Journal of Parallel and Distributed Computing - Special issue on parallel evolutionary computing
Journal of Parallel and Distributed Computing
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Scheduling in a Grid Computing Environment Using Genetic Algorithms
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
QoS guided min-min heuristic for grid task scheduling
Journal of Computer Science and Technology - Grid computing
Ant Colony Optimization
Grid middleware services for virtual data discovery, composition, and integration
MGC '04 Proceedings of the 2nd workshop on Middleware for grid computing
Analysis of Dynamic Heuristics for Workflow Scheduling on Grid Systems
ISPDC '06 Proceedings of the Proceedings of The Fifth International Symposium on Parallel and Distributed Computing
Dynamically mapping tasks with priorities and multiple deadlines in a heterogeneous environment
Journal of Parallel and Distributed Computing
Expert Systems with Applications: An International Journal
The Research of Ant Colony and Genetic Algorithm in Grid Task Scheduling
MMIT '08 Proceedings of the 2008 International Conference on MultiMedia and Information Technology
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A Knowledge-Based Ant Colony Optimization for Flexible Job Shop Scheduling Problems
Applied Soft Computing
Ant colony optimization for resource-constrained project scheduling
IEEE Transactions on Evolutionary Computation
Hi-index | 0.00 |
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.