Handling batch processing overloads in ERP

Users of Microsoft Dynamics AX ERP leverage batch jobs for processing large amounts of data. This kind of batch job processing is expected to cause high resource load on the system. Parallel execution of more than one such resource-intensive batch job can lead to overload of system resources. This results in poor interactive user experience due to high response times. This master's thesis introduces resource overload control solution that reduces number of parallel resource-intensive jobs by performing admission control. Because admission control distributes execution times of resource-intensive jobs over time, resource consumption also gets distributed. The introduction part of the thesis begins with a brief overview of Microsoft Dynamics AX system and batch job use. That is followed by analysis of system resources and batch job workload on the test environment. In analysis resources are represented as operating system resources and data resources that are defined as groups of database tables. In order to evaluate the proposed solution an artificial workload is needed, which is defined based on the results of workload analysis. The central part of the thesis presents how the standard algorithm for scheduling of batch jobs in AX works. The scheduling algorithm is then extended with admission control that uses information about tasks in combination with resource consumption in order to decide whether to select task for execution or not. Admission control needs information about state of resources, thus a monitoring mechanism is introduced. This monitoring implements a dynamic threshold algorithm to eliminate insignificant resource state changes. Final part of the thesis begins with the presentation of results obtained by using the solution on the test environment. First, the results are presented, which were obtained by applying the workload of generic batch jobs that consume a specific resource. This is used to demonstrate that the solution is working according to the design. That is followed by the presentation of the results that were obtained by applying workload of real batch jobs that consume various system resources. With this it is presented how well the solution performs when handling overloads in general. At the end the solution is evaluated by summarizing the results. In the process, the time is used as a criteria of evaluation, in which the resource consumption is above the given reference point

Handling batch processing overloads in ERP

Users of Microsoft Dynamics AX ERP leverage batch jobs for processing large amounts of data. This kind of batch job processing is expected to cause high resource load on the system. Parallel execution of more than one such resource-intensive batch job can lead to overload of system resources. This results in poor interactive user experience due to high response times. This master's thesis introduces resource overload control solution that reduces number of parallel resource-intensive jobs by performing admission control. Because admission control distributes execution times of resource-intensive jobs over time, resource consumption also gets distributed. The introduction part of the thesis begins with a brief overview of Microsoft Dynamics AX system and batch job use. That is followed by analysis of system resources and batch job workload on the test environment. In analysis resources are represented as operating system resources and data resources that are defined as groups of database tables. In order to evaluate the proposed solution an artificial workload is needed, which is defined based on the results of workload analysis. The central part of the thesis presents how the standard algorithm for scheduling of batch jobs in AX works. The scheduling algorithm is then extended with admission control that uses information about tasks in combination with resource consumption in order to decide whether to select task for execution or not. Admission control needs information about state of resources, thus a monitoring mechanism is introduced. This monitoring implements a dynamic threshold algorithm to eliminate insignificant resource state changes. Final part of the thesis begins with the presentation of results obtained by using the solution on the test environment. First, the results are presented, which were obtained by applying the workload of generic batch jobs that consume a specific resource. This is used to demonstrate that the solution is working according to the design. That is followed by the presentation of the results that were obtained by applying workload of real batch jobs that consume various system resources. With this it is presented how well the solution performs when handling overloads in general. At the end the solution is evaluated by summarizing the results. In the process, the time is used as a criteria of evaluation, in which the resource consumption is above the given reference point

Development of a grid service for multi-objective design optimisation

The emerging grid technology is receiving great attention from researchers and applications that need computational and data capabilities to enhance performance and efficiency. Multi-Objective Design Optimisation (MODO) is computationally and data challenging. The challenges become even more with the emergence of evolutionary computing (EC) techniques which produce multiple solutions in a single simulation run. Other challenges are the complexity in mathematical models and multidisciplinary involvement of experts, thus making MODO collaborative and interactive in nature. These challenges call for a problem solving environment (P SE) that can provide computational and optimisation resources to MODO experts as services. Current PSEs provide only the technical specifications of the services which is used by programmers and do not have service specifications for designers that use the system to support design optimisation as services. There is need for PSEs to have service specification document that describes how the services are provided to the end users. Additionally, providing MODO resources as services enabled designers to share resources that they do not have through service subscription. The aim of this research is to develop specifications and architecture of a grid service for MODO. The specifications provide the service use cases that are used to build MODO services. A service specification document is proposed and this enables service providers to follow a process for providing services to end users. In this research, literature was reviewed and industry survey conducted. This was followed by the design, development, case study and validation. The research studied related PSEs in literature and industry to come up with a service specification document that captures the process for grid service definition. This specification was used to develop a framework for MODO applications. An architecture based on this framework was proposed and implemented as DECGrid (Decision Engineering Centre Grid) prototype. Three real-life case studies were used to validate the prototype. The results obtained compared favourably with the results in literature. Different scenarios for using the services among distributed design experts demonstrated the computational synergy and efficiency in collaboration. The mathematical model building service and optimisation service enabled designers to collaboratively build models using the collaboration service. This helps designers without optimisation knowledge to perform optimisation. The key contributions in this research are the service specifications that support MODO, the framework developed which provides the process for definining the services and the architecture used to implement the framework. The key limitations of the research are the use of only engineering design optimisation case studies and the prototype is not tested in industry.EThOS - Electronic Theses Online ServiceGBUnited Kingdo