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CD 2004. A Tailorable Environment for Assessing the Quality of Deployment Architectures in Highly Distributed Settings. Sam Malek and Marija Mikic-Rakic Nels Beckman Nenad Medvidovic. University of Southern California. Outline. Motivation Background

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Sam malek and marija mikic rakic nels beckman nenad medvidovic

CD 2004

A Tailorable Environment for Assessing the Quality of Deployment Architectures in Highly Distributed Settings

Sam Malek

and

Marija Mikic-Rakic

Nels Beckman

Nenad Medvidovic

University of Southern California


Outline

Outline

  • Motivation

  • Background

    • Problem description

    • Algorithms

  • DeSi

  • Under the hood

    • Architecture

    • Implementation

  • Future work and concluding remarks

CD 2004


Motivation

Motivation

How good is this deployment architecture?

Deployment architecture: distribution (i.e., assignment) of software components onto hardware nodes.

What are its properties?

How should it be modified to ensure higher availability?

CD 2004


Outline1

Outline

  • Motivation

  • Background

    • Problem description

    • Algorithms

  • DeSi

  • Under the hood

    • Architecture

    • Implementation

  • Future work and concluding remarks

CD 2004


System model

(2) a set H of k hardware nodes (

), two

,

, and a

relations

  • a set

(3) Two relations that restrict locations

of software components

), two relations

function

of n components (

, and a function

,

System model

Given:

CD 2004


Sam malek and marija mikic rakic nels beckman nenad medvidovic

Note that the possible number of different functions is

Problem – formal definition

Find a function

such that the

defined as

system’soverall availability

is maximized, and the following four conditions are satisfied:

CD 2004


Problem breakdown

Problem breakdown

  • Lack of knowledge about runtime system parameters

    • System model parameters not known at the time of initial deployment

    • System model parameters change at runtime

      • Reliability of links, frequencies of interaction, etc.

    • Middleware with monitoring support - PrismMW

  • Exponentially complex problem

    • n components and k hosts = kn possible deployments

    • Polynomial time approximating algorithms

  • Environment for assessing deployments

    • Comparison of different solutions and algorithms

    • performance vs. complexity, sensitivity analysis, etc

    • DeSi’s analysis and visualization utilities

  • Effecting the selected solution

    • Redeploying components

    • Requires an automated solution

    • Middleware with deployment support - PrismMW

CD 2004


Sam malek and marija mikic rakic nels beckman nenad medvidovic

Suite of algorithms

Exact – finds optimal solution O(k^n)

Biased/Unbiased stochastic – random selection O(n^2)

Avala – greedy approximation O(n^3)

DecAp – decentralized auction based O(n^3)

Clustering – decreases complexity

1

0.8

0.6

Achieved

0.4

availability

0.2

z

0

10 comps 100 comps 200 comps 1000 comps 100 comps 30 comps 300 comps

4 hosts 10 hosts 20 hosts 100 hosts 40 hosts 7 hosts 70 hosts

1000000

10000

Time taken

100

(in ms)

1

10 comps 100 comps 200 comps 1000 comps 100 comps 30 comps 300 comps

4 hosts 10 hosts 20 hosts 100 hosts 40 hosts 7 hosts 70 hosts

Original Availability

DecAp Algorithm

Exact Algorithm

Stochastic Algorithm

Avala Algorithm

CD 2004


Sam malek and marija mikic rakic nels beckman nenad medvidovic

DeSi

  • Deployment simulation environment

    • Specification and generation of deployment architectures

    • Visualization and analysis of distributed system

    • Estimation of the quality of deployment

    • Facilitation of rapid development and comparison of algorithms

CD 2004


Sam malek and marija mikic rakic nels beckman nenad medvidovic

CD 2004


Outline2

Outline

  • Motivation

  • Background

    • Problem description

    • Algorithms

  • DeSi

  • Under the hood

    • Architecture

    • Implementation

  • Future work and concluding remarks

CD 2004


Desi s architecture

DeSi’s architecture

DeSi Model

DeSi View

SystemData

AlgoResultData

TableView

GraphView

GraphViewData

DeSi Controller

Middleware

Platform

Generator

Middleware

Adapter

Legend:

Data flow

Control flow

Modifier

Monitor

Effector

Algorithm

Container

CD 2004


Sam malek and marija mikic rakic nels beckman nenad medvidovic

Prism middleware

  • An architectural middleware

  • Enables implementation and deployment of distributed systems in terms of their architectural elements

  • Support for monitoring and redeployment

CD 2004


Sam malek and marija mikic rakic nels beckman nenad medvidovic

Integration with middleware

Legend:

Architecture

Event frequency

monitor

Deployer

Skeleton

/Admin

configuration

Network reliability

monitor

Pointer to

architecture

i

Component

Distributed system

Monitoring Data

Redeployment Data

CD 2004


Desi s implementation

DeSi’s implementation

  • Eclipse plug-in

    • GEF

  • Tailorability

    • Simple API

    • Model specialization

  • Scalability

  • Efficiency

  • Exploration capability

CD 2004


Conclusion and future work

Conclusion and future work

  • Quality of deployment architecture

  • An environment that assists with

    • Development of redeployment algorithms

    • Analysis of real systems

    • Effecting the results

  • Scalability, efficiency, tailorability, explorability

    On-going/future work:

  • Modeling other system properties

  • Creating new visualizations

  • Integrating DeSi with other platforms

CD 2004


Questions

Questions?

CD 2004


Approach overview

Approach - overview

Enabling the system to:

  • Monitor its operation

  • Estimate its new deployment architecture

  • Effect the estimated architecture

CD 2004


Sam malek and marija mikic rakic nels beckman nenad medvidovic

Automatic algorithm selection

TE * AC + (TAVG – TE) * AEXP

CD 2004


Using prism mw

Component A

Component B

Connector C

Connector C

C

C

Component D

// establish the interconnections

arch.weld(a, conn);

arch.weld(b, conn);

arch.weld(conn, d)

}

}

Component A

Component B

Component D

Using Prism-MW

class DemoArch {

static public void main(String argv[]) {

Architecture arch = new Architecture ("DEMO ");

Architecture - DEMO

// create components

ComponentA a = new ComponentA ("A");

ComponentB b = new ComponentB ("B");

ComponentD d = new ComponentD (“D”);

// create connectors

Connector conn = new Connector("Conn");

// add components and connectors

arch.addComponent(a);

arch.addComponent(b);

arch.addComponent(d);

arch.addConnector(conn);

CD 2004


Using prism mw1

Send (e1)

Component A

Component B

  • Component B handles the event and sends a response

  • public void handle(Event e)

  • {

  • if (e.equals(“Event_D”)) {

  • ...

  • Event e1= new Event(“Response_to_D”);

  • e1.addParameter("response", resp);

  • send(e1);

  • }...

  • }

Connector C

C

Component D

Using Prism-MW

Component D sends an event

Event e = new Event (“Event_D”);

e.addParameter("param_1", p1);

send (e);

Architecture - DEMO

Send (e)

CD 2004


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