Performance-Effective and Low-Complexity Task Scheduling for Heterogeneous Computing
IEEE Transactions on Parallel and Distributed Systems
Run-Time Adaptation with Resource Co-Allocation for Grid Environments
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
Simgrid: A Toolkit for the Simulation of Application Scheduling
CCGRID '01 Proceedings of the 1st International Symposium on Cluster Computing and the Grid
Resource Co-allocation for Parallel Tasks in Computational Grids
CLADE '03 Proceedings of the 1st International Workshop on Challenges of Large Applications in Distributed Environments
A Framework for Mapping with Resource Co-Allocation in Heterogeneous Computing Systems
HCW '00 Proceedings of the 9th Heterogeneous Computing Workshop
A Synchronous Co-Allocation Mechanism for Grid Computing Systems
Cluster Computing
Design and Implementation of Grid Monitoring System Based on GMA
PDCAT '05 Proceedings of the Sixth International Conference on Parallel and Distributed Computing Applications and Technologies
A decentralized resource allocation policy in minigrid
Future Generation Computer Systems
Dynamic mapping of cooperating tasks to nodes in a distributed system
Future Generation Computer Systems
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In most of mapping Algorithms for application in HDC, the Alhusaini's method is one of the most important Algorithms. However, we find there are some weaknesses in Alhusaini's method though the experiments and analysis. So, we propose a two-phase algorithm called 2-phases dynamic resource co-allocation algorithm (2PDRCA) based on Alhusaini's method. The first phase only generates the data that will be used in the second phase. The second phase will selected a set of independent tasks and allocate according to the weight of each task in our method. The simulation results show that the method is effective, and solves the problem such as Low efficiency of Alhusaini's method in communication intension application.