of end-to-end delay or frame rate in heterogeneous network environments are critical to the success of these distributed applications that require fast response time or smooth data flow. We formulate six linear pipeline configuration problems with different mapping objectives and network constraints, and one general workflow mapping problem. We investigate the computational complexity of these problems and design optimal or heuristic algorithms with rigorous correctness proof and performance analysis. An extensive set of optimization experiments on a large number of simulated workflows and networks illustrate the superior performance of the proposed algorithms in comparison with that of existing methods.