© city university london, dept. of computing distributed systems / 2 - 1 distributed systems...

© City University London, Dept. of Computing Distributed Systems / 2 - 1

Distributed Systems

Session 2: Distributed Software Engineering

Christos KloukinasDept. of Computing

City University LondonSoftware Engineering: the study of techniques used to produce high-quality software


Outline

0 LAST Session Summary + additional material.

1 Motivation

2 The CORBA Object Model

3 The OMG Interface Definition Language (IDL)

4 Other Approaches

5 Summary


Summary & Key Points of Lecture 1

What is a Distributed System? Adoption of DS is driven by Non-Functional

Requirements Distribution needs to be transparent to users

and application designers Transparency has several dimensions Transparency dimensions depend on each

other


Definition

A distributed system consists of a collection of autonomous computers, connected through a network and distributed operating system software, which enables computers to coordinate their activities and to share the resources of the system, so that users perceive the system as a single, integrated computing facility.

Certain common characteristics can be used to assess distributed systems: Resource Sharing, Openness, Concurrency, Scalability, Fault Tolerance, and Transparency


Distributed System Types (Enslow 1978)

Fully Distributed

Data

Processors

Control

Fully replicated

Not fully replicated master directory

Local data, local directory

Master-slave

Autonomous transaction based

Autonomous fully cooperative

Homog. specialpurpose

Heterog.specialpurpose

Homog.generalpurpose

Heterog.generalpurpose


Dimensions Of Transparency

Scalability Transparency

Migration Transparency

Access Transparency

Performance Transparency

Replication Transparency

Location Transparency

Failure Transparency

Concurrency Transparency


1.3 Model of a Distributed System

Component 1 Component n

Middleware

Network Operating System

Hardware

Host 1

Component 1 Component n

Middleware

Network Operating System

Hardware

Host n

..

..

………...

Network


Middleware Examples

Transaction-oriented» IBM CICS

» BEA Tuxedo

» IBM Encina

» MS Transaction Server

Message-oriented» MS Message Queue

» NCR TopEnd

» IBM MQSeries

» Sun Tooltalk

» Sun JavaSpaces

Procedural» Sun ONC

» Linux RPCs

» OSF DCE

Object-oriented» OMG CORBA

» Sun Java/RMI

» Microsoft COM

» Sun Enterprise Java Beans


0.3 Client-Server Computing(O’Leary 2000)

A client is defined as a requester of services A server is defined as a provider of services A single machine can be both a client and a

server depending on the software configuration


0.4 Client-Server (O’Leary 2000)

Processing can be improved because client and server share processing loads

» Client/server computing considers that the client has computing power that is not being used

» Fundamental idea is to break apart an application into components that can run on different platforms

Thin vs. Fat Clients: » a thin client has most of the functionality with server;

» a fat client has most of the functionality with the client.


0.5 Two tier architectures

The user system interface is usually located in the user's desktop environment.

Database management services are usually in a server that is a more powerful machine that services many clients.

Processing management is split between the user system interface environment and the database management server environment.

The database management server provides stored procedures and triggers.

Good for LAN with work group users < 100


0.6 Three-Tiered Architecture

Three Tiered Architecture is an information model with distinct pieces -- client, applications services and data sources -- that can be distributed across a network.

Client Tier -- The user component displays information, processes, graphics, communications, keyboard input and local applications.

Applications Service Tier -- A set of sharable multitasking components that interact with clients and the data tier. It provides the controlled view of the underlying data sources.

Data Source Tier -- One or more sources of data such as mainframes, servers, databases, data warehouses, legacy applications etc.


0.7 Examples of three tier architectures

Three tier architecture with transaction processing monitor technology

Three tier with message server Three tier with an application server Three tier with an ORB architecture( e.g CORBA) Distributed/collaborative enterprise architecture.


ORB

CORBA IIOPO

RB

ORB

ORB

ORB

DBMS

Lotus Notes

TP Monitors

Tier 2Server Objects

Tier 1View Objects Legacy Applications

Tier 3

Business Objects

0.8 Three Tier Client/Server Object Style


1 CORBA – Motivation & Overview

Distributed Systems consist of multiple components.

Components are heterogeneous. Components still have to be interoperable. There has to be a common model for

components, which expresses» component states,

» component services, and

» interaction of components with other components.


1.1 Example1: Java Object Model & Java Language

Object»Runtime entity instance of class

Interface»declare a set of methods for a Java object

without implementation Method Invocation

»primitive type passed by value»object references passed by value


1.2 Ex 2: Distributed Object Model (Wolrath et al)

Remote object» object whose methods can be accessed from another address space

Remote interface» an interface that declares the methods of a remote object

throws Remote Exception to deal with different failure models

RMI» non-remote object passed by value

» remote object passed by remote reference


1.3 CORBA Object Model & OMG IDL

Model describes components, states, interactions and other concepts

OMG/IDL is a language for expressing all concepts of the CORBA object model.» separation of interface from implementation

» Enables interoperability and transparency

» IDL compiles into client stubs and server skeletons

» Stubs and skeletons serve as proxies for clients and servers, respectively


1.4 CORBAClient

Object Request Broker

Client StubClient Stub

Request

CORBA Object Implementations

CORBA ServicesCORBA Services

C++ Ada Cobol SmalltalkJavaC

Server SkeletonServer Skeleton

IDLIDL IDLIDL IDLIDL IDLIDL IDLIDL IDLIDL

C++ Ada Cobol SmalltalkJavaC


1.5 Example1: StockQuoter IDL Interface

module Quoter {//stock quoter server, some interface to query the prices of

stock exception Invalid_Stock_Symbol {};

interface Stock; interface Stock_Factory { Stock get_stock (in string stock_symbol) raises (Invalid_Stock_Symbol);

}; interface Stock {

readonly attribute string symbol; // Get the stock symbol. readonly attribute string full_name; // Get the name. double price (); // Get the price }; };


2.3 Example 2: ATM Controller


Teller Controller IDL Definition

interface ATM;

interface TellerCtrl {

typedef sequence<ATM> ATMList;

exception InvalidPIN;

exception NotEnoughMoneyInAccount {...};

readonly attribute ATMList ATMs;

readonly attribute BankList banks;

void accept_request(in Requester req,

in short amount)

raises(InvalidPIN,NotEnoughMoneyInAccount);

};


2 The CORBA Object Model

Components objects. Component state object attributes.

Usable component services object operations.

Component interactions operation execution requests.

Component service failures exceptions.


3 The OMG Interface Definition Language OMG/IDL is a language for expressing all concepts of the CORBA

object model.

IDL is a 'contractual' language that lets you specify a component's (object's) boundaries and its interfaces with potential clients

CORBA IDL is language neutral and totally declarative, i.e., it does not define implementations details

Provides operating system and programming language independent interfaces to all services and objects that reside on the CORBA bus.

Different programming language bindings are available. (We’ll

work with Java)


2.1 Types of Distributed Objects

Attributes and operations and exceptions are properties defined in object types.

Object types are those properties that are shared by similar objects. Only their identity and values of their attributes differ.

Objects may export these properties to other objects.

Objects are instances of types.

Object types are specified through interfaces that determine the operations that clients can request, that is, they define a contract that binds the interaction between client and sever objects.


3.1 Types

A type is one of the following: Atomic types

(void, boolean, short, long, float, char, string), Object types (interface), Constructed types:

» Records (struct),

» Variants (union), and

» Lists (sequence), or Named types – aliases (typedef).


3.1 Types (Examples)

struct Requester {

int PIN;

string AccountNo;

string Bank; };



2.2 Attributes

Attributes have a (unique) name and a type Type can be an object type or a non-object type

(e.g., Boolean values, characters or numbers). Attributes are readable by other components Attributes may or may not be modifiable by other

components (readonly). Attributes correspond to one or two operations

(get/set). Attributes are declared within an interface. Attribute name must be unique within interface.


2.2 Attributes (Examples)



readonly attribute string symbol; readonly attribute string full_name;


2.3 Operations

Operations modify the state of an object or just compute functions

Used for service requests Operations have a signature that consists of

» a name,

» a list of in, out, or inout parameters,

» a return value type (result) or void if none, and

» a list of exceptions that the operation can raise.


2.3 Operations (Examples)


in short amount)

raises(InvalidPIN,

NotEnoughMoneyInAccount);

short money_in_dispenser(in ATM dispenser)

raises(InvalidATM);


2.4 Operation Execution Requests

A client object can request an operation execution from a server object.

Operation request is expressed by sending a message (operation name) to server object.

Conceptually, an object request is a triple consisting of an object reference, the name of an operation and a list of actual parameters.

Parameters are marshaled (packaged and transmitted, e.g., serialisation )

Client have to react to exceptions that the operation may raise.


2.5 Exceptions Service requests may not be executed properly. Exceptions have a unique name. Exceptions may declare additional data structures. Exceptions are used to explain (and locate) the reason

of failure to the requester of the operation Operation execution failures may be

» generic (system), raised by the middleware, e.g., an unreachable server object; or

» specific, raised by the server object, when the execution of a request would violate the object’s integrity, e.g., not enough money in a bank account.


2.5 Exceptions cont…


exception InvalidATM;

exception NotEnoughMoneyInAccount {

short available;

};

Specific Failures may be explained by specific exceptionsExample


3.5 Interfaces

In distributed systems, services are syntactically specified through interfaces that capture the names of the functions available together with types of the parameters, return values, possible exceptions, etc.

There is no legal way a process can access or manipulate the state of an object other than invoking methods made available to it through an object’s interface.


3.5 Interfaces

Attributes, exceptions and operations are defined in interfaces.

Interfaces have an identifier, which denotes the object type associated with the interface.

Interfaces must be declared before they can be used.

Interfaces can be declared in a forward manner


3.5 Interfaces (Example)

interface ATM; /* forward declaration! */

interface TellerCtrl {


exception InvalidATM; exception InvalidPIN;

exception NotEnoughMoneyInAccount

{short available;};




in short amount)

raises(InvalidPIN,NotEnoughMoneyInAccount);

};


3.6 Modules

A single global name space for all identifiers is unreasonable.

IDL includes Modules to restrict visibility of identifiers.

Access to identifiers from other modules by qualification with module identifier:

moduleName::identifierName


3.6 Modules (Example)

module Bank {

interface AccountDB {};

};

module ATMNetwork {

typedef sequence<Bank::AccountDB> BankList;


interface ATM;

interface TellerCtrl {...};

};


2.6 Sub-typing/Inheritance

Object types are organised in a type hierarchy. Subtypes inherit attributes, exceptions and operations from

their supertypes. Subtypes can add more specific properties. Subtypes can redefine inherited properties. Advantages:

» Reuse

» Changes are easier to manage

» Abstraction makes designing DS elegant and easier to understand

» Enables polymorphism (an attribute or parameter can refer to instances of different types).


3.7 Inheritance

Notation to define object type hierarchy.

Type hierarchy has to form an acyclic graph.

Type hierarchy graph has one root called (Object).

Subtypes inherit the attributes, exceptions and operations of all super-types.


3.7 Inheritance (Examples)

interface Controllee;

interface Ctrl {

typedef sequence<Controllee> CtrleeList;

readonly attribute CtrleeList controls;

void add(in Controllee new_controllee);

void discard(in Controllee old_controllee);

};

interface ATM : Controllee {...};

interface TellerCtrl : Ctrl {...};


3.7 Multiple Inheritance

An object type can inherit from more than one super-type. May cause name clashes if different super-types export the

same identifier. Example:

interface Set {

void add(in Element new_elem);

};

interface TellerCtrl:Set, Ctrl { ... }; Name clashes are not allowed!


3.8 Redefinition

Behaviour of an operation as defined in a super-type may not be appropriate for a subtype.

Operation can be re-defined in the subtype. Binding messages to operations is dynamic. Operation signature must not be changed. Operations in (abstract) super-types are not

implemented.


3.8 Redefinition (Example)

interface Ctrl {

void add(in Controllee new_controllee);

};

interface TellerCtrl : Ctrl {

void add(in ATM new_controllee);

};

TellerCtrl cannot redefine add’s interface – only its behaviour!

It cannot overload it either!


3.9 Polymorphism

Objects can be assigned to an attribute or passed as a parameter, even though they are instances of subtypes of the attribute’s/parameter’s respective type.

Attributes, parameters and operations are polymorph.

Example:Using Polymorphism, instances of type ATM can be inserted into attribute controls that Ctrl has inherited from Ctrl.


2.7 Problems of the Model

Interactions between components are not defined in the model.

No concept for abstract or deferred types. Model does not include primitives for the

behavioural specification of operations. Semantics of the model is only defined

informally.


4 Other Approaches: (D)COM

(D)COM is Microsoft’s Distributed Component Object Model (http://microsoft.com/com/).

Evolved from OLE/COM. Weaker than CORBA object model since it

» does not support inheritance,

» does not have a strong type system and

» does not support exceptions.


4. Other Approaches: Darwin

Experimental language developed at Imperial Collegehttp://www-dse.doc.ic.ac.uk/Research/Darwin

Supports dynamic configuration of distributed components.

Graphical and textual notation. Components provide and require services. Primitive for binding service requester to service

provider. Formal semantics based on Milner’s -calculus.


5 Summary

Client-Server vs n-Tier Architecture Why do we need a component model? What are the primitives of the CORBA object

model? What is OMG/IDL? What are the strengths and weaknesses of the

CORBA approach?


EXTRA MATERIAL

(Not to be examined)


0.2 Further Examples:Computational Grids

Inspired by the electrical power grid’s pervasiveness, reliability and easy to use, computer scientists in the mid-90s began exploring the design and development of an analogous infrastructure called the

computational power Grid


Vision

To build an environment that enables

» sharing, » selection,» aggregation of a wide variety of

geographically distributed resources including» supercomputers, » storage systems, data sources, and » specialised devices owned by different organisations for

solving large-scale resource intensive problems in science, engineering, and commerce (Buyya, 2002).


0.2 Computational Grid

Motivation: Small computing resources such as PCs have the potential to provide vast computing power when connected. And yet…

Many of these resources lie idle most of the time. Millions of online-PCs are only involved in tasks like word processing or browsing the Internet. The computing resources of many organisations are often severely under-utilised, specially outside of peak business hours.

At the same time, there are many individuals and organisations that have intensive computations to perform but only have limited access to resources that are available

to execute them.


Possible exploitation (Source: IBM)

Analyze the value of an investment portfolio in minutes rather than hours?

Unite research teams with others around the world to take advantage of the most up-to-date knowledge?

Significantly accelerate the drug discovery process? Scale your business to meet cyclical demand? Cut the design time of your products in half while reducing the

instances of defects?

Source: http://www-1.ibm.com/grid/about_grid/index.shtml

© City University London, Dept. of Computing Distributed Systems / 2 - 56DOE X-ray grand challenge: ANL, USC/ISI, NIST, U.Chicago

tomographic reconstruction

real-timecollection

wide-areadissemination

desktop & VR clients with shared controls

Advanced Photon Source

Online Access to Scientific Instruments

archival storage

© City University London, Dept. of Computing Distributed Systems / 2 - 57Image courtesy Harvey Newman, Caltech

Data Grids forHigh Energy Physics

Tier2 Centre ~1 TIPS

Online System

Offline Processor Farm

~20 TIPS

CERN Computer Centre

FermiLab ~4 TIPSFrance Regional Centre

Italy Regional Centre

Germany Regional Centre

InstituteInstituteInstituteInstitute ~0.25TIPS

Physicist workstations

~100 MBytes/sec

~100 MBytes/sec

~622 Mbits/sec

~1 MBytes/sec

There is a “bunch crossing” every 25 nsecs.

There are 100 “triggers” per second

Each triggered event is ~1 MByte in size

Physicists work on analysis “channels”.

Each institute will have ~10 physicists working on one or more channels; data for these channels should be cached by the institute server

Physics data cache

~PBytes/sec

~622 Mbits/sec or Air Freight (deprecated)




Caltech ~1 TIPS

~622 Mbits/sec

Tier 0Tier 0

Tier 1Tier 1

Tier 2Tier 2

Tier 4Tier 4

1 TIPS is approximately 25,000

SpecInt95 equivalents


Network for EarthquakeEngineering Simulation

NEESgrid: national infrastructure to couple earthquake engineers with experimental facilities, databases, computers, & each other

On-demand access to experiments, data streams, computing, archives, collaboration

NEESgrid: Argonne, Michigan, NCSA, UIUC, USC


Community =» 1000s of home computer

users

» Philanthropic computing vendor (Entropia)

» Research group (Scripps)

Common goal= advance AIDS research

Home ComputersEvaluate AIDS Drugs


Computational Grids Resourses

Global Grid Forum (http://www.gridforum.org/): community-initiated forum of 5000+ individual researchers and practitioners working on distributed computing, or "grid" technologies

GridComputing (http://www.gridcomputing.com/) myGrid (http://www.mygrid.org.uk/), an EPSRC project Platforms:

» Globus (http://www.globus.org/)» Unicore (http://www.unicore.org/)» Load Sharing Facility (http://www.platform.com/)

© city university london, dept. of computing distributed systems / 2 - 1 distributed systems...

Documents

computing distributed

distributed systems

distributed system component

transparency dimensions

network slide

summary slide

highquality software

software configuration