Name
Abstract | ||
|---|---|---|
Service-oriented grid environment enables a new way of service provisioning based on utility computing models, where users
consume services based on their QoS (Quality of Service) requirements. In such “pay-per-use” Grids, workflow execution cost
must be considered during scheduling based on users’ QoS constraints. In this paper, we propose a knowledge-based ant colony
optimization algorithm (KBACO) for grid workflow scheduling with consideration of two QoS constraints, deadline and budget.
The objective of this algorithm is to find a solution that minimizes execution cost while meeting the deadline in terms of
users’ QoS requirements. Based on the characteristics of workflow scheduling, we define pheromone in terms of cost and design
a heuristic in terms of latest start time of tasks in workflow applications. Moreover, a knowledge matrix is defined for the
ACO approach to integrate the ACO model with knowledge model. Experimental results show that our algorithm achieves solutions
effectively and efficiently.
|
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-13495-1_30 | ICSI |
Keywords | Field | DocType |
utility computing,ant colony,ant colony optimization,knowledge base,quality of service,scheduling problem | Ant colony optimization algorithms,Heuristic,Scheduling (computing),Computer science,Quality of service,Utility computing,Workflow management system,Workflow,Grid,Distributed computing | Conference |
Volume | Issue | ISSN |
6145 LNCS | PART 1 | 0302-9743 |
ISBN | Citations | PageRank |
3-642-13494-7 | 3 | 0.44 |
References | Authors | |
14 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yan-Li Hu | 1 | 17 | 2.55 |
| Lining Xing | 2 | 16 | 8.51 |
| Wei Ming Zhang | 3 | 69 | 6.72 |
| Weidong Xiao | 4 | 314 | 59.09 |
| Daquan Tang | 5 | 31 | 7.70 |