1

Distributed Systems

Alexis Delis

ad@di.uoa.gr

Monday 6:00-9:00

Spring 2002

www.di.uoa.gr/~ad/MDE519.html

2

Grades - Evaluation

Final Examination: 35%In-class Presentations & Homeworks: 30%

Project(s): 35%

Book: A.S. Tanenbaum, M. van Steen, Distributed Systems, Prentice Hall, 2002.

Other:Papers (available from the course’s WWW site)

3

Definition of a Distributed System

A distributed system is:

A collection of independent computers that appears to its

users as a single coherent system.

4

Definition of a Distributed System

A distributed system is organized as middleware.Note that the middleware layer may extend over multiple machines.

Examples: Workflow Systems, WWW-services (URL)

1.1

5

Goals of Distributed Systems

• connecting users with resources• transparency• openess • scalability

6

Transparency in a Distributed System

Different forms of transparency in a distributed system.

Transparency Description

AccessHide differences in data representation and how a resource is accessed

Location Hide where a resource is located

Migration Hide that a resource may move to another location

RelocationHide that a resource may be moved to another location while in use

ReplicationHide that a resource may be shared by several competitive users

ConcurrencyHide that a resource may be shared by several competitive users

Failure Hide the failure and recovery of a resource

PersistenceHide whether a (software) resource is in memory or on disk

7

Openness

Open DS: a system that offer services according to Standard Rules.

Such rules are described in terms of protocols

IDLs help in the description of such protocols.

Interoperability?Portability?Difference between the two?

8

ScalabilityNumerous “definitions” of scalability system can be scalable in terms of size

Add more users/resources into the system

Geographically Scalable systemUsers/resources may lie far apart

Administratively ScalableEasy to manage even if it spans multiple orgs.

GOLDEN RULE: as system becomes scalable in one of these

three dimension exhibits loss in performance.

9

Scalability Problems

Examples of scalability limitations.

Concept Example

Centralized services A single server for all users

Centralized data A single on-line telephone book

Centralized algorithmsDoing routing based on complete information

10

Scaling Techniques

asynchronous communication filling (database) forms. distribution (take a component, break into smaller pieces, spread these components across the system

Example: DNS – Domain Name Service.Division in (non-overlapping) zones – domains

11

Scaling Techniques

1.4

The difference between letting:

a) a server (character/string-based communication) or

b) a client check forms as they are being filled (bulk uploading).

12

Scaling Techniques

1.5

An example of dividing the DNS name space into zones.

13

Scalability - Caching

Generally Good Idea: Replicate (data/services)

Replication increases availability (of systems)

Caching (difference from replication?)

Main problem with caching/replication? Is this a serious problem? CDNs (how do they do it?)

14

Hardware Concepts

1.6

Different basic organizations and memories in distributed computer systems

15

Multiprocessors

A bus-based multiprocessor.

1.7

16

Multiprocessors

a) A crossbar switch (n*n crosspoint switches needed)

b) An omega switching network (low latency problem)

c) How to avoid latency? use hierarchical schemes: NUMA (NonUniform Memory Access)

1.8

17

Homogeneous Multicomputer Systems(building is “easy”-problem:interconnection network)

a) Bus-based (FDDI/ Fast-Ethernet /Gigabit network )b) Grid (switched based; messages are routed via the interconnection network)c) Hypercube(switched based; four dimensional (b); two ordinary cubes with 8

vertices and 12 edges)

1-9

Homogeneous Multi-computers: System Area Networks (SANs)

18

Switched Multi-computersCan vary significantly…

From…

• Massively Parallel Processors ($$ MPP – CM5, IBM SP2 etc.)

To..

• Clusters/Networks of Workstations (cheap$ - COWs or NOWs)

19

Software Concepts

An overview between • DOS (Distributed Operating Systems)• NOS (Network Operating Systems)• Middleware

System Description Main Goal

DOSTightly-coupled operating system for multi-processors and homogeneous multicomputers

Hide and manage hardware resources

NOSLoosely-coupled operating system for heterogeneous multicomputers (LAN and WAN)

Offer local services to remote clients

MiddlewareAdditional layer atop of NOS implementing general-purpose services

Provide distribution transparency

20

Uniprocessor Operating Systems

Separating applications from operating system code through a microkernel.

1.11

21

Multiprocessor Operating Systems

A monitor to protect an integer against concurrent access.

monitor Counter {

private:

int count = 0;

public:

int value() { return count;}

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

void decr() { count = count – 1;}

}

22

Multiprocessor Operating Systems (2)

A monitor to protect an integer against concurrent access, but blocking a process.

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;

}

}

23

Distributed Shared Memory Systems (DSM)

a) Pages of address space distributed among four machines

b) Situation after CPU 1 references page 10

c) Situation if page 10 is read only and replication is used

Trick: replicate pages that are referenced frequently!Another: replicate all pages (??) – problems? Solutions?

24

Distributed Shared Memory Systems•Always an issue: size of a page in DSM – why?•Large sized page are potentially good but they may entail false sharing•Having data belonging to two independent processes in the same page…

25

Network Operating System

General structure of a network operating system.

1-19

26

Network Operating System

Two clients and a server in a network operating system.

• Services allowed to users…

• rlogin machineA

• rcp machineA:file1 machineB:file2

• ftp, http, sftp, ssh, etc.

1-20

27

Network Operating System

Different clients may mount the servers in different places.

1.21

•Issue of FS mount-ing

28

Positioning Middleware

General structure of a distributed system as middleware.

1-22

29

Middleware and Openness

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.

1.23

30

Comparison between Systems

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

ItemDistributed OS

Network OS

Middleware-based OSMultipro

c.Multicomp

.

Degree of transparency

Very High High Low High

Same OS on all nodes

Yes Yes No No

Number of copies of OS

1 N N N

Basis for communication

Shared memory

Messages FilesModel

specific

Resource management

Global, central

Global, distributed

Per node Per node

Scalability No Moderately Yes Varies

Openness Closed Closed Open Open

31

Clients and Servers

General interaction between a client and a server.

1.25

32

An Example Client and Server

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

33

An Example: The Server

A sample server.

34

An Example: The Client

A client using the server to copy a file.

1-27 b

35

Three Processing Levels

The general organization of an Internet Search Engine into three different layers

1-28

36

Multitiered Architectures

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

1-29

37

Multitiered Architectures

An example of a server acting as a client.

1-30

38

Modern Architectures

An example of horizontal distribution of a Web service.

1-31

39

Ongoing (Research) Work

• DSs based on Horizontal Distribution(of data/services)

• DSs based on Horizontal and/or Vertical Distribution (of data/services)

• Peer-to-Peer– Distributions of data– Services (indexing, querying, TP processing)– Self-organizing systems