A mobile agent platform based on tuple space coordination
Advances in Engineering Software
GRID '02 Proceedings of the Third International Workshop on Grid Computing
On Quality of Service Optimization with Discrete QoS Options
RTAS '99 Proceedings of the Fifth IEEE Real-Time Technology and Applications Symposium
A Scalable Solution to the Multi-Resource QoS Problem
RTSS '99 Proceedings of the 20th IEEE Real-Time Systems Symposium
Supporting QoS-Based Discovery in Service-Oriented Grids
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Apply agent to build grid service management
Journal of Network and Computer Applications
QoS-Aware Middleware for Web Services Composition
IEEE Transactions on Software Engineering
QoS computation and policing in dynamic web service selection
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
IEEE Internet Computing
Competitive proportional resource allocation policy for computational grid
Future Generation Computer Systems - Special issue: Computational science of lattice Boltzmann modelling
The use of economic agents under price driven mechanism in grid resource management
Journal of Systems Architecture: the EUROMICRO Journal
End-to-end quality of service for high-end applications
Computer Communications
| Hi-index | 0.00 |
This paper presents a Quality of Service (QoS) guaranteed dynamic grid resource scheduling algorithm. It mainly deals with multiple QoS-based grid resource scheduling models and solves the scheduling problems using optimization techniques. The paper proposes the idea of decomposing a global optimization problem in multiple QoS-based resource scheduling into two sub-problems, which simplifies the problem and makes it mathematically tractable. An iterative algorithm is also presented to get grid users and grid resource providers to interact with each other in an interactive process in resource market and achieve optimal QoS constraint dynamic grid resource scheduling. The paper provides performance studies comparing the proposed optimal approach with three possible easier approaches, which provide only partial optimization. The experimental results show that the proposed approach considering both computation and network traffic is able to better optimize the execution time than approaches, which consider only one or none of these criteria.