Concurrency In Networks
The term concurrency refers to real or apparent simultaneous computing. For example, a multi-user computer system can achieve concurrency by time-sharing, a design that arranges to switch a single processor among multiple computations quickly enough to give the appearance of simultaneous progress; or by multiprocessing, a design in which multiple processors perform multiple computations simultaneously.Concurrent processing is fundamental to distributed computing and occurs in many forms. Among machines on a single network, many pairs of application programs can communicate concurrently, sharing the network that interconnects them. For example, application A on one machine may communicate with application B on another machine, while application C on a third machine communicates with application D on a fourth. Although they all share a single network, the applications appear to proceed as if they operate independently. The network hardware enforces access rules that allow each pair of communicating machines to exchange messages. The access rules prevent a given pair of applications from excluding others by consuming all the network bandwidth.
Concurrency can also occur within a given computer system. For example, multiple users on a timesharing system can each invoke a client application that communicates with an application on another machine. One user can transfer a file while another user conducts a remote login session. From a user's point of view, it appears that all client programs proceed simultaneously.
Client software does not usually require any special attention or effort on the part of the programmer to make it usable concurrently. The application programmer designs and constructs each client program without regard to concurrent execution; concurrency among multiple client programs occurs automatically because the operating system allows multiple users to each invoke a client concurrently. Thus, the individual clients operate much like any conventional program. To summarize:
Most client software achieves concurrent operation because the underlying operating system allows users to execute client programs concurrently or because users on many machines each execute client software simultaneously. An individual client program operates like any conventional program; it does not manage concurrency explicitly.
Concurrency In Servers
In contrast to concurrent client software, concurrency within a server requires considerable effort. As figure 3.2 shows, a single server program must handle incoming requests concurrently.To understand why concurrency is important, consider server operations that require substantial computation or communication. For example, think of a remote login server. It it operates with no concurrency, it can handle only one remote login at a time. Once a client contacts the server, the server must ignore or refuse subsequent requests until the first user finishes. Clearly, such a design limits the utility of the server, and prevents multiple remote users from accessing a given machine at the same time.
Terminology And Concepts
Because few application programmers have experience with the design of concurrent programs, understanding concurrency in servers can be challenging. This section explains the basic concept of concurrent processing and shows how an operating system supplies it.The Process Concept
In concurrent processing systems, the process abstraction defines the fundamental unit of computation1. The most essential information associated with a process is an instruction pointer that specifies the address at which the process is executing. Other information associated with a process includes the identity of the user that owns it, the compiled program that it is executing, and the memory locations of the process' program text and data areas.A process differs from a program because the process concept includes only the active execution of a computation, not the code. After the code has been loaded into a computer, the operating system allows one or more processes to execute it. In particular, a concurrent processing system allows multiple processes to execute the same piece of code "at the same time." This means that multiple processes may each be executing at some point in the code. Each process proceeds at its own rate, and each may begin or finish at an arbitrary time. Because each has a separate instruction pointer that specifies which instruction it will execute next, there is never any confusion.
Of course, on a uniprocessor architecture, the single CPU can only execute one process at any instant in time. The operating system makes the computer appear to perform more than one computation at a time by switching the CPU among all executing processes rapidly. From a human observer's point of view, many processes appear to proceed simultaneously. In fact, one process proceeds for a short time, then another process proceeds for a short time, and so on. We use the term concurrent execution to capture the idea. It means "apparently simultaneous execution." On a uniprocessor, the operating system handles concurrency, while on a multiprocessor, all CPUs can execute processes simultaneously.
The important concept is:
Application programmers build programs for a concurrent environment without knowing whether the underlying hardware consists of a uniprocessor or a multiprocessor.
Programs vs. Processes
In a concurrent processing system, a conventional application program is merely a special case: it consists of a piece of code that is executed by exactly one process at a time. The notion of process differs from the conventional notion of program in other ways. For example, most application programmers think of the set of variables defined in the program as being associated with the code. However, if more than one process executes the code concurrently, it is essential that each process has its own copy of the variables. To understand why, consider the following segment of C code that prints the integers from 1 to 10:for ( i=1 ; i <= 10 ; i++)The iteration uses an index variable, i. In a conventional program, the programmer thinks of storage for variable i as being allocated with the code. However, if two or more processes execute the code segment concurrently, one of them may be on the sixth iteration when the other starts the first iteration. Each must have a different value for i. Thus, each process must have its own copy of variable i or confusion will result, To summarize:
printf("%d\n", i);
When multiple processes execute a piece of code concurrently, each process has its own, independent copy of the variables associated with the code.
Procedure Calls
In a procedure-oriented language, like Pascal or C, executed code can contain calls to subprograms (procedures or functions). Subprograms accept arguments, compute a result, and then return just after the point of the call. If multiple processes execute code concurrently, they can each be at a different point in the sequence of procedure calls. One process, A, can begin execution, call a procedure, and then call a second-level procedure before another process, B, begins. Process B may return from a first-level procedure call just as process A returns from a second-level call. The run-time system for procedure-oriented programming languages uses a stack mechanism to handle procedure calls.The run-time system pushes a procedure activation record on the stack whenever it makes a procedure call. Among other things, the activation record stores information about the location in the code at which the procedure call occurs. When the procedure finishes execution, the run-time system pops the activation record from the top of the stack and returns to the procedure from which the call occurred. Analogous to the rule for variables, concurrent programming systems provide separation between procedure calls in executing processes:
When multiple processes execute a piece of code concurrently, each has its own run-time stack of procedure activation records.
An Example Of Concurrent Process Creation
A Sequential C Example
The following example illustrates concurrent processing in the UNIX operating system. As with most computational concepts, the programming language syntax is trivial; it occupies only a few lines of code. For example, the following code is a conventional C program that prints the integers from I to 5 along with their sum:/* sum.c - A conventional C program that sum integers from 1 to 5 */
#include <stdlib.h>
#include <stdio.h>
int sum;
/* sum is a global variable */
main () {
int i;
/* i is a local variable */
/* iterate i from 1 to 5 */
sum = 0;
for (i=1 ; i <=5 ; i++) {
printf("The value of i is %d\n", i);
fflush(stdout);
/* flush the buffer
*/
sum += i;
}
printf ("The sum is %d\n", sum);
exit(0);
/* terminate the program */
}
When executed, the program emits six lines of output:
The value of i is 1
The value of i is 2
The value of i is 3
The value of i is 4
The value of i is 5
The sum is 15
A Concurrent Version
#include <stdlib.h>#include <stdio.h>
int
sum;
main() {
int i;
sun = 0;
fork();
/* create a new process */
for (i=1 ; i<=5 ; i++) {
printf ("The value of i is %d\n", i);
fflush(stdout);
sum += i;
}
printf ("The sum is %d\n", sum);
exit (0)
}
When a user executes the concurrent version of the program, the system begins with a single process executing the code.However, when the process reaches the call to fork, the system duplicates the process and allows both the original process andthe newly created process to execute. Of course, each process has its own copy of the variables that the program uses. In fact, theeasiest way to envision what happens is to imagine that the system makes a second copy of the entire running program. Then imagine that both copies run Oust as if two users had both simultaneously executed the program). To summarize:
To understand the fork function, imagine that fork causes the operating system to make a copy of the executing program and allows both copies to run at the same time.
