1. Distributed Process Scheduling : A SummaryBy
Pragati Sahu

2. 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)

3. Static Process Scheduling
Mapping of process to processor is determined before the execution process.
Precedence Process Model
Communication Process Model

4. Example

5. Example

6. 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.

7. 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.

8. 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.

9. Real Time Scheduling Rate Monotonic Deadline 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
It is harder to analyze as no formula based on the load that guarantee feasible schedule.

10. 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

11. 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.

12. Future Work
Enhancements in real time scheduling for Cloud and Big Data.
Energy efficient scheduling techniques for vast datacenters i.e. Big Data.

13. Thank You !!!