Analysis and evaluation of heuristic methods for static task scheduling
Journal of Parallel and Distributed Computing
IEEE Transactions on Parallel and Distributed Systems
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
Computing shortest paths for any number of hops
IEEE/ACM Transactions on Networking (TON)
A Generalized Scheme for Mapping Parallel Algorithms
IEEE Transactions on Parallel and Distributed Systems
Configuring sessions in programmable networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
ICDCS '95 Proceedings of the 15th International Conference on Distributed Computing Systems
Resource allocation in a middleware for streaming data
MGC '04 Proceedings of the 2nd workshop on Middleware for grid computing
ISCC '04 Proceedings of the Ninth International Symposium on Computers and Communications 2004 Volume 2 (ISCC"04) - Volume 02
A Statistical Study of the Performance of a Task Scheduling Algorithm
IEEE Transactions on Computers
Overlay Networks with Linear Capacity Constraints
IEEE Transactions on Parallel and Distributed Systems
Mapping pipeline skeletons onto heterogeneous platforms
Journal of Parallel and Distributed Computing
Performance of local search heuristics on scheduling a class of pipelined multiprocessor tasks
Computers and Electrical Engineering
Genetic algorithms for task scheduling problem
Journal of Parallel and Distributed Computing
Optimizing End-to-end Performance of Distributed Applications with Linear Computing Pipelines
ICPADS '09 Proceedings of the 2009 15th International Conference on Parallel and Distributed Systems
A scheduling framework for large-scale, parallel, and topology-aware applications
Journal of Parallel and Distributed Computing
Journal of Grid Computing
Proceedings of the 46th Annual Simulation Symposium
| Hi-index | 0.00 |
Supporting high-performance data-intensive computing pipelines in wide-area networks is crucial for enabling large-scale distributed scientific applications that require minimizing end-to-end delay for single-input applications or maximizing frame rate for streaming applications. We formulate and categorize the data-intensive computing pipeline mapping problems into six classes with two optimization objectives, i.e. minimum end-to-end delay and maximum frame rate, and three network constraints, i.e. no, contiguous, and arbitrary node reuse. We design a dynamic programming-based optimal solution to the problem of minimum end-to-end delay with arbitrary node reuse and prove the NP-completeness of the rest five problems, for each of which, a heuristic algorithm based on a similar optimization procedure is proposed. These heuristics are implemented and tested on a large set of simulated pipelines and networks of various scales and their performance superiority is illustrated by extensive simulation results in comparison with existing methods.