TY  - JOUR
AU  - Buyya, R
AU  - Murshed, M
AU  - Abramson, D
AU  - Venugopal, S
Y2  - 2014/05/22
Y1  - 2005
SN  - 0038-0644
UR  - http://hdl.handle.net/11343/30834
AB  - Computational Grids and peer-to-peer (P2P) networks enable the sharing, selection, and aggregation of geographically distributed resources for solving large-scale problems in science, engineering, and commerce. The management and composition of resources and services for scheduling applications, however, becomes a complex undertaking. We have proposed a computational economy framework for regulating the supply of and demand for resources and allocating them for applications based on the users' quality-of-service requirements. The framework requires economy-driven deadline- and budget-constrained (DBC) scheduling algorithms for allocating resources to application jobs in such a way that the users' requirements are met. In this paper, we propose a new scheduling algorithm, called the DBC cost-time optimization scheduling algorithm, that aims not only to optimize cost, but also time when possible. The performance of the cost-time optimization scheduling algorithm has been evaluated through extensive simulation and empirical studies for deploying parameter sweep applications on global Grids.
LA  - English
PB  - Wiley
KW  - Distributed Computing
T1  - Scheduling parameter sweep applications on global Grids: A deadline and budget constrained cost-time optimization algorithm
DO  - 10.1002/spe.646
IS  - Software - Practice and Experience
VL  - 35
IS  - 5
SP  - 491-512
L1  - /bitstream/handle/11343/30834/280199_43919.pdf?sequence=1&isAllowed=n
ER  -