Task scheduling in parallel and distributed systems
Task scheduling in parallel and distributed systems
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
IEEE Transactions on Parallel and Distributed Systems
Static scheduling algorithms for allocating directed task graphs to multiprocessors
ACM Computing Surveys (CSUR)
Performance-Effective and Low-Complexity Task Scheduling for Heterogeneous Computing
IEEE Transactions on Parallel and Distributed Systems
IEEE Transactions on Parallel and Distributed Systems
Static task scheduling and grain packing in parallel processing systems
Static task scheduling and grain packing in parallel processing systems
A taxonomy of scientific workflow systems for grid computing
ACM SIGMOD Record
Scheduling of scientific workflows in the ASKALON grid environment
ACM SIGMOD Record
Partitioning rules for orchestrating mobile information systems
Personal and Ubiquitous Computing
Discovering Resources in Computational GRID Environments
The Journal of Supercomputing
Pegasus: A framework for mapping complex scientific workflows onto distributed systems
Scientific Programming
Dynamic workflow model fragmentation for distributed execution
Computers in Industry
Scheduling Data-IntensiveWorkflows onto Storage-Constrained Distributed Resources
CCGRID '07 Proceedings of the Seventh IEEE International Symposium on Cluster Computing and the Grid
Journal of Parallel and Distributed Computing
Performance and cost optimization for multiple large-scale grid workflow applications
Proceedings of the 2007 ACM/IEEE conference on Supercomputing
Scientific Programming - Scientific Workflows
Resource scheduling with conflicting objectives in grid environments: Model and evaluation
Journal of Network and Computer Applications
Adaptive hierarchical scheduling policy for enterprise grid computing systems
Journal of Network and Computer Applications
QoS Constrained Grid Workflow Scheduling Optimization Based on a Novel PSO Algorithm
GCC '09 Proceedings of the 2009 Eighth International Conference on Grid and Cooperative Computing
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Genetic algorithms for task scheduling problem
Journal of Parallel and Distributed Computing
Grid load balancing using intelligent agents
Future Generation Computer Systems
List scheduling with duplication for heterogeneous computing systems
Journal of Parallel and Distributed Computing
AINA '10 Proceedings of the 2010 24th IEEE International Conference on Advanced Information Networking and Applications
On cluster resource allocation for multiple parallel task graphs
Journal of Parallel and Distributed Computing
Contention-aware scheduling with task duplication
Journal of Parallel and Distributed Computing
BTS: Resource capacity estimate for time-targeted science workflows
Journal of Parallel and Distributed Computing
Online algorithms for advance resource reservations
Journal of Parallel and Distributed Computing
Cost optimized provisioning of elastic resources for application workflows
Future Generation Computer Systems
A hybrid heuristic-genetic algorithm for task scheduling in heterogeneous processor networks
Journal of Parallel and Distributed Computing
Scheduling and planning job execution of loosely coupled applications
The Journal of Supercomputing
Adapting market-oriented scheduling policies for cloud computing
ICA3PP'10 Proceedings of the 10th international conference on Algorithms and Architectures for Parallel Processing - Volume Part I
Flexible service selection with user-specific QoS support in service-oriented architecture
Journal of Network and Computer Applications
Dynamic multi-resource advance reservation in grid environment
The Journal of Supercomputing
Enhancing genetic algorithms for dependent job scheduling in grid computing environments
The Journal of Supercomputing
Optimal resource provisioning for cloud computing environment
The Journal of Supercomputing
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The increasing demand on execution of large-scale Cloud workflow applications which need a robust and elastic computing infrastructure usually lead to the use of high-performance Grid computing clusters. As the owners of Cloud applications expect to fulfill the requested Quality of Services (QoS) by the Grid environment, an adaptive scheduling mechanism is needed which enables to distribute a large number of related tasks with different computational and communication demands on multi-cluster Grid computing environments. Addressing the problem of scheduling large-scale Cloud workflow applications onto multi-cluster Grid environment regarding the QoS constraints declared by application's owner is the main contribution of this paper. Heterogeneity of resource types (service type) is one of the most important issues which significantly affect workflow scheduling in Grid environment. On the other hand, a Cloud application workflow is usually consisting of different tasks with the need for different resource types to complete which we call it heterogeneity in workflow. The main idea which forms the soul of all the algorithms and techniques introduced in this paper is to match the heterogeneity in Cloud application's workflow to the heterogeneity in Grid clusters. To obtain this objective a new bi-level advanced reservation strategy is introduced, which is based upon the idea of first performing global scheduling and then conducting local scheduling. Global-scheduling is responsible to dynamically partition the received DAG into multiple sub-workflows that is realized by two collaborating algorithms: (1)聽The Critical Path Extraction algorithm (CPE) which proposes a new dynamic task overall critically value strategy based on DAG's specification and requested resource type QoS status to determine the criticality of each task; and (2)聽The DAG Partitioning algorithm (DAGP) which introduces a novel dynamic score-based approach to extract sub-workflows based on critical paths by using a new Fuzzy Qualitative Value Calculation System to evaluate the environment. Local-scheduling is responsible for scheduling tasks on suitable resources by utilizing a new Multi-Criteria Advance Reservation algorithm (MCAR) which simultaneously meets high reliability and QoS expectations for scheduling distributed Cloud-base applications. We used the simulation to evaluate the performance of the proposed mechanism in comparison with four well-known approaches. The results show that the proposed algorithm outperforms other approaches in different QoS related terms.