Performance-Effective and Low-Complexity Task Scheduling for Heterogeneous Computing
IEEE Transactions on Parallel and Distributed Systems
Task Scheduling Algorithms for Heterogeneous Processors
HCW '99 Proceedings of the Eighth Heterogeneous Computing Workshop
Integrating trust into grid economic model scheduling algorithm
ODBASE'06/OTM'06 Proceedings of the 2006 Confederated international conference on On the Move to Meaningful Internet Systems: CoopIS, DOA, GADA, and ODBASE - Volume Part II
A trust-oriented heuristic scheduling algorithm for grid computing
PaCT'07 Proceedings of the 9th international conference on Parallel Computing Technologies
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Grid technologies have enabled the sharing and aggregation of geographically distributed heterogeneous resources for solving large scale problems like research and scientific applications (include independent and workflow applications). In Grid computing, all the resources collaboratively provide large computing power for solving complex problems. In order to estimate the time required to schedule the workflow applications in grid environment, we have lot of algorithms for scheduling these kinds of applications in grid environment. In Grid environment, since these resources are provided and controlled by different organizations, the resources may fail to provide service to user at any point of time. So we cannot estimate the time for running application. To solve this problem, trust is included in scheduling algorithms for estimating the time required to run the application. Here, trust is used in static list-based task scheduling algorithms Critical Path based Hybrid Heuristic (CPHH) [7] and Hybrid Heuristic Scheduling (HHS) [4] Algorithm. For measuring the performance Speedup, Schedule Length Ratio (SLR) and Running time are considered. Our algorithm is simulated using MATLAB R2009b and TORSCHE toolbox [12]. The results show that Trust used CPHH (TCPHH) algorithm performs better than Trust used HHS (THHS) algorithm.