Mean value analysis of a database grid application
This presentation is the property of its rightful owner.
Sponsored Links
1 / 19

Mean Value Analysis of a Database Grid Application PowerPoint PPT Presentation


  • 79 Views
  • Uploaded on
  • Presentation posted in: General

Mean Value Analysis of a Database Grid Application. Dale R. Thompson Computer Science and Computer Engineering University of Arkansas. Introduction. The analysis of a queueing network is important for predicting the performance of a system.

Download Presentation

Mean Value Analysis of a Database Grid Application

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Mean value analysis of a database grid application

Mean Value Analysis of a Database Grid Application

Dale R. Thompson

Computer Science and Computer Engineering

University of Arkansas

University of Arkansas


Introduction

Introduction

  • The analysis of a queueing network is important for predicting the performance of a system.

  • A database grid application was modeled using a queueing network.

  • The queueing network was analyzed by using an approximate mean value analysis algorithm called the Bard-Schweitzer algorithm or the proportional estimate (PE) algorithm.

  • Several different types of record flows were modeled. For example, uniform, non-uniform, etc.

  • A system in which the batch and interactive requests are segregated was modeled.

University of Arkansas


Queueing network system

queue

client

server

[Single class queueing server]

queue

client1

client2

client3

server

[Multiple class queueing server]

Queueing Network System

University of Arkansas


Mva algorithms

When Queueing Server,

When Delay Server,

MVA algorithms

when class c is a batch processing,

Zc=0

  • Mean Value Analysis calculates throughput (Xc), response time (Rc), and queue length (Qd,c)of each class.

  • It can be classified with the number of client – open or closed.

  • It also can be classified with how to get the values Exactly or Approximately.

  • Single class or multiple classes?

University of Arkansas


Classification of mva algorithms

Classification of MVA algorithms

University of Arkansas


Comparison of mva algorithms

Comparison of MVA algorithms

University of Arkansas


Database grid application

Database Grid Application

Database Link Application Example

High-level Overview of System

University of Arkansas


Database grid application cont

Database Grid Application Cont.

A high-level view of the grid

The Flow of Records

University of Arkansas


Current queueing model

Current Queueing Model

Queueing Model

University of Arkansas


Cpu and network demand

CPU and Network Demand

  • Record size - 500bytes, Ethernet - 26bytes, IP - 20bytes, TCP - 20bytes. Total actual record size - 566bytes

  • Service demand1 : computers in the clients, the director grid, and database grid.

  • Service demand2 : network cards in the clients, the director grid, and database grid.

University of Arkansas


Maximum throughput and block size

Maximum Throughput and Block size

  • Maximum attainable throughput : 79.5Mega record/hr

  • The block size :

    • Batch class : 1150 records

    • Interactive class : 1 record.

University of Arkansas


Uniforms distributions

Uniforms Distributions

  • Each record was equally likely to go to any of the computers in the database grid,

    • Block size : varying

University of Arkansas


Non uniform distribution

Non-uniform Distribution

  • Non-uniform distribution of demands was created by assuming that

    • 20 clients : 10,15,20 director computers : 70 database computers

    • 80% of the requests from clients (16 clients) => 20% of the database grid (14 Computers).

    • The remaining 20% of the requests (4 clients)=> the remaining 80% of the database grid (56 Computers)

University of Arkansas


Uniform number of clients

Uniform : Number of Clients

  • Uniform : 1150 records

  • Varying number of Clients : 20, 40, 60

University of Arkansas


Proposed change to application

Proposed Change to application

  • It was assumed that there were two updates per request

  • This proposed change was modeled by having 5% of the clients (1 client out of 20) require demand from two different database grid computers.

  • Block size : 1150 records

University of Arkansas


Segregation of batch and interactive classes

Segregation of batch and interactive classes

  • This model is for the actual system.

    • 20 clients : 16 director computers : 70 database computers.

  • There are 12 clients batch and 8 clients interactive record.

    • Batch 12 clients => 12 directors

    • Interactive 8 clients => 4 directors.

  • This reduces the mean delay per record to better serve the interactive clients

  • The database link application could use the 0.0002 s/record parameter as a design parameter

University of Arkansas


Conclusions

Conclusions

  • The number of directors should be approximately equal to the number of clients to obtain the maximum throughput of the system.

  • The bottleneck device in this system is the network.

  • The proposed application change that caused 5% of the records to require service from two database grid computers did not significantly decrease the performance of the system.

  • Segregating the batch and interactive classes at the director level causes the response time of the interactive classes to decrease. The decreased response time comes at the price of lowering the overall throughput of the system. As discussed, the model can be used to determine the trade offs of decreased response time versus increased throughput.

University of Arkansas


Future work

Future Work

  • Traffic analysis of submitted records

  • Simulation of alternate configurations

  • Scheduling of grid computers

  • Modeling/Simulation of different applications

  • Grid-enable applications that run in different locations and organizations

  • Others?

University of Arkansas


Contact information and copy of this presentation

Contact Information and Copy of this Presentation

Dale R. Thompson

311 Engineering Hall

Fayetteville, Arkansas, USA

72701

Phone: +1 (479) 575-5090

E-mail: [email protected]

WWW: http://csce.uark.edu/~drt

University of Arkansas


  • Login