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School of Computing FACULTY OF ENGINEERING Richard Kavanagh Research Group: Collaborative Systems and Performance, Supervisors: Karim Djemame and Natasha.

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Presentation on theme: "School of Computing FACULTY OF ENGINEERING Richard Kavanagh Research Group: Collaborative Systems and Performance, Supervisors: Karim Djemame and Natasha."— Presentation transcript:

1 School of Computing FACULTY OF ENGINEERING Richard Kavanagh Research Group: Collaborative Systems and Performance, Supervisors: Karim Djemame and Natasha Shakhlevitch Contact Em ail: Motivation Grids are used for large scale computation, by sending computational work jobs to a large collection of distributed computers. This is however limited in that it is largely done upon a best effort approach with no guarantees. This is not useful for time critical experiments and for commercial usage. The goal is therefore to add Quality of Service (QoS) provision by offer guarantees in Grids in terms of both time and cost. A powerful mechanism for adding QoS to Grids is the Service Level Agreement. Work upon SLAs will require the specifying of the appropriate following parts: Universal Variables Common Functions SLA Indicators The most common standard for defining an SLAs is WS-Agreement (WS-A) [4]. The key parts of an SLA in WS-A that will need specifying are: Context – The parties involved, agreement duration etc Service Terms –The description of the job, i.e. In Job Submission Description Language (JSDL). Guarantee Terms – The assurances made: Cost Time Work will focus upon ensuring the most useful terms are specified and that SLA compliance can be measured. SLA Bag of Tasks (BoT) are the most common form of task performed upon the Grid [6]. They are tasks that have no dependencies upon one another. In order to maximise the relevance of the projects work efforts will focus upon this type of task. BoT have higher flexibility in terms of scheduling than other types of task as they have no dependencies upon other tasks i.e. Workflows or tasks with message passing. It is therefore more likely that these tasks will be able to be scheduled with QoS in mind, considering that Grids are such a distributed and heterogeneous environment. Bag of TasksISQoS Broker Grid Economy An economic model is going to be taken, which can enhance Grids in the following ways [1-3]: User priorities are better discovered, allowing for better prioritisation of the jobs. Better welfare at peak demand as more valuable jobs can be prioritised. Adding quality of service adds value It makes sense to offer incentives for providing resources to the Grid. It limits unfair excessive usage as users would not want to run jobs that have limited value. GLUE 2.0 In Grids due to their large scale distributed nature, delays in getting the most current and up to date information about the current state of the Grid environment is difficult. This is compounded by the need to aggregate information together from multiple providers. The aim will be to perform experiments to directly relate how delays in information distribution effect the timeliness of job execution. This information will then be used to ensure information that is most relevant to schedules is updated more frequently and thus aiding the resource selection process and provision of QoS. Resource Selection References [1] Buyya, R., D. Abramson, and S. Venugopal, The Grid economy. Proceedings of the IEEE, (3): p [2] Lai, K., Markets are dead, long live markets. SIGecom Exch., (4): p [3] C. Kenyon and G. Cheliotis, Architecture requirements for commercializing Grid resources, Proc. High Performance Distributed Computing, HPDC Proceedings. 11th IEEE International Symposium on, 2002, pp [4] Open Grid Forum, Web Services Agreement Specification (WS-Agreement),2007. p. 81 [5] Open Grid Forum, GLUE Specification v p. 76. [6] A. Iosup and D. Epema, Grid Computing Workloads: Bags of Tasks, Workflows, Pilots, and Others, Internet Computing, IEEE, vol. PP, no. 99, pp [7] KNOWARC. The Arc Middleware [cited th November]; Available from: Grid Resource Brokering for Quality of Service Provision School of Computing One of the latest standards in Grids is for storing environment information in a standard schema called GLUE 2.0 [5]. This allows for easier communication between different middleware, by producing a common way of representing data. The project will extend GLUE 2.0 so the QoS requirements of the jobs been performed may be stored. The ISQoS broker will be aimed at ensuring QoS for Bag of tasks via economic methods. It will offer various SLAs via a component called the QoS decision maker. Users of this broker will be able to express their service requirements to the broker via a request manager. The jobs will then be either accepted or rejected based on if the QoS request can be satisfied. The viable jobs will then be executed upon the Grid. The broker that is to be developed will be aimed at been standards compliant. This ensures faster communication as it lacks the need for adaptors. The primary candidate for the middleware, that this broker will sit upon will be be KnowARC[7]. ISQoS Broker KnowARC Middleware


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