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

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 LabNational University of Singapore (NUS), Singapore.

www.gridbus.org/gridsim/

2

Presentation Outline

• Introduction• Background• Design and Implementation• Experiments and Results• Related Work• Conclusion and Further Work• Questions and Answers

3

Grid as Cyberinfrastructure for e-Science and e-Business

Applications

Grid Resource Broker

Resource Broker

Application

Grid Information Service

Grid Resource Broker

databaseR2R3

RN

R1

R4

R5

R6

Grid Information Service

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

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

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

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

GridSim - System Architecture

Basic Discrete Event Simulation Infrastructure

Virtual Machine (Java, cJVM, RMI)

PCs ClustersWorkstations

. . .

SMPs Distributed Resources

GridSim Toolkit

Application Modeling

InformationServices

Resource Allocation

Grid Resource Brokers or Schedulers’s Simulation

Statistics

Resource Modeling and Simulation (with Time and Space shared schedulers)

Job Management

ClustersSingle CPU ReservationSMPs Load Pattern

Application Configuration

Resource Configuration

Visual Modeler

Grid Scenario

Network

SimJava Distributed SimJava

Resource Entities

Output

Application, User, Grid Scenario’s Input and Results

Add your own policy for resource allocation

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

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

EA

Output_EA

Input_EA

EB

Output_EB

Input_EB

body()

Send(output, data, EB)……

body()

body()

…

…body() …

body()

…

body()

Receive(input, data, EA)……

Timed Event Delivery

data, t2

(Deliver data @ t2)

GridSim Entities Communication Model

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

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

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

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

GrangeNet and Grid Modeling

17

Resource Characteristics

Name

Location Resource Characteristics Num CPU

A SPEC Rating

R0 Dept. of Physics,Univ. of Melbourne

PC with Intel Pentium 2.0 Ghz, 512MB RAM

1 684

R1 GRIDS Lab, Univ. of Melbourne

Dual Intel Xeon 2.6 Ghz, 2GB RAM

4 1050

R2 Dept. of Physics, Univ. of Sydney

Dual Intel Xeon 2.6 Ghz, 2GB RAM

4 1050

R3 Dept. of Computer Sc., Univ. of Adelaide

Dual Intel Xeon 2.6 Ghz, 2GB RAM

4 1050

R4 Australia National Univ., Canberra

Dual Intel Xeon 2.6 Ghz, 2GB RAM

4 1050

Table 1.Australian Belle analysis data grid testbed simulated

using GridSim

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

Results: Advantage of network QoS in a shared network

environmentPriority With background

traffic(in simulation

minutes)

High 22.82

Normal 23.57

Priority With SCFQ scheduler(in simulation

seconds)

High 1.20 x 10-6

Normal 2.38 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

Results

Packet Scheduling With background traffic (seconds)

Without background traffic

(seconds)

SCFQ 122 x 10-6 121 x 10-6

FIFO 149 x 10-6 146 x 10-6

Table 4.An average of high priority package

lifetime at the Melbourne Leaf Routerunder a heavier load (job data size =

10MB, previously 1 MB)

21

Results: effect of background traffic

Number of packets passing through the Melbourne Leaf Router

22

Related Work

Simulation Tools

Routing Table Entry

Type of Transport Protocol

Data Packetizati

on

Runtime Network Status

Network QoS

GridSim Automatic

A datagram oriented protocol similar to UDP

Supported Supported

Supported

MicroGrid Automatic

TCP and UDP Supported Supported

Not supporte

d

SimGrid Manual TCP Not supported

Supported

Not supporte

d

OptorSim Manual Not supported Not supported

Not supported

Not supporte

dTable 5. Listing of network functionalities and features for each grid simulator

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

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

Selected GridSim Users