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1 Constructing A Grid Simulation with Differentiated Network Service using GridSim Anthony Sulistio, Gokul Poduval, Rajkumar Buyya, Chen-Kong Tham Fellow.

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Presentation on theme: "1 Constructing A Grid Simulation with Differentiated Network Service using GridSim Anthony Sulistio, Gokul Poduval, Rajkumar Buyya, Chen-Kong Tham Fellow."— Presentation transcript:

1 1 Constructing A Grid Simulation with Differentiated Network Service using GridSim Anthony Sulistio, Gokul Poduval, Rajkumar Buyya, Chen-Kong Tham Fellow of Grid Computing Grid Computing and Distributed Systems (GRIDS) Lab. The University of Melbourne, Australia Networks and Distributed Systems Lab National University of Singapore (NUS), Singapore. www.gridbus.org/gridsim/

2 2 Presentation Outline Introduction Background Design and Implementation Experiments and Results Related Work Conclusion and Further Work Questions and Answers

3 3 Grid as Cyberinfrastructure for e-Science and e-Business Applications Grid Resource Broker Resource Broker Application Grid Information Service Grid Resource Broker database R2R2 R3R3 RNRN R1R1 R4R4 R5R5 R6R6 Grid Information Service

4 4 Resource Management and Application Scheduling This is one of most challenging aspect of Grid Computing: Due to presence of heterogeneity resources along dynamic variation of available capability of resources. Application Scheduling Policies need to properly investigated/evaluated before deploying them on production Grids.

5 5 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 ?

6 6 Grid Environment Dynamic: 1. Resource and User Properties vary with time.  Experiment cannot be repeated. 2. Resources are distributed and owned by different organizations. 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 modeling and simulation.

7 7 GridSim Toolkit GridSim is a Java-based discrete-event grid simulation package. GridSim is based on SimJava2. Few functionalities of GridSim: Allows modeling of heterogeneous of various types of resources & users. Resources can be extended to implement your own allocation policies (e.g, SLA or VO based allocation). Supports simulation of both static & dynamic schedulers. Simulates applications with different parallel models.

8 8 GridSim - 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’s Simulation 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 Add your own policy for resource allocation

9 9 Network Functionalities Communication networks serve as a fundamental component of grid computing. A realistic simulation of grid environments should include the effects of sending data over shared communication lines. Earlier versions of GridSim did not have the ability to specify a network topology, nor the functionality to connect resources through network links in the experiment.

10 10 Our Work In this work, GridSim has been extended to address the above problems with the ability to simulate realistic network models by: allowing users to create a network topology, packetizing a data into smaller chunks for sending it over a network, generating background traffic, and incorporating different level of services for sending packets.

11 11 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 data @ t2) GridSim Entities Communication Model

12 12 New Network Extension Model New functionalities: support for Network Quality of Service, such as each packet has a Type of Service (ToS) attribute support for Runtime Information, such as an ICMP ping message. generate background traffic, which is done by Output

13 13 Experiment The main aim of this experiment is to show GridSim's ability to simulate an adequate-size grid testbed. For this experiment, we are mainly concern about the network behavior in a grid environment. Hence, we are trying to look at: how background traffic might affect network loads and overall execution time; and how differentiated QoS for packets might help in a heavy load situation;

14 14 Australian BADG test-bed – Hardware Uni.Adelaide CS group 2 Xeon 2.6GHz (IBM) 70 GB disk APAC/GrangeNet (at ANU) 2 Xeon 2.6GHz (IBM) 70 GB disk Uni.Melbourne EPP group 1 P4 Intel 2.0GHz 70 GB disk Uni.Melbourne GridBus/CS 2 Xeon 2.6GHz (IBM) 70 GB disk Uni.Sydney HEP group 2 Xeon 2.6GHz (IBM) 70 GB disk

15 15 Experiment Setup Five resources are created in four different locations: Canberra, Adelaide, Melbourne and Sydney. All resources are connected via GrangeNet, a Gigabit wide-area network within Australia. All links share same characteristics, i.e. MTU size of 1,500 bytes and latency of 10 milliseconds.

16 16 GrangeNet and Grid Modeling

17 17 Resource Characteristics NameLocationResource CharacteristicsNum CPU A SPEC Rating R0Dept. of Physics, Univ. of Melbourne PC with Intel Pentium 2.0 Ghz, 512MB RAM 1684 R1GRIDS Lab, Univ. of Melbourne Dual Intel Xeon 2.6 Ghz, 2GB RAM41050 R2Dept. of Physics, Univ. of Sydney Dual Intel Xeon 2.6 Ghz, 2GB RAM41050 R3Dept. of Computer Sc., Univ. of Adelaide Dual Intel Xeon 2.6 Ghz, 2GB RAM41050 R4Australia National Univ., Canberra Dual Intel Xeon 2.6 Ghz, 2GB RAM41050 Table 1. Australian Belle analysis data grid testbed simulated using GridSim

18 18 User Characteristics There are 5 users located on each of the four locations, sharing the same characteristics: bandwidth: 100 Mbps connected to a leaf router of each testbed site total number of jobs: 20 each job data size: 1 MB each job processing power: 100 Million Instructions (MI) each job submission: uniformly distributed among five resources as mentioned in Table 1. background traffic: submits to all resources and other users, with inter-arrival time using a Poisson distribution approach with mean of 5 minutes. Total number of packets for each interval is uniformly distributed in [1... 10]. The size of each packet is 1,500 bytes

19 19 Results: Advantage of network QoS in a shared network environment PriorityWith background traffic (in simulation minutes) High22.82 Normal23.57 PriorityWith SCFQ scheduler (in simulation seconds) High1.20 x 10 -6 Normal2.38 x 10 -6 Table 2. Network QoS using SCFQ (self clocked fair queuing) packet scheduler (4 users out of 20 are given high priority for sending their jobs) Table 3. An Average Packet Lifetime at the Melbourne Leaf Router (which links 2 resources, hence more traffic that other leaf routers)

20 20 Results Packet SchedulingWith background traffic (seconds) Without background traffic (seconds) SCFQ122 x 10 -6 121 x 10 -6 FIFO149 x 10 -6 146 x 10 -6 Table 4. An average of high priority package lifetime at the Melbourne Leaf Router under a heavier load (job data size = 10MB, previously 1 MB)

21 21 Results: effect of background traffic Number of packets passing through the Melbourne Leaf Router

22 22 Related Work Simulation Tools Routing Table Entry Type of Transport Protocol Data Packetization Runtime Network Status Network QoS GridSimAutomaticA datagram oriented protocol similar to UDP Supported MicroGridAutomaticTCP and UDPSupported Not supported SimGridManualTCPNot supportedSupportedNot supported OptorSimManualNot supported Table 5. Listing of network functionalities and features for each grid simulator

23 23 Conclusion GridSim toolkit provides comprehensive support application scheduling simulations in Grid computing environment. GridSim has new features such as generating background traffic during an experiment, requesting network information during runtime and providing differentiated service for packets based on users‘ Quality of Service (QoS) requirements. Our experiment has shown how GridSim can be used to simulate a medium-sized grid testbed. GridSim is available to download: www.gridbus.org/gridsim/

24 24 Future Work We are planning to incorporate additional features into GridSim, such as having different types of routing algorithms, schedulers and reservation of network resources. adding other type of network building blocks like switches and domain gateways. support will be added for non work-conserving routers. planning an ability to design the network topology using scripts similar to ns-2.

25 25 Selected GridSim Users


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