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Distributed Process Scheduling : A Summary By Pragati Sahu

Distributed Process Scheduling : A Summary By Pragati Sahu

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Page 1: Distributed Process Scheduling : A Summary By Pragati Sahu

Distributed Process Scheduling : A Summary

By

Pragati Sahu

Page 2: Distributed Process Scheduling : A Summary By Pragati Sahu

System Performance Model

Precedence process Model Applied for concurrent process.

Communication process Model Applied for process that coexist and communicate asynchronously.

Disjoint Process Model Process that run independently.

Speedup Factor

S= F(Algorithm,System,Schedule)

Page 3: Distributed Process Scheduling : A Summary By Pragati Sahu

Static Process Scheduling

Mapping of process to processor is determined before the execution process.

Precedence Process Model

Communication Process Model

Page 4: Distributed Process Scheduling : A Summary By Pragati Sahu

Example

Page 5: Distributed Process Scheduling : A Summary By Pragati Sahu

Example

Page 6: Distributed Process Scheduling : A Summary By Pragati Sahu

Static Scheduling Challenges

Prior knowledge of execution time and communication behavior of the process is required.

Once a process is assigned to a processor it remains there until completion of execution.

Page 7: Distributed Process Scheduling : A Summary By Pragati Sahu

Dynamic Load Sharing and Balance

Sender initiated Algorithm Transfer of process require 3 basic decisions. i.e.

Transfer Policy, Selection Policy and location policy.

Receiver initiated Algorithm Receiver pulls process to be executed to its site. Uses similar transfer policy i.e. activates pull when

queue size is below threshold. More Stable than the sender.

Page 8: Distributed Process Scheduling : A Summary By Pragati Sahu

Distributed Process Implementation

The three significant application scenario : Remote Service The message is interpreted as a request for a known service at

remote site

Remote Execution

The messages contain a program to be executed at the remote site. Process Migration The messages representing process are migrated to the remote site

for continuing execution.

Page 9: Distributed Process Scheduling : A Summary By Pragati Sahu

Real Time Scheduling

Rate Monotonic Optimal static-priority scheduling It assigns priority according to period A task with a shorter period has a higher priority Executes a job with the shortest period

Deadline Monotonic Optimal static-priority scheduling It is harder to analyze as no formula based on the load

that guarantee feasible schedule.

Page 10: Distributed Process Scheduling : A Summary By Pragati Sahu

Real Time Scheduling

Earliest Deadline First Optimal dynamic priority scheduling A task with a shorter deadline has a higher priority Executes a job with the earliest deadline

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Recent Research Paper Liu Dun-nan, Jiang Xin-fan, Hu Bin-qi ,hang Si-yuan, Real-time

scheduling feedback fuzzy control system based on area control error and power generation error in :9th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD),2012.

Weijing Song,Shasha Yue, Lizhe Wang, Wanfeng Zhang, Dingsheng Liu, Task Scheduling of Massive Spatial Data Processing across Distributed Data Centers: What's New?, in: 17th International Conference on Parallel and Distributed Systems (ICPADS) ,2011.

Page 12: Distributed Process Scheduling : A Summary By Pragati Sahu

Future Work

Enhancements in real time scheduling for Cloud and Big Data.

Energy efficient scheduling techniques for vast datacenters i.e. Big Data.

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Thank You !!!