1 GridSim 2.0 Adv. Grid Modelling & Simulation Toolkit Rajkumar Buyya, Manzur Murshed (Monash), Anthony Sulistio, Chee Shin Yeo Grid Computing and Distributed Systems (GRIDS) Lab, Dept. of Computer Science and Software Engineering The University of Melbourne Thanks to David Abramson

2 Outline Motivation. System Architecture. GridSim Entities. Visual Modeller. Experiments.

3 Performance Evaluation: With Large Scenarios Varying the number of Resources (1 to 100s..1000s..). Resource capability. Cost (Access Price). Users. Deadline and Budget. Workload. Different Time (Peak and Off-Peak). We need a repeatable and controllable environment. Can this be achieved on Real Grid testbed ?

4 Grid Environment Dynamic: 1. Resource and User Properties vary with time.  Experiment cannot be repeated. 2. Resources are distributed and owned by different organisations. Heterogeneous users.  It is hard to create a controllable environment. Grid testbed size is limited. Also, creating testbed infrastructure is time consuming and expensive. Hence, grid computing researchers turn to modelling and simulation.

5 GridSim Toolkit GridSim 1.0 released in Dec GridSim and GridBroker. GridSim 2.0 released in Nov. SC Improvements in GridSim and GridBroker. Add Visual Modeler. Few functionalities of GridSim: Allows modelling of heterogeneous of resources & users. Supports simulation of both static & dynamic schedulers. Simulates applications with different parallel models.

6 System Architecture Basic Discrete Event Simulation Infrastructure Virtual Machine (Java, cJVM, RMI) PCs Clusters Workstations... SMPs Distributed Resources GridSim Toolkit Application Modeling Information Services Resource Allocation Grid Resource Brokers or Schedulers Statistics Resource Modeling and Simulation (with Time and Space shared schedulers) Job Management ClustersSingle CPUReservationSMPsLoad Pattern Application Configuration Resource Configuration Visual Modeler Grid Scenario Network SimJavaDistributed SimJava Resource Entities Output Application, User, Grid Scenario’s Input and Results

7 GridSim Entities Jobs Appli cation Scheduler User #i Broker #i Output Input Output Input Resource #j Job In Queue Job Out Queue Process Queue Resource List Information Service Internet Report Writer #i Statistics Recorder #i Shutdown Signal Manager #i Input Output

8 EAEA Output_E A Input_E A EBEB Output_E B Input_E B body() Send(output, data, E B ) … body() … … … … Receive(input, data, E A ) … Timed Event Delivery data, t2 (Deliver t2) GridSim Entities Communication Model

9 Time Shared: Multitasking and Multiprocessing PE1 PE2 G1 G2 G3 G1 G2 G3 P1-G2 P1-G1 P3-G2P1-G3P2-G3 Time G1 G1: Gridlet1 Arrives G1FG3 G1F: Gridlet1 Finishes G2G2FG3F Gridlet1 (10 MIs) Gridlet2 (8.5 MIs) Gridlet3 (9.5 MIs) P2-G2: Gridlet2 finishes at the 2 nd prediction time. P1-G2: Gridlet2 didn’t finish at the 1 st prediction time. Tasks on PEs/CPUs P2-G2

10 Space Shared: Multicomputing G1 G2 G3 G1G3 G2G3 P1-G1 P1-G2P1-G3 Time G1 G1: Gridlet1 Arrives G1FG3 G1F: Gridlet1 Finishes G2G2FG3F Gridlet1 (10 MIs) Gridlet2 (8.5 MIs) Gridlet3 (9.5 MIs) P1-G2: Gridlet2 finishes as per the 1 st Predication Tasks on PEs/CPUs PE1 PE2

11 Visual Modeler Available in GridSim 2.0 Functionalities: Create and delete many users and resources. Able to save and load the model file (XML format). Generate Java source code.

12 Experiment 1 Create 21 users and 25 resources. Cost varies from 10 to 20 units per sec (G$/sec). Each user has 20 jobs with variation of ± 2. Want to optimise cost. Simulation Time approx. 7 hours. Number of users grows -> Pr (one resource per user) decreases. This low Pr demands high D_Factor and B_Factor in order to achieve very high job completion rate.

13 D-Factor Any job with D_Factor < 0 would never be completed. As long as some resources are available throughout the deadline, any job with D_Factor  1 would always be completed.

14 B-Factor Any job with B_Factor < 0 would never be completed. As long as some resources are available throughout the deadline, any job with B_Factor  1 would always be completed.

15 Main Window of Visual Modeler

16 View User Property Dialog

17 View Resource Property Dialog

18 Job Completion & Cost Optimise

19 Time Utilisation & Cost Optimise

20 Budget Utilisation & Cost Optimise

21 Experiment 2 Workload Synthesis:  200 jobs, each job processing requirement = 10K MI or SPEC with random variation from 0-10%. Exploration of many scenarios:  Deadline: 100 to 3600 simulation time, step = 500.  Budget: 500 to G$, step = Deadline and Budget Constraint (DBC) Strategies:  Cost Optimisation for a single user. Resources: Simulated WWG resources.

22 Simulated WWG Resources

23 Gridlets vs Budget

24 Impact of budget for deadline values

25 Budget spent with deadline values

26 Selected GridSim Users

27 Conclusion GridSim toolkit is suitable for application scheduling simulations in Grid and P2P computing environment. GridSim 2.0 is available to download:  Extending to support Data Grid modelling