Introduction to algorithms
Scheduling pipelined communication in distributed memory multiprocessors for real-time applications
ISCA '91 Proceedings of the 18th annual international symposium on Computer architecture
Optimal Data Scheduling for Uniform Multidimensional Applications
IEEE Transactions on Computers
Scheduling data transfers in a network and the set scheduling problem
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
IEEE Transactions on Parallel and Distributed Systems
Proceedings of the 2001 ACM/IEEE conference on Supercomputing
Data Intensive Distributed Computing; A Medical Application Example
HPCN Europe '99 Proceedings of the 7th International Conference on High-Performance Computing and Networking
Decoupling Computation and Data Scheduling in Distributed Data-Intensive Applications
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
Scheduling Deadline Driven Packet Flows in HiperAccess
ISCC '03 Proceedings of the Eighth IEEE International Symposium on Computers and Communications
End-to-End Scheduling in Real-Time Packet-Switched Networks
ICNP '96 Proceedings of the 1996 International Conference on Network Protocols (ICNP '96)
Optimizing Data Scheduling on Processor-In-Memory Arrays
IPPS '98 Proceedings of the 12th. International Parallel Processing Symposium on International Parallel Processing Symposium
Performance of file replication policies for real-time file access in data grids
Proceedings of the first international conference on Networks for grid applications
ISPA'06 Proceedings of the 4th international conference on Parallel and Distributed Processing and Applications
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The static staging heuristics proposed in the literature for staging the data items associated with real-time distributed applications adhere to a method by which only one data item is transferred in each communication step to optimize a specific cost function. In this paper, we first propose the Extended Partial Path (EPP) algorithm based on the same method. In terms of maximizing the number of satisfied requests, we have analytically shown that EPP has a performance that is equal to or greater than the Partial Path Heuristic (PPH) introduced previously [CHECK END OF SENTENCE], thanks to excluding the data items that cannot be satisfied by PPH from scheduling and scheduling the satisfiable data-items along their extended paths. In contrast to EPP and other data staging heuristics proposed, we develop the concurrent scheduling (CS) heuristic which allows simultaneous transfer of more than one data item in an organized fashion, thereby improving the overall performance of the staging system. At the heart of the CS heuristic are EPP and the local priority assignment method devised for solving the conflicts between data items at the intermediate nodes. The extensive simulation results further confirm the superiority of the CS heuristic over PPH.