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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

slide6

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

slide8

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

slide9
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

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

slide13

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

slide14

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

slide19

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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