Dang Minh Quan

Mapping Heavy Communication Grid-Based Workflows Onto Grid Resources Within an SLA Context Using Metaheuristics

Service Level Agreements (SLAs) are currently one of the major research topics in grid computing. Among many system components for SLA-related grid jobs, the SLA mapping mechanism has received widespread attention. It is responsible for assigning sub-jobs of a workflow to a variety of grid resources in a way that meets the users deadline and costs as little as possible. With the distinguished workload and resource characteristics, mapping a heavy communication workflow within an SLA context gives rise to a complicated combinatorial optimization problem. This paper presents the application of various metaheuristics and suggests a possible approach to solving this problem. Performance measurements deliver evaluation results on the quality and efficiency of each method.

Business Model and the Policy of Mapping Light Communication Grid-Based Workflow Within the SLA Context

In the business Grid environment, the business relationship between a customer and a service provider should be clearly defined. The responsibility of each partner can be stated in the so-called Service Level Agreement (SLA). In the context of SLA-based workflows, the business model is an important factor to determine its job-resource-mapping policy. However, this aspect has not been described fully in the literature. This paper presents the business model of a system handling SLA-based workflow within the business Grid computing environment. From this business model, the mapping policy of the broker is derived. The experiment results show the impact of business models on the efficiency of mapping policies.

Bilateral Bargaining Game and Fuzzy Logic in the System Handling SLA-Based Workflow

In the business Grid, the owner of a workflow is assumed to ask an SLA Workflow broker to execute the workflow for him. The price for executing a workflow on the Grid is negotiated between the user and the broker. Determining a price that satisfies both, the user and the SLA workflow broker, is a difficult task. This paper proposes a method using bilateral bargaining game model based on fuzzy logic to determine the price that the user and the broker could accept after the first negotiation round. We also analyze many parameters affecting the price determination process. The validation results show that the approach is suitable with business rules.

Mapping a group of jobs in the error recovery of the Grid-based workflow within SLA context

The error recovery mechanism receives an important position in the system supporting service level agreements (SLAs) for the grid-based workflow. If one sub-job of the workflow is late, a group of directly affected sub-jobs should be re-mapped in a way that does not affect the start time of other sub-jobs in the workflow and is as inexpensive as possible. With the distinguished workload and resource characteristics as well as the goal of the problem, this problem needs new method to be solved. This paper presents a mapping algorithm, which can cope with the problem. Performance measurements deliver good evaluation results on the quality and efficiency of the method.

Concepts and Algorithms of Mapping Grid-Based Workflow to Resources Within an SLA Context

With the popularity of Grid-based workflow, ensuring the Quality of Service (QoS) for workflow by Service Level Agreements (SLAs) is an emerging trend in the business grid. Among many system components for supporting SLA-aware Grid-based workflow, the SLA mapping mechanism is allotted an important position as it is responsible for assigning sub-jobs of the workflow to Grid resources in a way that meets the user’s deadline and minimizes costs. To meet those requirements, the resource in each Grid site must be reserved and the user must provide the estimated runtime of each sub-job correlated with a resource configuration. With many different kinds of sub-jobs and resources, the process of mapping a Grid-based workflow within an SLA context defines an unfamiliar and difficult problem. To solve this problem, this chapter describes related concepts and mapping algorithms. In particular, several suboptimization algorithms to map sub-jobs of the workflow to the Grid resources within an SLA context are described. The simulation results show the efficiency of those mapping algorithms.

Optimizing the Execution Time of the SLA-based Workflow in the Grid with Parallel Processing Technology

Service level agreements (SLAs) is currently one of the major research topics in grid computing. Among many system components for the supporting of SLA-aware Grid- based workflow, the SLA mapping module receives important positions. Optimizing execution time is an important task of the mapping module as it helps in finding out a feasible solution when the Grid is busy or by eliminating the negative effects of the error. With the previously proposed algorithm for optimizing the execution time of the workflow, the mapping module may, when many requests come in a short period of time, become the bottleneck of the system. This paper presents a parallel mapping algorithm for optimizing the execution time of the workflow, which can cope with the problem. Performance measurements deliver evaluation results on the quality of the method.

Mapping Light Communication SLA-Based Workflows onto Grid Resources with Parallel Processing Technology

Service level agreements (SLAs) are currently one of the major research topics in grid computing. Among many system components for supporting of SLA-aware Grid jobs, the SLA mapping module holds an important position and the capability of the mapping module depends on the runtime of the mapping algorithm. With the previously proposed mapping algorithm, the mapping module may develop into the bottleneck of the system if many requests come in during a short period of time. This paper presents a parallel mapping algorithm to map heavy communication SLA-based workflow onto Grid resources which can cope with the problem. Performance measurements thereby deliver evaluation results showing the quality of the method.

Mapping Heavy Communication SLA-Based Workflows onto Grid Resources with Parallel Processing Technology

Service level agreements (SLAs) are currently one of the major research topics in grid computing. Among many system components for supporting of SLA-aware Grid jobs, the SLA mapping module holds an important position and the capability of the mapping module depends on the runtime of the mapping algorithm. With the previously proposed mapping algorithm, the mapping module may develop into the bottleneck of the system if many requests come in during a short period of time. This paper presents a parallel mapping algorithm to map heavy communication SLA-based workflow onto Grid resources which can cope with the problem. Performance measurements thereby deliver evaluation results showing the quality of the method.

A recovery mechanism for errors caused by a late subjob in a system handling SLA-based Grid workflows

Supporting SLAs (Service Level Agreements) for Grid-based workflows requires providing mechanisms for handling errors (i.e., the failures of subjobs). In the context of this paper, we propose an error recovery mechanism which can handle one failed subjob of a workflow. The error recovery mechanism has a maximum of three phases, depending on the impact of the error. In each phase, we use a dedicated algorithm to remap the subjobs of the workflow to the resources. The main contributions of the paper are the error recovery mechanism for SLA-based workflows and the mapping algorithm G-map, which is used in the first phase of the recovery mechanism. The G-map remaps the groups of subjobs, which are directly affected by an error. The efficiency of the proposed algorithm is validated through simulation results.