Rapid Prototyping and Deployment of Distributed Web / Grid Services in a Service Oriented Architecture using Scripting

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Rapid Prototyping and Deployment of

Distributed Web / Grid Services in a

Service Oriented Architecture using

Scripting

Thesis Proposal

Harshawardhan Gadgil

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Outline

n

Motivation

n

Literature Survey

n

Re

search Issues

n

HPSearch Architecture

n

Contributions and Milestones

n

Applications

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Motivation

n

Critical Infrastructure systems connect disparate data

sources, high-performance computing applications

and visualization services for real-time data

processing.

n

Real-time data processing

n

Results required in real-time

. Data available in streams.

Requires pre-processing (e.g. filtering data to remove

unwanted parts).

n

Scalability

n

Potentially large number of data sources (Static,

dynamic) or data processing elements (services)

n

Unpredictable behavior

n

Fault-tolerance a key factor. E.g. Incorporate new data

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Motivation (contd.)

n

System Management

n

Increasing complexity of application implies

more metadata.

n

Proper management required to ensure

smooth functioning of the system.

n

Require easy access to manage system

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Motivatio

Streaming data Processing

n Critical Infrastructure systems

(Scientific applications)

n Real-time streaming sources exist

E.g. sensors, satellite stations

OR

Static data sources (databases containing previously warehoused observations)

n Data filtering / transformation essential in most cases for

converting data to proper format for processing application

n Real-time processing required.

Crucial for critical infrastructure applications

n Audio/video applications.

n Real-time sources

E.g. Collaborative sessions OR

Static data source (stored A/V files)

n Pre-processing required to modify A/V characteristic

n Format (encoding) / bit rate

(quality) etc…

n Real-time processing crucial for

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Outline

n

Motivation

n

Literature Survey

n

Re

search Issues

n

HPSearch Architecture

n

Contributions and Milestones

n

Applications

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Literature Survey

n

Services (Web / Grid)

n

Scripting Languages

n Benefits

n Possible problems

n

Handling data flow in applications

n File-based vs. Streaming

n

Workflow Systems

n Enable gluing High performance components n GUI – based building and programming flavor

n

Component based architectures

n

Messaging systems (for High throughput data

transfer)

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Service

n “Service is a logical manifestation of a logical /physical resource (DB,

programs, devices, humans etc) and/or some application logic exposed to network”

- Web Service Grids: An Evolutionary Approach (2004) n Web Services

n Simple mechanism for distributed computing n Language independent, firewall friendly

n Grid Services

n Are essentially Web Services

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Scripting Languages

n Benefits

n Enables Rapid prototyping (less code size and development time) n Less effort to

n Perform complex tasks

n Interface with OS (hosting environment) n Glue code to tie programs

n Usually portable

n Primarily for Plugging existing components together

n However, some disadvantages too

n Weak typing

n Less structure, difficult to maintain

n Some examples

n Rhino – Java script for JAVA n Perl, VBScript, (P/J)ython

n Scripting vs GUI builders

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Scripting Environment

Hosting Services

n

OGSI:Lite & WSRF:Lite

n

Based on Perl

n

Rapidly deploy grid services

n

Matlab / Jython from GEODISE

n

GEODISE – Suite of CAD integrated with distributed

grid-enabled computing, data, analysis and knowledge

resources

n

Uses Matlab to provide programatic access to GEODISE

functions along with an existing suite of Matlab tools

n

Jython used to provide a hosting environment using

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Data flow in applications

n

Real-time processing required.

n

Typically data transfer involves temporary storing of

data. This data may be transferred using files (E.g.

Grid FTP).

n

Every component of the chain processes data from

input file, writes processed data to output file.

n

Time and Space critical in real-time applications hence

file-based transfer is undesirable for real-time

applications.

n

Tools to automate data transfer and invoke

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Workflow Architectures

n

Triana – Graphical PSE to compose scientific

applications

n Composed of one or more Triana engines.

n Distributed version

n Data transfer takes place using JXTA pipes.

n

Taverna

n Can interact with arbitrary services.

n Plugins to mediate / operate the service in each case

n Uses XScufl (derived from WSFL) workflow language.

n

Kepler

n Java packages for designing and execution.

n Has a graphical interface for composing complex workflows

n Can wrap existing code written in different languages. For e.g. Perl

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Component Architectures

n

XCAT @ IU-Extreme

n

Connects components (Provides and Uses ports)

n

Jython based scripting to do application

management tasks (create application, set

properties, invoke application)

n

Data transfer by GridFTP between components,

Globus Reliable File Transfer (fault tolerance).

n

Many other systems

n

Focus mainly on invocation of services as in a

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Messaging systems

n JXTA – P2P middleware, JMS for communication

n Pastry

n Fault tolerant P2P middleware

n Based on Distributed Hash tables

n No real-time routing possible

n NaradaBrokering @ IU – http://www.naradabrokering.org

n Event- brokering system designed to run on a large network of

co-operating brokers.

n Implements high-performance protocols (message transit time < 1

ms per broker)

n Order-preserving optimized message transport

n Interface with reliable storage for persistent events

n Fault tolerant data transport

n Support for different underlying transport implementations such as

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System Management

n

Increasing complexity of systems implies increasing

amount of metadata to be managed

n

Provide access to

System

and management of

System metadata

- WS - Management

n

E.g. Performance metrics, logs, service metadata

n

Require ability to query system data and take

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Outline

n

Motivation

n

Literature Survey

n

Research Issues

n

HPSearch Architecture

n

Contributions and Milestones

n

Applications

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Research Issues

n Support for streaming data processing.

n Data transfer and processing in real-time

n Data transfer to be carried on between the end-points

(sender and recipient) without the flow engine mediating

- Grid Services Flow Language

n Design a run-time system that allows merging data sources,

data filtering and processing applications and visualization tools in a service-oriented architecture

n Assume all components available as Web (Grid) services. n Scalability an issue – Addition of data sources or processing

applications (Services) should not degrade the system performance

n Fault-tolerance – Services and data sources may be lost.

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Research Issues

n

System Management Interface - Allow access to

system and manipulate the characteristics of system

by querying system metadata

n

Create Virtual topology for application deployment

n

Query performance metrics to design policies to

change routing substrate characteristics (E.g. Add new

brokers or links between existing brokers to aid

efficient routing)

n

Discover Services / brokers / topics of interest.

n

To dynamically rewire components with data

streams.

n

Replay events

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Outline

n

Motivation

n

Literature Survey

n

Re

search Issues

n

HPSearch Architecture

n

Contributions and Milestones

n

Applications

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HPSearch

n Binds URI to a scripting language

n We use Mozilla Rhino (A Javascript implementation, Refer:

http://www.mozilla.org/rhino), but the principles may be applied to any other scripting language

n Every Resource may be identified by a URI and HPSearch allows us to manipulate the

resource using the URI.

n For e.g. Read from a web address and write it to a local file

x = “http://trex.ucs.indiana.edu/data.txt”; y = “file:///u/hgadgil/data.txt”;

Resource r = new Resource(“Copier”);

r.port[0].subscribeFrom(x); /* read from */

r.port[0].publishTo(y); /* write to */

f = new Flow();

f.addStartActivities(r); f.start(“1”);

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HPSearch (contd.)

n Currently provide bindings for the following n file://

n socket://ip:port n http://, ftp:// n topic://

n jdbc:

n Host-objects to do specific tasks

n WSDL – invoke web-services using SOAP

n PerfMetrics – Bind NaradaBrokering performance metrics.

Store published metrics and allow querying

n Resource – Every data source / filter / sink is a resource. n Flow – To create a data flow between resources. Useful for

creating data flows

n For more information, visit

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Architecture

n Consists of

n SHELL

n Front end to scripting.

n TASK_SCHEDULER (FLOW_ENGINE)

n Distributes tasks among co-operating engines for load-balancing

purposes.

n WSPROXY

-n An AXIS web service wraps an actual service. The behavior of the

service can be controlled by making simple WS calls to this proxy.

§ Can be controlled by any Workflow Engine

§ WSProxy handles streaming data communication on behalf of the service.

n Service only sees I/P and O/P streams. These could be files or a

remote data stream or even a file transferred via HTTP / FTP or results from a database query

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Architecture

n WSProxy - Interfaces

n Runnable

n More control over execution (start, suspend, resume, stop…)

n Basic idea (read block of data, process it, write it out)

n Ideal for designing quick filtering applications that process data

in streams.

n Wrapped

n Wrap an existing service (Executables [*.exe], Matlab scripts,

shell / Perl scripts etc…)

n Less control, can only start, stop

n Ideal for wrapping existing programs / services to expose as a

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So what is the overhead

Partial results as of now

n Taken on 1.6 GHz Pentium 4 machine w/ 256 MB RAM running

Java 1.4.1_02, NB version 0.98 rc2, Rhino 1.5R3

n Shell Init: 2085 mSec (average)

n Results from RDAHMM Script (26 lines, small script) takes about

15 mSec (average per line) to execute

n Task distribution (2 engine, 4 tasks) 3897.645 mSec

n WSProxy (Init – depends on number of streams to initialize) 700

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Outline

n

Motivation

n

Literature Survey

n

Re

search Issues

n

HPSearch Architecture

n

Contributions and Milestones

n

Applications

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Contribution of this Thesis

n Stream and Service Management - Program data-flows

n Incorporate static and dynamic data sources

n WSProxy ensures that data flows directly between components

(Services) without the HPSearch engine mediating. Useful for streaming large amounts of data without clouding the controller.

n Scalable ?

n We use NB as our messaging substrate which can handle large number

of clients

n All components (data sources, data processing and visualization

applications) are clients. HPSearch manages streams and connects and steers components.

n Fault – tolerant ?

n Data source, data filter (processing application) failure possible.

n HPSearch can use the discovery service to invoke new services (in lieu

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Contribution of this Thesi

(contd.)

n System Management - Scripting admin tasks

n Creating network (virtual broker network) topology n Querying Performance metrics

n Topic / Broker discovery

n Rapid deployment of applications

n Deploy Network topology n Set Application properties n Deploy Application

n In short:

n Provide alternative programmatic (scripting) access to

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Milestones

n Implement WS front-end to shell

n Remotely submit a script for execution, possibly through a portal

n WSProxy / Handler: Fault tolerance to handle situations when

n The machine hosting the WSProxy dies

n The broker which is used by the proxy dies n The HPSearch Engine dies

n Design Application Interface

n Allow users to create applications using this interface

n Set Application properties, Allow modification of application

properties at runtime using scripting

n NB Admin objects

n

NaradaBroker

,

PerfMetrics

, NBDiscovery,

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Milestones (contd.)

n

Design

stream negotiation module

to allow

WSProxy to negotiate stream characteristics

n

Select best possible transport and other QoS

elements for data transfer between two

services (for a particular stream)

n

Applications

- To demonstrate the use

n

Audio / Video mixer application

n

Multiple data sources and data filtering

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Outline

n

Motivation

n

Literature Survey

n

Re

search Issues

n

HPSearch Architecture

n

Contributions and Milestones

n

Applications

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Applications

Streaming Data Filtering

GPS Data

Data Filter

Filters the input data to get

only the estimate and error

values

RDAHMM

Analyze the data

Matlab Plotting

Script Graph

HPSearch

Kernel

-TSE _Kernel

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trex.ucs.indiana.edu school.cs.indiana.edu

Applications

Creating Virtual Broker Network for deploying

applications

b = new NaradaBroker("school.cs.indiana.edu");

b.create(""); /* OR b.create("file:///u/hgadgil/alternateConfig.conf"); */

b.connectTo("156.56.104.170", "5045", "t", "");

b.requestNodeAddress("156-56-104-170.bl-dhcp.indiana.edu:5045", "0"); c = new NaradaBroker("trex.ucs.indiana.edu");

c.create("");

c.connectTo("156.56.104.170", "5045", "t", "");

c.requestNodeAddress("tcp://156-56-104-170.bl-dhcp.indiana.edu:5045", "0");

156.56.104.

170 _{school.cs.indian}

a.edu

trex.cs.indiana. edu

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Applications

Invoking Arbitrary Web Services

approved = false;

userID = "111-22-3333"; if(loanAmt < 10000)

approved = true; else {

wsRA = new WSDL("http://www.riskAssessor.com/services/RiskAssessor"); risk = wsRA.invoke("assessRisk", userID, loanAmt);