240-322 cli/serv.: dist. prog./21 client/server distributed systems v objectives –explain the...

240-322 Cli/Serv.: Dist. Prog./2 1

Client/Server Distributed SystemsClient/Server Distributed Systems

ObjectivesObjectives– explain the general meaning of distributed explain the general meaning of distributed

programming beyond client/serverprogramming beyond client/server– look at the history of distributed programminglook at the history of distributed programming

240-322, Semester 1, 2005-2006

2. Distributed Programming Concepts


OverviewOverview1. Definition1. Definition

2.2. From Parallel to Distributed From Parallel to Distributed

3.3. Forms of Communication Forms of Communication

4. Data Distribution4. Data Distribution

5. Algorithmic Distribution5. Algorithmic Distribution

6. Granularity6. Granularity

7. Load Balancing7. Load Balancing

8. Brief History of Distributed Programming8. Brief History of Distributed Programming


1. Definition1. Definition

Distributed programming is the spreading of a Distributed programming is the spreading of a computational task across several programs, computational task across several programs, processes, or processors.processes, or processors.

Includes parallel (concurrent) and networked Includes parallel (concurrent) and networked programming.programming.

Definition is a bit vague.Definition is a bit vague.


2. From Parallel to Distributed2. From Parallel to Distributed

Most parallel languages talk about processes:Most parallel languages talk about processes:– these can be on different processors these can be on different processors oror on different on different

computerscomputers

The implementor may choose to add language The implementor may choose to add language features to explicitly say features to explicitly say wherewhere a process should run. a process should run.

May also choose to address network issues May also choose to address network issues (bandwidth, failure, etc.) at the language level.(bandwidth, failure, etc.) at the language level.

continued


Often resources required by programs Often resources required by programs are distributed, which means that the are distributed, which means that the programs must be distributed.programs must be distributed.

continued

240-322 Cli/Serv.: Dist. Prog./2 6continued


Network TransparencyNetwork Transparency

Most users want networks to be as Most users want networks to be as transparenttransparent (invisible) as possible:(invisible) as possible:– users do not want to care which machine is used to users do not want to care which machine is used to

store their filesstore their files

– they do not want to know where a process is runningthey do not want to know where a process is running


3. Forms of Communication3. Forms of Communication

1-to-1 communication1-to-1 communication

1-to-many communication1-to-many communication

continued

These can be supported on top of shared memory oror distributed memory platforms.

processes


many-to-1 communicationmany-to-1 communication

many-to-many communicationmany-to-many communication


4. Data Distribution4. Data Distribution

Divide input data between identical separate Divide input data between identical separate processes.processes.

Examples:Examples:– database searchdatabase search– edge detection in an imageedge detection in an image– builders making a room with bricksbuilders making a room with bricks


Boss-WorkersBoss-Workers

boss

workers(all database search engines)

send partpart of database

send answer


workers often need to talk to one anotherworkers often need to talk to one another

boss

workers (all builders)

send bricks

done

talking


Boss - Eager WorkersBoss - Eager Workers

boss

workers (all builders)

ask for bricks

send bricks

talking


Things to NoteThings to Note

The code is duplicated in every process.The code is duplicated in every process.

The maximum no. of processes depends on the The maximum no. of processes depends on the size of the task and difficulty of dividing data.size of the task and difficulty of dividing data.

Talking can be very hard to code.Talking can be very hard to code.

Talking is usually called communication, Talking is usually called communication, synchronisationsynchronisation or or cooperationcooperation

continued


Communication is almost always implemented Communication is almost always implemented using message passing.using message passing.

How are processes assigned to processors?How are processes assigned to processors?


5. Algorithmic Distribution5. Algorithmic Distribution Divide algorithm into parallel parts / processesDivide algorithm into parallel parts / processes

– e.g. UNIX pipese.g. UNIX pipes

collector washer

DrierStacker

dirtyplates

clean wetplates

wipe dryplates

dirty plateson table

plates incupboard


Things to NoteThings to Note

Talking is simple: pass data to next process Talking is simple: pass data to next process which ‘wakes up’ that process.which ‘wakes up’ that process.

Talking becomes harder to code if there are Talking becomes harder to code if there are loops.loops.

How to assign processes to processors?How to assign processes to processors?


Several Workers per Sub-taskSeveral Workers per Sub-task

Use both algorithmic and data distribution.Use both algorithmic and data distribution. Problems: how to divide data?Problems: how to divide data?

how to combine data?how to combine data?

collectorwasher

DrierStacker

Drier

Drier

collector


Parallelise Separate Sub-tasksParallelise Separate Sub-tasks

bricklaying

electricalwiring

plumbing

Build a house:

paint

b | (pl & e) | pt


6. Granularity6. Granularity

Amount of data handled by a process:Amount of data handled by a process:

Course grainedCourse grained: lots of data per process: lots of data per process– e,g, UNIX processese,g, UNIX processes

Fine grainedFine grained: small amounts of data per : small amounts of data per processprocess– e.g. UNIX threads, Java threadse.g. UNIX threads, Java threads


7. Load Balancing7. Load Balancing

How to assign processes to processors?How to assign processes to processors?

Want to ‘even out’ work so that each processor Want to ‘even out’ work so that each processor does about the same amount of work.does about the same amount of work.

But: But: – different processors have different capabilitiesdifferent processors have different capabilities

– must consider cost of moving a process to a processormust consider cost of moving a process to a processor(e.g. network speed, load)(e.g. network speed, load)


8. Brief History of (UNIX) 8. Brief History of (UNIX) Distributed ProgrammingDistributed Programming

1970’s: UNIX was a multi-user, time-sharing OS1970’s: UNIX was a multi-user, time-sharing OS– &, pipes&, pipes

– interprocess communication (IPC) on a single interprocess communication (IPC) on a single processorprocessor

mid 1980’s: System V UNIXmid 1980’s: System V UNIX– added extra IPC mechanisms: shared memory, added extra IPC mechanisms: shared memory,

messages, queues, etc.messages, queues, etc.

continued


late 1970's to mid 1980’s: ARPA late 1970's to mid 1980’s: ARPA – US Advanced Research Projects AgencyUS Advanced Research Projects Agency– funded research that produced TCP/IP, socketsfunded research that produced TCP/IP, sockets– added to BSD Unix 4.2added to BSD Unix 4.2

mid-late 1980’s: utilities developedmid-late 1980’s: utilities developed– telnettelnet, , ftpftp

– r* utilities: r* utilities: rloginrlogin, , rcprcp, , rshrsh

– client-server model based on socketsclient-server model based on sockets

continued


1986: System V UNIX1986: System V UNIX– released TL1, a set of socket-based libraries that released TL1, a set of socket-based libraries that

support OSIsupport OSI– not widely usednot widely used

late 1980’s: Sun Microsystemslate 1980’s: Sun Microsystems– NFS (Network File System)NFS (Network File System)– RPC (Remote Procedure Call)RPC (Remote Procedure Call)– NIS (Network Information Services)NIS (Network Information Services)

continued


early 1990’searly 1990’s– POSIX threads (light-weight processes)POSIX threads (light-weight processes)– Web client-server model based on TCP/IPWeb client-server model based on TCP/IP

mid 1990's: Javamid 1990's: Java– Java threadsJava threads– Java Remote Method Invocation (RMI)Java Remote Method Invocation (RMI)– CORBACORBA

continued


late 1990's / early 2000'slate 1990's / early 2000's– J2EE, .NETJ2EE, .NET– peer-to-peer (P2P)peer-to-peer (P2P)

Napster, Gnutella, etc.Napster, Gnutella, etc.

– JXTAJXTA

240-322 cli/serv.: dist. prog./21 client/server distributed systems v objectives –explain the...

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