1 / 10

10 th December, 2013

Lab Meeting. Papers Reviewed:. 10 th December, 2013. 1. Fault tolerant workflow scheduling. Primary Issue : Scheduling workflows in a cloud environment, with deadlines, is a complex problem

gaius
Download Presentation

10 th December, 2013

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Lab Meeting Papers Reviewed: 10th December, 2013

  2. 1 Fault tolerant workflow scheduling • Primary Issue : • Scheduling workflows in a cloud environment, with deadlines, is a complex problem • Issues of shared resources, time to release, resource availability, access control during execution, failures, etc. • The main goal is to schedule workflows and execute these workflows within the deadline in-spite of many failures that occur in the environment. • Solution: • Use of replication and resubmission of tasks based on priority of task. • Need to avoid resource wastages • Heuristic metric finds trade-off between replication and resubmission factors without the need for history data 1. Fault tolerant workflow scheduling based on replication and resubmission of tasks in Cloud Computing. Jayadivya et. al.

  3. 1 Results Ratio of success rate and resource usage Failure Probability 1. Fault tolerant workflow scheduling based on replication and resubmission of tasks in Cloud Computing. Jayadivya et. al.

  4. 1 My Observations • Difficult to understand the relevance of the deadline to the success or failure curves • Failure probabilities for ‘with replication’ would be expected to be much better • Surprising result is Performance Comparison are similar – this is probably due to heuristic metric – which is not discussed in detail. • The mean number of replications necessary to achieve results is not specified 1. Fault tolerant workflow scheduling based on replication and resubmission of tasks in Cloud Computing. Jayadivya et. al.

  5. 2 Prediction of Remaining Service Execution Time • Primary Benefits: • Dynamic Process Tracking requires predicted remaining duration • It also assists scheduling of resources • It provides feedback to the client • Present State • Present methods update predictions on event arrival and subtract elapsed time • New Approach: • Also consider expected events that have not occurred • Prediction approach based on PN formalism so that concurrency can be modelled 2. Prediction of remaining service execution time using stochastic PN with arbitrary firing delays. Andreas Rogge-Solti et. al.

  6. Prediction of Remaining Service Execution Time

  7. Prediction of Remaining Service Execution Time

  8. 1 My Observations • Empirical Models are not use • Requires immediate notification of event • Simulations assume a stable state • In a real-time system this may not be feasible

  9. Thank you…. QUESTIONS

More Related