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Distributed Systems CS 3850 Soufiane Noureddine Lectures MWF 14:00 – 14:50 (PE207D) Office Hours MW 11:00 – 12:00 (C520) Introduction Chapter 1 Computer Networks

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Distributed SystemsCS 3850Soufiane NoureddineLecturesMWF 14:00 – 14:50 (PE207D)Office HoursMW 11:00 – 12:00 (C520)


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Introduction

Chapter 1


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Computer Networks

A collection of computers communicating through an underlying network is called a computer network (in contrast to a single-processor system)

Local Area Network: LAN

10 to 1000 Mb/sec

Wide Area Network: WAN

64 kbps to gigabits/sec


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Definition of a Distributed System (1)

  • A distributed system is:

  • A collection of independent computers that appears to its users as a single coherent system.

  • A. Tanenbaum


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Definition of a Distributed System (2)

“You know you have one when the crash of a computer you never heard of stops you from getting any work done.”

L. Lamport


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Organization of a Distributed System

1.1

A distributed system organized as middleware.Note that the middleware layer extends over multiple machines.


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Characteristics of a distributed System

 Differences between computers are hidden

 Communication between computers is hidden

 Internal organization of the system is hidden

 Single system image: interaction with the system is independent from location (and time)

 Ease of extension

 High availability


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Examples of distributed Systems

  • Network of workstations + Pool of processors:

  • - Single file system (uniform naming scheme)

  • - Processors are allocated dynamically when needed (load sharing)

  • - System acts like a single-processor system

  • 2. Workflow systems

  • - Orders arrive dynamically (e.g. via laptops, cellular phones)

  • - System assigns orders to the corresponding departments and initiates the needed business processes and users are unaware of the internal flow of orders

  • - System acts like a centralized database

  • WWW

  • - No need to know where documents are stored (at least in theory)

  • - Accessing remote documents is like accessing local ones


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Goals of distributed Systems

  • Connecting users and resources:

  •  consequence: communication and collaboration (e.g. joint editing)

  •  issue: security

  • 2. Openness

  • - Services should obey to standard rules specifying syntax and semantics

  • - Services are specified in general as interfaces in an interface definition language

  • - IDL includes rather syntax and no semantics

  • - Specification of interface should be completed and neutral (w.r.t. implementation)

  • - Openness promotes interoperability and portability

  • Transparency (see next slides)

  • Scalability (see next slides)


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Transparency in a Distributed System

Different forms of transparency in a distributed system.

Degree of transparency: More transparency means less performance

In reality: Systems are transparent only to certain degree


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Network

(e.g. Telecom)

Clients

Software Developers

e.g. Company

Network Provider


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Network

(e.g. Telecom)

Clients

Software Developers

e.g. Company

Company A

Company B

Network Provider


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Network

(e.g. Telecom)

Clients

Software Developers

e.g. Company

Company A

Company B

Network Provider


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Network

(e.g. Telecom)

Clients

Software Developers

e.g. Company

Company A

Company B

Network Provider


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Network

(e.g. Telecom)

Clients

Software Developers

e.g. Company

Company A

Company B

Network Provider


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Network

(e.g. Telecom)

Clients

Software Developers

e.g. Company

Applications

Operating System & Hardware

Network Provider


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Network

(e.g. Telecom)

Clients

Software Developers

e.g. Company

Applications

AEM: Availability Enhancing Middleware

Operating System & Hardware

Network Provider


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Scalability Problems

A system is scalable when it is easy to extend without loss of performance.

  • Examples of scalability limitations.

  • Centralized solutions tend to be non-scalable

  • Decentralized solutions promote scalability


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Decentralized Algorithms

  • No machine has complete information about the system state

  • Machines make decisions based only on local information

  • Failures of one machine does not ruin the whole algorithm

  • No assumption on the existence of a global time


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Scaling Techniques (1)

  • Ways to solve scalability problems:

  • Hide communication latencies (geographical scalability)

  • Use of distribution (in order to avoid bottlenecks)

  • Use of replication

  • Ad a)

    • Batch processing: Asynchronous communication instead of synchronous communication

    • Interactive applications: Reduce overall communication

      Example: Move part of computation from server to client (e.g. Java applet)


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Scaling Techniques (2)

1.4

  • The difference between letting:

  • a server or

  • a client check forms as they are being filled


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Scaling Techniques (3)

Ad b) Use of distribution

1.5

An example of dividing the DNS name space into zones.

Clientserver Z1: nl.vu.cs.fluit

Server Z1  Client: address of Z2

Clientserver Z2: vu.cs.fluit


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Scaling Techniques (4)

  • Ad c) Use of replication

  • Replication raises:

    • Availability: in general the primary goal

    • Performance:

  • By balancing the load among replicas

  • By locating replicas close to users/clients

  • Example: Caching (e.g. browser cache for used WWW pages)

  • Main issue in connection with replication: consistency


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Hardware Concepts

1.6

Different basic organizations and memories in distributed computer

systems


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Multiprocessors (1)

1.7

A bus-based multiprocessor.

Issues:

Scalability

Cache consistency


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Multiprocessors (2)

1.8

  • A crossbar switch: n2 switches!

  • An omega switching network: less switches



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Software Concepts

  • An overview of

  • DOS (Distributed Operating Systems)

  • NOS (Network Operating Systems)

  • Middleware


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Uniprocessor Operating Systems

1.11

Separating applications from operating system code through

a microkernel.


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Multiprocessor Operating Systems (1)

monitor Counter {

private:

int count = 0;

public:

int value() { return count;}

void incr () { count = count + 1;}

void decr() { count = count – 1;}

}

A monitor to protect an integer against concurrent access.


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Multiprocessor Operating Systems (2)

monitor Counter {

private:

int count = 0;

int blocked_procs = 0;

condition unblocked;

public:

int value () { return count;}

void incr () {

if (blocked_procs == 0)

count = count + 1;

else

signal (unblocked);

}

void decr() {

if (count ==0) {

blocked_procs = blocked_procs + 1;

wait (unblocked);

blocked_procs = blocked_procs – 1;

}

else

count = count – 1;

}

}

A monitor to protect an integer against concurrent access, but

blocking a process.


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Multicomputer Operating Systems (1)

1.14

General structure of a multicomputer operating system


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Multicomputer Operating Systems (2)

1.15

Alternatives for blocking and buffering in message passing.


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Multicomputer Operating Systems (3)

Relation between blocking, buffering, and reliable communications.


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Distributed Shared Memory Systems (1)

  • Pages of address space distributed among four machines

  • Situation after CPU 1 references page 10

  • Situation if page 10 is read only and replication is used

  • Replicating all pages:

  •  Coherence protocols:

  • a) strong (transparent)

  • b) weak (not transparent)


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Distributed Shared Memory Systems (2)

Page size: small  more communication overhead

large  less communication, but false sharing may occur

1.18

False sharing of a page between two independent processes.

Problem with DSM: not as efficient as expected


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Network Operating System - NOS (1)

1-19

General structure of a network operating system.

Main features: Independent operating systems

Services for accessing remote resources


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Network Operating System (2)

1-20

Two clients and a server in a network operating system.


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Network Operating System (3)

1.21

Different clients may mount the servers in different places.


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NOS vs DOS (3)

Distributed operating system:

Fully transparent

For homogeneous systems  computers are not independent More secure, but less scalable and less open

Network operating system:

Not transparent

For heterogeneous system  computers are independent

Easier to extend (e.g. adding a new node in the Internet)

Both do not really qualify as a distributed system!!!

 Solution: Middleware atop of a NOS hiding heterogeneity and improving transparency


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Positioning Middleware

1-22

General structure of a distributed system as middleware.

Middleware Services: rather a functionally complete set of services in order to hide heterogeneity, direct access to NOS is discouraged.


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Middleware and Openness

1.23

In an open middleware-based distributed system, the protocols used by each middleware layer should be the same, as well as the interfaces they offer to applications.

 implementations of the middleware should not use the NOS-provided protocols


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Comparison between Systems

A comparison between multiprocessor operating systems, multicomputer operating systems, network operating systems, and middleware-based distributed systems.


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Clients and Servers

1.25

General interaction between a client and a server.


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An Example Client and Server (1)

The header.h file used by the client and server.



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An Example Client and Server (3)

1-27 b

A client using the server to copy a file.


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Processing Level

1-28

The general organization of an Internet search engine into three different layers


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Multitiered Architectures (1)

1-29

Alternative client-server organizations (a) – (e).


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Multitiered Architectures (2)

1-30

An example of a server acting as a client.


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Modern Architectures

1-31

An example of horizontal distribution of a Web service.


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