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1
Languages and Compilers(SProg og Oversættere)
Concurrency and distribution
Bent Thomsen
Department of Computer Science
Aalborg University
With acknowledgement to John Mitchell whose slides this lecture is based on.
2
Concurrency, distributed computing, the Internet
• Traditional view:• Let the OS deal with this• => It is not a programming language issue!• End of Lecture• Wait-a-minute …• Maybe “the traditional view” is getting out of date?
3
Languages with concurrency constructs
• Maybe the “traditional view” was always out of date?• Simula• Modula3• Occam• Concurrent Pascal• ADA• Linda• CML• Facile• Jo-Caml• Java• C#• …
4
Categories of Concurrency:
1. Physical concurrency - Multiple independent processors ( multiple threads of control)
• Uni-processor with I/O channels (multi-programming)
• Multiple CPU (parallel programming)
• Network of uni- or multi- CPU machines (distributed programming)
2. Logical concurrency - The appearance of physical concurrency is presented by time-sharing one processor (software can be designed as if there were multiple threads of control)
• Concurrency as a programming abstraction
Def: A thread of control in a program is the sequence of program points reached as control flows through the program
5
Introduction
• Reasons to Study Concurrency1. It involves a different way of designing software that can be
very useful—many real-world situations involve concurrency– Control programs– Simulations– Client/Servers– Mobile computing– Games
2. Computers capable of physical concurrency are now widely used
– High-end servers– Game consoles– Grid computing
6
The promise of concurrency
• Speed– If a task takes time t on one processor, shouldn’t it take time
t/n on n processors?
• Availability– If one process is busy, another may be ready to help
• Distribution– Processors in different locations can collaborate to solve a
problem or work together
• Humans do it so why can’t computers?– Vision, cognition appear to be highly parallel activities
7
Challenges
• Concurrent programs are harder to get right– Folklore: Need an order of magnitude speedup (or more) to be
worth the effort
• Some problems are inherently sequential– Theory – circuit evaluation is P-complete
– Practice – many problems need coordination and communication among sub-problems
• Specific issues– Communication – send or receive information
– Synchronization – wait for another process to act
– Atomicity – do not stop in the middle and leave a mess
8
Why is concurrent programming hard?• Nondeterminism
– Deterministic: two executions on the same input it always produce the same output
– Nondeterministic: two executions on the same input may produce different output
• Why does this cause difficulty?– May be many possible executions of one system
– Hard to think of all the possibilities
– Hard to test program since some may occur infrequently
9
Traditional C Library for concurrency
System Calls
- fork( )
- wait( )
- pipe( )
- write( )
- read( )
Examples
10
Process Creation
Fork( )NAME
fork() – create a new processSYNOPSIS
# include <sys/types.h># include <unistd.h>pid_t fork(void)
RETURN VALUEsuccess
parent- child pidchild- 0
failure-1
11
Fork()- program structure
#include <sys/types.h>#include <unistd.h>#include <stdio.h>Main(){
pid_t pid;if((pid = fork())>0){/* parent */}else if ((pid==0){/*child*/}else {
/* cannot fork*}exit(0);
}
12
Wait() system call
Wait()- wait for the process whose pid reference is passed to finish executing
SYNOPSIS
#include<sys/types.h>
#include<sys/wait.h>
pid_t wait(int *stat)loc)
The unsigned decimal integer process ID for which to wait
RETURN VALUE
success- child pid
failure- -1 and errno is set
13
Wait()- program structure
#include <sys/types.h>#include <unistd.h>#include <stdlib.h>#include <stdio.h>Main(int argc, char* argv[]){
pid_t childPID;if((childPID = fork())==0){/*child*/}else {
/* parent*wait(0);
}exit(0);
}
14
Pipe() system call
Pipe()- to create a read-write pipe that may later be used to communicate with a process we’ll fork off.
SYNOPSIS
Int pipe(pfd)
int pfd[2];
PARAMETERPfd is an array of 2 integers, which that will be used to save the two file descriptors used to access the pipe
RETURN VALUE:0 – success;-1 – error.
15
Pipe() - structure
/* first, define an array to store the two file descriptors*/Int pipes[2];
/* now, create the pipe*/int rc = pipe (pipes); if(rc = = -1) {
/* pipe() failed*/Perror(“pipe”);exit(1);
}
If the call to pipe() succeeded, a pipe will be created, pipes[0] will contain the number of its read file descriptor, and pipes[1] will contain the number of its write file descriptor.
16
Write() system call
Write() – used to write data to a file or other object identified by a file descriptor.
SYNOPSIS#include <sys/types.h>Size_t write(int fildes, const void * buf, size_t nbyte);
PARAMETERfildes is the file descriptor,buf is the base address of area of memory that data is copied from,nbyte is the amount of data to copy
RETURN VALUEThe return value is the actual amount of data written, if this differs from nbyte then something has gone wrong
17
Read() system call
Read() – read data from a file or other object identified by a file descriptor
SYNOPSIS
#include <sys/types.h>
Size_t read(int fildes, void *buf, size_t nbyte);
ARGUMENTfildes is the file descriptor,buf is the base address of the memory area into which the data is read, nbyte is the maximum amount of data to read.
RETURN VALUEThe actual amount of data read from the file. The pointer is incremented by the amount of data read.
18
Solaris 2 Synchronization
• Implements a variety of locks to support multitasking, multithreading (including real-time threads), and multiprocessing.
• Uses adaptive mutexes for efficiency when protecting data from short code segments.
• Uses condition variables and readers-writers locks when longer sections of code need access to data.
• Uses turnstiles to order the list of threads waiting to acquire either an adaptive mutex or reader-writer lock.
19
Windows 2000 Synchronization
• Uses interrupt masks to protect access to global resources on uniprocessor systems.
• Uses spinlocks on multiprocessor systems.• Also provides dispatcher objects which may act as
wither mutexes and semaphores.• Dispatcher objects may also provide events. An event
acts much like a condition variable.
20
Basic question
• Maybe the library approach is not such a good idea?
• How can programming languages make concurrent and distributed programming easier?
21
Language support for concurrency
• Help promote good software engineering• Allowing the programmer to express solutions more
closely to the problem domain• No need to juggle several programming models
(Hardware, OS, library, …)• Make invariants and intentions more apparent (part of
the interface and/or type system)• Allows the compiler much more freedom to choose
different implementations• Base the programming language constructs on a well-
understood formal model => formal reasoning may be less hard and the use tools may be possible
22
What could languages provide?
• Abstract model of system – abstract machine => abstract system
• Example high-level constructs– Communication abstractions
• Synchronous communication
• Buffered asynchronous channels that preserve msg order
– Mutual exclusion, atomicity primitives
• Most concurrent languages provide some form of locking
• Atomicity is more complicated, less commonly provided
– Process as the value of an expression
• Pass processes to functions
• Create processes at the result of function call
23
Basic issue: conflict between processes• Critical section
– Two processes may access shared resource
– Inconsistent behavior if two actions are interleaved
– Allow only one process in critical section
• Deadlock– Process may hold some locks while awaiting others
– Deadlock occurs when no process can proceed
24
Concurrency
• Def: A task is disjoint if it does not communicate with or affect the execution of any other task in the program in any way
• Task communication is necessary for synchronization– Task communication can be through:
1. Shared nonlocal variables
2. Parameters
3. Message passing
25
Synchronization
• Kinds of synchronization:1. Cooperation
– Task A must wait for task B to complete some specific activity before task A can continue its execution e.g., the producer-consumer problem
2. Competition
– When two or more tasks must use some resource that cannot be simultaneously used e.g., a shared counter
– Competition is usually provided by mutually exclusive access (approaches are discussed later)
26
Design Issues for Concurrency:
1. How is cooperation synchronization provided?
2. How is competition synchronization provided?
3. How and when do tasks begin and end execution?
4. Are tasks statically or dynamically created?
5. Are there any syntactic constructs in the language?
6. Are concurrency construct reflected in the type system?
27
Concurrent Pascal: cobegin/coend
• Limited concurrency primitive• Example
x := 0;cobegin
begin x := 1; x := x+1 end; begin x := 2; x := x+1 end;coend;print(x);
execute sequentialblocks in parallel
x := 0x := 2
x := 1
print(x)
x := x+1
x := x+1
Atomicity at level of assignment statement
28
Mutual exclusion
• Sample actionprocedure sign_up(person)
beginnumber := number + 1;list[number] := person;
end;
• Problem with parallel executioncobegin
sign_up(fred);sign_up(bill);
end; bob fredbillfred
29
Locks and Waiting
<initialze concurrency control>cobegin
begin <wait> sign_up(fred); // critical section<signal>
end;begin
<wait>sign_up(bill); // critical section<signal>
end;end;
Need atomic operations to implement wait
30
Mutual exclusion primitives
• Atomic test-and-set– Instruction atomically reads and writes some location
– Common hardware instruction
– Combine with busy-waiting loop to implement mutex
• Semaphore– Avoid busy-waiting loop
– Keep queue of waiting processes
– Scheduler has access to semaphore; process sleeps
– Disable interrupts during semaphore operations
• OK since operations are short
31
Monitor Brinch-Hansen, Dahl, Dijkstra, Hoare
• Synchronized access to private data. Combines:– private data
– set of procedures (methods)
– synchronization policy
• At most one process may execute a monitor procedure at a time; this process is said to be in the monitor.
• If one process is in the monitor, any other process that calls a monitor procedure will be delayed.
• Modern terminology: synchronized object
32
Java Concurrency• Threads
– Create process by creating thread object
• Communication– shared variables
– method calls
• Mutual exclusion and synchronization– Every object has a lock (inherited from class Object)
• synchronized methods and blocks– Synchronization operations (inherited from class Object)
• wait : pause current thread until another thread calls notify
• notify : wake up waiting threads
33
Java Threads
• Thread– Set of instructions to be executed one at a time, in a specified
order
• Java thread objects– Object of class Thread
– Methods inherited from Thread:
• start : method called to spawn a new thread of control; causes VM to call run method
• suspend : freeze execution
• interrupt : freeze execution and throw exception to thread
• stop : forcibly cause thread to halt
34
Example subclass of Thread
class PrintMany extends Thread {
private String msg;
public PrintMany (String m) {msg = m;}
public void run() {
try { for (;;){ System.out.print(msg + “ “);
sleep(10);
}
} catch (InterruptedException e) {
return;
}
} (inherits start from Thread)
35
Interaction between threads
• Shared variables– Two threads may assign/read the same variable
– Programmer responsibility
• Avoid race conditions by explicit synchronization!!
• Method calls– Two threads may call methods on the same object
• Synchronization primitives– Each object has internal lock, inherited from Object
– Synchronization primitives based on object locking
36
Synchronization example
• Objects may have synchronized methods• Can be used for mutual exclusion
– Two threads may share an object.
– If one calls a synchronized method, this locks object.
– If the other calls a synchronized method on same object, this thread blocks until object is unlocked.
37
Synchronized methods
• Marked by keywordpublic synchronized void commitTransaction(…) {…}
• Provides mutual exclusion– At most one synchronized method can be active
– Unsynchronized methods can still be called
• Programmer must be careful
• Not part of method signature– sync method equivalent to unsync method with body
consisting of a synchronized block
– subclass may replace a synchronized method with unsynchronized method
38
Join, another form of synchronization
• Wait for thread to terminateclass Future extends Thread {
private int result;
public void run() { result = f(…); }
public int getResult() { return result;}
}…
Future t = new future;
t.start() // start new thread…
t.join(); x = t.getResult(); // wait and get result
39
Aspects of Java Threads
• Portable since part of language– Easier to use in basic libraries than C system calls
– Example: garbage collector is separate thread
• General difficulty combining serial/concur code– Serial to concurrent
• Code for serial execution may not work in concurrent sys
– Concurrent to serial• Code with synchronization may be inefficient in serial
programs (10-20% unnecessary overhead)
• Abstract memory model– Shared variables can be problematic on some implementations
40
C# Threads
• Basic thread operations– Any method can run in its own thread
– A thread is created by creating a Thread object
– Creating a thread does not start its concurrent execution; it must be requested through the Start method
– A thread can be made to wait for another thread to finish with Join
– A thread can be suspended with Sleep– A thread can be terminated with Abort
41
C# Threads
• Synchronizing threads– The Interlock class
– The lock statement
– The Monitor class
• Evaluation– An advance over Java threads, e.g., any method can run its
own thread
– Thread termination cleaner than in Java
– Synchronization is more sophisticated
42
Polyphonic C#
• An extension of the C# language with new concurrency constructs
• Based on the join calculus– A foundational process calculus like the -calculus but better suited to
asynchronous, distributed systems• A single model which works both for
– local concurrency (multiple threads on a single machine)– distributed concurrency (asynchronous messaging over LAN or WAN)
• It is different• But it’s also simple – if Mort can do any kind of concurrency, he
can do this
43
In one slide:
• Objects have both synchronous and asynchronous methods.
• Values are passed by ordinary method calls:– If the method is synchronous, the caller blocks until the method returns some result
(as usual).
– If the method is async, the call completes at once and returns void.
• A class defines a collection of chords (synchronization patterns), which define what happens once a particular set of methods have been invoked. One method may appear in several chords.– When pending method calls match a pattern, its body runs.
– If there is no match, the invocations are queued up.
– If there are several matches, an unspecified pattern is selected.
– If a pattern containing only async methods fires, the body runs in a new thread.
44
Extending C# with chords
• Interesting well-formedness conditions:1. At most one header can have a return type (i.e. be synchronous).2. Inheritance restriction.3. “ref” and “out” parameters cannot appear in async headers.
• Classes can declare methods using generalized chord-declarations instead of method-declarations.
chord-declaration ::= method-header [ & method-header ]* body
method-header ::= attributes modifiers [return-type | async] name (parms)
45
A Simple Buffer
class Buffer {
String get() & async put(String s) {
return s;
}
}
•Calls to put() return immediately (but are internally queued if there’s no waiting get()).
•Calls to get() block until/unless there’s a matching put()
•When there’s a match the body runs, returning the argument of the put() to the caller of get().
•Exactly which pairs of calls are matched up is unspecified.
46
OCCAM
• Program consists of processes and channels
• Process is code containing channel operations• Channel is a data object• All synchronization is via channels• Formal foundation based on CSP
47
Channel Operations in OCCAM
• Read data item D from channel C– D ? C
• Write data item Q to channel C– Q ! C
• If reader accesses channel first, wait for writer, and then both proceed after transfer.
• If writer accesses channel first, wait for reader, and both proceed after transfer.
48
Concurrent ML
• Threads– New type of entity
• Communication– Synchronous channels
• Synchronization– Channels
– Events
• Atomicity– No specific language support
49
Threads
• Thread creation– spawn : (unit unit) thread_id
• Example code CIO.print "begin parent\n";
spawn (fn () => (CIO.print "child 1\n";));
spawn (fn () => (CIO.print "child 2\n";));
CIO.print "end parent\n“
• Result
end parent
child 2
child 1
begin parent
50
Channels
• Channel creation– channel : unit ‘a chan
• Communication– recv : ‘a chan ‘a– send : ( ‘a chan * ‘a ) unit
• Example ch = channel(); spawn (fn()=> … <A> … send(ch,0); … <B> …); spawn (fn()=> … <C> … recv ch; … <D> …);
• Resultsend/recv
<C>
<A>
<D>
<B>
51
CML programming
• Functions– Can write functions : channels threads
– Build concurrent system by declaring channels and “wiring together” sets of threads
• Events– Delayed action that can be used for synchronization
– Powerful concept for concurrent programming
• Sample Application– eXene – concurrent uniprocessor window system
52
A CML implementation (simplified)
• Use queues with side-effecting functionsdatatype 'a queue = Q of {front: 'a list ref, rear: 'a list ref}
fun queueIns (Q(…)) = (* insert into queue *)
fun queueRem (Q(…)) = (* remove from queue *)
• And continuationsval enqueue = queueIns rdyQ
fun dispatch () = throw (queueRem rdyQ) ()
fun spawn f = callcc (fn parent_k =>
( enqueue parent_k; f (); dispatch()))
Source: Appel, Reppy
53
Language issues in client/server programming
• Communication mechanisms– RPC, Remote Objects, SOAP
• Data representation languages– XDR, ASN.1, XML
• Parsing and deparsing between internal and external representation
• Stub generation
54
Client/server example
• The basic organization of the X Window System
• A major task of most clients is to interact with a human user and a remote server.
55
Client-Side Software for Distribution Transparency
• A possible approach to transparent replication of a remote object using a client-side solution.
56
The Stub Generation Process
Interface Specification
Stub Generator
ServerStub
CommonHeader
Client Stub
ClientSource
RPCLIBRARY
ServerSource
Compiler / Linker
RPCLIBRARY
ClientProgram
ServerProgram
Compiler / Linker
57
RPC and the OSI Reference Model
Application Layer
Presentation Layer (XDR)
Session Layer (RPC)
Transport Layer (UDP)
58
Representation
• Data must be represented in a meaningful format.• Methods:
– Sender or Receiver makes right (NDR).
• Network Data Representation (NDR).
• Transmit architecture tag with data.
– Represent data in a canonical (or standard) form
• XDR
• ASN.1
• Note – these are languages, but traditional DS programmers don’t like programming languages, except C
59
XDR - eXternal Data Representation
• XDR is a universally used standard from Sun Microsystems used to represent data in a network canonical (standard) form.
• A set of conversion functions are used to encode and decode data; for example, xdr_int( ) is used to encode and decode integers.
• Conversion functions exist for all standard data types– Integers, chars, arrays, …
• For complex structures, RPCGEN can be used to generate conversion routines.
60
RPC Example
gcc
RPClibrary
-lnsl
clientclient.c
date_proc.c gcc date_svc
date.x RPCGEN
date_clnt.c
date_svc.c
date_xdr.c
date.h
61
XDR Example
#include <rpc/xdr.h>
..
XDR sptr; // XDR stream pointer
XDR *xdrs; // Pointer to XDR stream pointer
char buf[BUFSIZE]; // Buffer to hold XDR data
xdrs = (&sptr);
xdrmem_create(xdrs, buf, BUFSIZE, XDR_ENCODE);
..
int i = 256;
xdr_int(xdrs, &i);
printf(“position = %d. \n”, xdr_getpos(xdrs));
xdrs
sptr
buf
62
Abstract Syntax Notation 1 (ASN.1)
• ASN.1 is a formal language that has two features:
– a notation used in documents that humans read
– a compact encoded representation of the same information used in communication protocols.
• ASN.1 uses a tagged message format:
– < tag (data type), data length, data value >
• Simple Network Management Protocol (SNMP) messages are encoded using ASN.1.
63
Distributed Objects
• CORBA• Java RMI• SOAP and XML
64
Distributed ObjectsProxy and Skeleton in Remote Method
Invocation
object A object Bskeleton
Requestproxy for B
Reply
CommunicationRemote Remote referenceCommunication
module modulereference module module
for B’s class& dispatcher
remoteclient server
65
CORBA
• Common Object Request Broker Architecture• An industry standard developed by OMG to help in distributed
programming• A specification for creating and using distributed objects• A tool for enabling multi-language, multi-platform communication• A CORBA based-system is a collection of objects that isolates the
requestors of services (clients) from the providers of services (servers) by an encapsulating interface
66
CORBA objects
They are different from typical programming objects in three ways:
• CORBA objects can run on any platform• CORBA objects can be located anywhere on the
network• CORBA objects can be written in any language that has
IDL mapping.
67
Client ClientObject Implementation Object Implementation
ORB ORB
NETWORK
IDL IDLIDL IDL
A request from a client to an Object implementation within a network
68
IDL (Interface Definition Language)
• CORBA objects have to be specified with interfaces (as with RMI) defined in a special definition language IDL.
• The IDL defines the types of objects by defining their interfaces and describes interfaces only, not implementations.
• From IDL definitions an object implementation tells its clients what operations are available and how they should be invoked.
• Some programming languages have IDL mapping (C, C++, SmallTalk, Java,Lisp)
69
IDL File
IDL Compiler
Client StubFile
ServerSkeleton File
ClientImplementation
ObjectImplementation
ORB
70
The IDL compiler
• It will accept as input an IDL file written using any text editor (fileName.idl)
• It generates the stub and the skeleton code in the target programming language (ex: Java stub and C++ skeleton)
• The stub is given to the client as a tool to describe the server functionality, the skeleton file is implemented at the server.
71
IDL Example
module katytrail { module weather { struct WeatherData { float temp; string wind_direction_and_speed; float rain_expected; float humidity; }; typedef sequence<WeatherData> WeatherDataSeq interface WeatherInfo { WeatherData get_weather( in string site ); WeatherDataSeq find_by_temp( in float temperature ); };
72
IDL Example Cont.
interface WeatherCenter { register_weather_for_site ( in string site, in WeatherData site_data ); }; };};
Both interfaces will have Object Implementations.A different type of Client will talk to each of theinterfaces.
The Object Implementations can be done in oneof two ways. Through Inheritance or througha Tie.
73
Stubs and Skeletons
• In terms of CORBA development, the stubs and skeleton files are standard in terms of their target language.
• Each file exposes the same operations specified in the IDL file.• Invoking an operation on the stub file will cause the method to be
executed in the skeleton file• The stub file allows the client to manipulate the remote object
with the same ease with each a local file is manipulated
74
Java RMI
• Overview– Supports remote invocation of Java objects– Key: Java Object Serialization
Stream objects over the wire – Language specific
• History– Goal: RPC for Java– First release in JDK 1.0.2, used in Netscape 3.01– Full support in JDK 1.1, intended for applets– JDK 1.2 added persistent reference, custom protocols, more support for
user control.
75
Java RMI
• Advantages– True object-orientation: Objects as arguments and values– Mobile behavior: Returned objects can execute on caller– Integrated security– Built-in concurrency (through Java threads)
• Disadvantages– Java only
• Advertises support for non-Java• But this is external to RMI – requires Java on both sides
76
Java RMI Components
• Base RMI classes– Extend these to get RMI functionality
• Java compiler – javac– Recognizes RMI as integral part of language
• Interface compiler – rmic– Generates stubs from class files
• RMI Registry – rmiregistry– Directory service
• RMI Run-time activation system – rmid– Supports activatable objects that run only on demand
77
RMI Implementation
Java Virtual Machine
ClientObject
Java Virtual Machine
RemoteObject
Stub Skeleton
Client Host Server Host
78
Java RMI Object Serialization
• Java can send object to be invoked at remote site– Allows objects as arguments/results
• Mechanism: Object Serialization– Object passed must inherit from serializable– Provides methods to translate object to/from byte stream
• Security issues:– Ensure object not tampered with during transmission– Solution: Class-specific serialization
Throw it on the programmer
79
Building a Java RMI Application
• Define remote interface– Extend java.rmi.Remote
• Create server code– Implements interface– Creates security manager, registers with registry
• Create client code– Define object as instance of interface– Lookup object in registry– Call object
• Compile and run– Run rmic on compiled classes to create stubs– Start registry– Run server then client
80
Parameter Passing
• Primitive types– call-by-value
• Remote objects– call-by-reference
• Non-remote objects– call-by-value
– use Java Object Serialization
81
Java Serialization
• Writes object as a sequence of bytes• Writes it to a Stream• Recreates it on the other end• Creates a brand new object with the old data• Objects can be transmitted using any byte stream
(including sockets and TCP).
82
Codebase Property
• Stub classpaths can be confusing– 3 VMs, each with its own classpath– Server vs. Registry vs. Client
• The RMI class loader always loads stubs from the CLASSPATH first
• Next, it tries downloading classes from a web server– (but only if a security manager is in force)
• java.rmi.server.codebase specifies which web server
83
CORBA vs. RMI
• CORBA was designed for language independence whereas RMI was designed for a single language where objects run in a homogeneous environment
• CORBA interfaces are defined in IDL, while RMI interfaces are defined in Java
• CORBA objects are not garbage collected because they are language independent and they have to be consistent with languages that do not support garbage collection, on the other hand RMI objects are garbage collected automatically
84
SOAP Introduction
• SOAP is simple, light weight and text based protocol• SOAP is XML based protocol (XML encoding)• SOAP is remote procedure call protocol, not object oriented
completely• SOAP can be wired with any protocol
SOAP is a simple lightweight protocol with minimum set of rules for invoking remote services using XML data representation and HTTP wire.
• Main goal of SOAP protocol – Interoperability
• SOAP does not specify any advanced distributed services.
W indow s
E-Commerce
Unix
MainFrame
SOAP
85
Why SOAP – What’s wrong with existing distributed technologies
• Platform and vendor dependent solutions (DCOM – Windows) (CORBA – ORB vendors) (RMI – Java)
• Different data representation schemes (CDR – NDR)
• Complex client side deployment
• Difficulties with firewall Firewalls allows only specific ports ( port 80 ), but DCOM and CORBA assigns port numbers dynamically.
• In short, these distributed technologies do not communicate easily with each other because of lack of standards between them.
86
Base Technologies – HTTP and XML
• SOAP uses the existing technologies, invents no new technology.• XML and HTTP are accepted and deployed in all platforms.• Hypertext Transfer Protocol (HTTP)
– HTTP is very simple and text-based protocol.– HTTP layers request/response communication over TCP/IP. HTTP
supports fixed set of methods like GET, POST.– Client / Server interaction
• Client requests to open connection to server on default port number• Server accepts connection• Client sends a request message to the Server• Server process the request• Server sends a reply message to the client• Connection is closed
– HTTP servers are scalable, reliable and easy to administer.• SOAP can be bind any protocol – HTTP , SMTP, FTP
87
Extensible Markup Language (XML)
• XML is platform neutral data representation protocol.• HTML combines data and representation, but XML contains just
structured data. • XML contains no fixed set of tags and users can build their own
customized tags.<student>
<full_name>Bhavin Parikh</full_name><email>[email protected]</email>
</student>• XML is platform and language independent.• XML is text-based and easy to handle and it can be easily
extended.
88
Architecture diagram
Client Application(CO M clien t or CO RBA clien t or
Java RM I client)
W eb ServicesDescriptionLanguage
XML Parser SOAP Library
Proxy Object
Server Application(CO M ob ject or CO RBA ob ject or
RM I O bject)
HTTP Server
SOAP Listener
SOAP Request
Calldirect
Call throughproxy
SOAP Response
SOAP = HTTP +XM L + RPCOR
SOAP = HTTPS +XM L + RPC
1. C lient call rem ote serviceusing SOAP
2. C lient can use proxy object tohide all SOAP details
M appingTool
4. Mapping tool m aps SOAP request torem ote serice
3. SOAP Listener can be im plem entedas ASP, JSP, CGI or SERVLET
XML Parser
SOAP Library
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Parsing XML Documents
• Remember: XML is just text• Simple API for XML (SAX) Parsing
– SAX is typically most efficient– No Memory Implementation!
• Left to the Developer
• Document Object Model (DOM) Parsing– “Parsing” is not fundamental emphasis.– A “DOM Object” is a representation of the XML document in
a binary tree format.
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Parsing: Examples
• SaxParseExample– “Callback” functions to process Nodes
• DomParseExample– Use of JAXP (Java API for XML Parsing)
• Implementations can be ‘swapped’, such as replacing Apache Xerces with Sun Crimson.
– JAXP does not include some ‘advanced’ features that may be useful.
– SAX used behind the scenes to create object model
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Web-based applications today
Presentation: HTML, CSS, Javascript, Flash, Java applets, ActiveX controls
Business logic: C#, Java, VB, PHP, Perl, Python,Ruby …
Database: SQL
File system
Application serverWeb serverContent management system
Operating System
Sockets, HTTP, email, SMS, XML, SOAP, REST, Rails, reliable messaging, AJAX, …Replication, distribution,
load-balancing, security, concurrency
Beans, servlets, CGI, ASP.NET,…
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Languages for distributed computing
• Motivation– Why all the fuss about language and platform independence?
• It is extremely inefficient to parse/deparse to/from external/internal representation
• 95% of all computers run Windows anyway
• There is a JVM for almost any processor you can think of
• Few programmers master more than one programming language anyway
– Develop a coherent programming models for all aspects of an application
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Facile Programming Language
• Integration of Multiple Paradigms– Functions
– Types/complex data types
– Concurrency
– Distribution/soft real-time
– Dynamic connectivity
• Implemented as extension to SML• Syntax for concurrency similar to CML
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Facile implementation
• Pre-emptive scheduler implemented at the lowest level– Exploiting CPS translation => state characterised by the set of
registers
• Garbage collector used for linearizing data structures• Lambda level code used as intermediate language when
shipping data (including code) in heterogeneous networks
• Native representation is shipped when possible– i.e. same architecture and within same trust domain
• Possibility to mix between interpretation or JIT depending on usage
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Conclusion
• Concurrency may be an order of magnitude more difficult to handle
• Programming language support for concurrency may help make the task easier
• Which concurrency constructs to add to the language is still a very active research area
• If you add concurrency construct, be sure you base them on a formal model!
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The guiding principle
• Provide better level of abstraction
• Make invariants and intentions more apparent (part of the interface)
• Give stronger compile-time guarantees (types)
• Enable different implementations and optimizations
• Expose structure for other tools to exploit (e.g. static analysis)
Put important features in the language itself, rather than in libraries