Process Synchronization UNIT4 PDF

Chapter 5: Process Synchronization Process Cooperation and Synchronization Background The Critical-Section Problem Peterson’s Solution Synchronization Hardware Mutex Locks Semaphores Classic Problems of Synchronization Monitors Synchronization Examples Alternative App...

Chapter 5: Process Synchronization Process Cooperation and Synchronization Background The Critical-Section Problem Peterson’s Solution Synchronization Hardware Mutex Locks Semaphores Classic Problems of Synchronization Monitors Synchronization Examples Alternative Approaches  Objectives To present the concept of process synchronization. To introduce the critical-section problem, whose solutions can be used to ensure the consistency of shared data To present both software and hardware solutions of the critical-section problem To examine several classical process-synchronization problems To explore several tools that are used to solve process synchronization problems  Inter process communication (IPC) Inter process communication (IPC) is a mechanism which allows processes to communicate with each other and synchronize their actions. Processes within a system may be:  Operating Systems Client/Server Communication Client/Server communication involves two components, namely a client and a server. They are usually multiple clients in communication with a single server. The clients send requests to the server and the server responds to the client requests. There are three main methods to client/server communication. These are given as follows − Sockets Remote Procedure Calls Pipes  Operating Systems Client/Server Communication SOCKET: Sockets facilitate communication between two processes on the same machine or different machines.  They are used in a client/server. framework and consist of the IP address and port number. Many application protocols use sockets for data connection and data transfer between a client and a server.  Operating Systems Client/Server Communication Remote Procedure Calls These are interprocess communication techniques that are used for client_x0002_server based applications. A remote procedure call is also known as a subroutine call or a function call. A client has a request that the RPC translates and sends to the server. This request may be a procedure or a function call to a remote server. When the server receives the request, it sends the required response back to the client. Pipes These are interprocess communication methods that contain two end points. Data is entered from one end of the pipe by a process and consumed from the other end by the other process. The two different types of pipes are ordinary pipes and named pipes. Ordinary pipes only allow one way communication. For two way communication, two pipes are required. Ordinary pipes have a parent child relationship between the processes as the pipes can only be accessed by processes that created or inherited them  Cooperating Process Cooperating Processes Independent process cannot affect or be affected by the execution of another process. Cooperating process can affect or be affected by the execution of another process Advantages of process cooperation Information sharing Computation speed-up Modularity Convenience Robustness  Background Processes can execute concurrently  May be interrupted at any time, partially completing execution Concurrent access to shared data may result in data inconsistency Maintaining data consistency requires mechanisms to ensure the orderly execution of cooperating processes Illustration of the problem: Suppose that we wanted to provide a solution to the consumer- producer problem that fills all the buffers. We can do so by having an integer counter that keeps track of the number of full buffers. Initially, counter is set to 0. It is incremented by the producer after it produces a new buffer and is decremented by the consumer after it consumes a buffer.  Producer while (true) { while (counter == BUFFER_SIZE) ; buffer[in] = next_produced; in = (in + 1) % BUFFER_SIZE; counter++; }  Consumer while (true) { while (counter == 0) ; next_consumed = buffer[out]; out = (out + 1) % BUFFER_SIZE; counter--; }  Race Condition counter++ could be implemented as register1 = counter register1 = register1 + 1 counter = register1 counter-- could be implemented as register2 = counter register2 = register2 - 1 counter = register2 Consider this execution interleaving with “count = 5” initially: S0: producer execute register1 = counter {register1 = 5} S1: producer execute register1 = register1 + 1 {register1 = 6} S2: consumer execute register2 = counter {register2 = 5} S3: consumer execute register2 = register2 – 1 {register2 = 4} S4: producer execute counter = register1 {counter = 6 } S5: consumer execute counter = register2 {counter = 4}  Critical Section Problem Consider system of n processes {p0, p1, … pn-1} Each process has critical section segment of code  Process may be changing common variables, updating table, writing file, etc  When one process in critical section, no other may be in its critical section Critical section problem is to design protocol to solve this Each process must ask permission to enter critical section in entry section, may follow critical section with exit section, then remainder section  Critical Section General structure of process Pi  Algorithm for Process Pi do { while (turn == j); critical section turn = j; remainder section } while (true);  Solution to Critical-Section Problem 1. Mutual Exclusion - If process Pi is executing in its critical section, then no other processes can be executing in their critical sections 2. Progress - If no process is executing in its critical section and there exist some processes that wish to enter their critical section, then the selection of the processes that will enter the critical section next cannot be postponed indefinitely 3. Bounded Waiting - A bound must exist on the number of times that other processes are allowed to enter their critical sections after a process has made a request to enter its critical section and before that request is granted  Assume that each process executes at a nonzero speed  No assumption concerning relative speed of the n processes  Critical-Section Handling in OS Two approaches depending on if kernel is preemptive or non- preemptive  Preemptive – allows preemption of process when running in kernel mode  Non-preemptive – runs until exits kernel mode, blocks, or voluntarily yields CPU Essentially free of race conditions in kernel mode  Peterson’s Solution Good algorithmic description of solving the problem Two process solution Assume that the load and store machine-language instructions are atomic; that is, cannot be interrupted The two processes share two variables:  int turn;  Boolean flag The variable turn indicates whose turn it is to enter the critical section The flag array is used to indicate if a process is ready to enter the critical section. flag[i] = true implies that process Pi is ready!  Algorithm for Process Pi do { flag[i] = true; turn = j; while (flag[j] && turn = = j); critical section flag[i] = false; remainder section } while (true);  Peterson’s Solution (Cont.) Provable that the three CS requirement are met: 1. Mutual exclusion is preserved Pi enters CS only if: either flag[j] = false or turn = i 2. Progress requirement is satisfied 3. Bounded-waiting requirement is met  Synchronization Hardware Many systems provide hardware support for implementing the critical section code. All solutions below based on idea of locking  Protecting critical regions via locks Uniprocessors – could disable interrupts  Currently running code would execute without preemption  Generally too inefficient on multiprocessor systems  Operating systems using this not broadly scalable Modern machines provide special atomic hardware instructions  Atomic = non-interruptible  Either test memory word and set value  Or swap contents of two memory words  Solution to Critical-section Problem Using Locks do { acquire lock critical section release lock remainder section } while (TRUE);  test_and_set Instruction Definition: boolean test_and_set (boolean *target) { boolean rv = *target; *target = TRUE; return rv: } 1. Executed atomically 2. Returns the original value of passed parameter 3. Set the new value of passed parameter to “TRUE”.  Solution using test_and_set() Shared Boolean variable lock, initialized to FALSE Solution: do { while (test_and_set(&lock)) ; lock = false; } while (true);  compare_and_swap Instruction Definition: int compare _and_swap(int *value, int expected, int new_value) { int temp = *value; if (*value == expected) *value = new_value; return temp; } 1. Executed atomically 2. Returns the original value of passed parameter “value” 3. Set the variable “value” the value of the passed parameter “new_value” but only if “value” ==“expected”. That is, the swap takes place only under this condition.  Solution using compare_and_swap Shared integer “lock” initialized to 0; Solution: do { while (compare_and_swap(&lock, 0, 1) != 0) ; lock = 0; } while (true);  Bounded-waiting Mutual Exclusion with test_and_set do { waiting[i] = true; key = true; while (waiting[i] && key) key = test_and_set(&lock); waiting[i] = false; j = (i + 1) % n; while ((j != i) && !waiting[j]) j = (j + 1) % n; if (j == i) lock = false; else waiting[j] = false; } while (true);  Mutex Locks Previous solutions are complicated and generally inaccessible to application programmers OS designers build software tools to solve critical section problem Simplest is mutex lock Protect a critical section by first acquire() a lock then release() the lock  Boolean variable indicating if lock is available or not Calls to acquire() and release() must be atomic  Usually implemented via hardware atomic instructions But this solution requires busy waiting This lock therefore called a spinlock  acquire() and release() acquire() { while (!available) ; available = false; } release() { available = true; } do { acquire lock critical section release lock remainder section } while (true);  Semaphore Synchronization tool that provides more sophisticated ways (than Mutex locks) for process to synchronize their activities. Semaphore S – integer variable Can only be accessed via two indivisible (atomic) operations wait() and signal()  Originally called P() and V() Definition of the wait() operation wait(S) { while (S value--; if (S->value < 0) { add this process to S->list; block(); } } signal(semaphore *S) { S->value++; if (S->value list; wakeup(P); } }  Deadlock and Starvation Deadlock – two or more processes are waiting indefinitely for an event that can be caused by only one of the waiting processes Let S and Q be two semaphores initialized to 1 P0 P1 wait(S); wait(Q); wait(Q); wait(S);...... signal(S); signal(Q); signal(Q); signal(S); Starvation – indefinite blocking  A process may never be removed from the semaphore queue in which it is suspended Priority Inversion – Scheduling problem when lower-priority process holds a lock needed by higher-priority process  Solved via priority-inheritance protocol  Classical Problems of Synchronization Classical problems used to test newly-proposed synchronization schemes  Bounded-Buffer Problem  Readers and Writers Problem  Dining-Philosophers Problem  Bounded-Buffer Problem n buffers, each can hold one item Semaphore mutex initialized to the value 1 Semaphore full initialized to the value 0 Semaphore empty initialized to the value n  Bounded Buffer Problem (Cont.) The structure of the producer process do {...... wait(empty); wait(mutex);...... signal(mutex); signal(full); } while (true);  Bounded Buffer Problem (Cont.) The structure of the consumer process Do { wait(full); wait(mutex);...... signal(mutex); signal(empty);...... } while (true);  Readers-Writers Problem A data set is shared among a number of concurrent processes  Readers – only read the data set; they do not perform any updates  Writers – can both read and write Problem – allow multiple readers to read at the same time  Only one single writer can access the shared data at the same time Several variations of how readers and writers are considered – all involve some form of priorities Shared Data  Data set  Semaphore rw_mutex initialized to 1  Semaphore mutex initialized to 1  Integer read_count initialized to 0  Readers-Writers Problem (Cont.) The structure of a writer process do { wait(rw_mutex);...... signal(rw_mutex); } while (true);  Readers-Writers Problem (Cont.) The structure of a reader process do { wait(mutex); read_count++; if (read_count == 1) wait(rw_mutex); signal(mutex);...... wait(mutex); read count--; if (read_count == 0) signal(rw_mutex); signal(mutex); } while (true);  Readers-Writers Problem Variations First variation – no reader kept waiting unless writer has permission to use shared object Second variation – once writer is ready, it performs the write ASAP Both may have starvation leading to even more variations Problem is solved on some systems by kernel providing reader-writer locks  Dining-Philosophers Problem Philosophers spend their lives alternating thinking and eating Don’t interact with their neighbors, occasionally try to pick up 2 chopsticks (one at a time) to eat from bowl  Need both to eat, then release both when done In the case of 5 philosophers  Shared data  Bowl of rice (data set)  Semaphore chopstick initialized to 1  Dining-Philosophers Problem Algorithm The structure of Philosopher i: do { wait (chopstick[i] ); wait (chopStick[ (i + 1) % 5] ); // eat signal (chopstick[i] ); signal (chopstick[ (i + 1) % 5] ); // think } while (TRUE); What is the problem with this algorithm?  Dining-Philosophers Problem Algorithm (Cont.) Deadlock handling  Allow at most 4 philosophers to be sitting simultaneously at the table.  Allow a philosopher to pick up the forks only if both are available (picking must be done in a critical section.  Use an asymmetric solution -- an odd-numbered philosopher picks up first the left chopstick and then the right chopstick. Even-numbered philosopher picks up first the right chopstick and then the left chopstick.  Problems with Semaphores Incorrect use of semaphore operations:  signal (mutex) …. wait (mutex)  wait (mutex) … wait (mutex)  Omitting of wait (mutex) or signal (mutex) (or both) Deadlock and starvation are possible.  Monitors A high-level abstraction that provides a convenient and effective mechanism for process synchronization Abstract data type, internal variables only accessible by code within the procedure Only one process may be active within the monitor at a time But not powerful enough to model some synchronization schemes monitor monitor-name { // shared variable declarations procedure P1 (…) { …. } procedure Pn (…) {……} Initialization code (…) { … } } } Schematic view of a Monitor  Condition Variables condition x, y; Two operations are allowed on a condition variable:  x.wait() – a process that invokes the operation is suspended until x.signal()  x.signal() – resumes one of processes (if any) that invoked x.wait()  If no x.wait() on the variable, then it has no effect on the variable Monitor with Condition Variables  Condition Variables Choices If process P invokes x.signal(), and process Q is suspended in x.wait(), what should happen next?  Both Q and P cannot execute in paralel. If Q is resumed, then P must wait Options include  Signal and wait – P waits until Q either leaves the monitor or it waits for another condition  Signal and continue – Q waits until P either leaves the monitor or it waits for another condition  Both have pros and cons – language implementer can decide  Monitors implemented in Concurrent Pascal compromise  P executing signal immediately leaves the monitor, Q is resumed  Implemented in other languages including Mesa, C#, Java  Monitor Solution to Dining Philosophers monitor DiningPhilosophers { enum { THINKING; HUNGRY, EATING) state ; condition self ; void pickup (int i) { state[i] = HUNGRY; test(i); if (state[i] != EATING) self[i].wait; } void putdown (int i) { state[i] = THINKING; // test left and right neighbors test((i + 4) % 5); test((i + 1) % 5); }  Solution to Dining Philosophers (Cont.) void test (int i) { if ((state[(i + 4) % 5] != EATING) && (state[i] == HUNGRY) && (state[(i + 1) % 5] != EATING) ) { state[i] = EATING ; self[i].signal () ; } } initialization_code() { for (int i = 0; i < 5; i++) state[i] = THINKING; } }  Solution to Dining Philosophers (Cont.) Each philosopher i invokes the operations pickup() and putdown() in the following sequence: DiningPhilosophers.pickup(i); EAT DiningPhilosophers.putdown(i); No deadlock, but starvation is possible  Monitor Implementation Using Semaphores Variables semaphore mutex; // (initially = 1) semaphore next; // (initially = 0) int next_count = 0; Each procedure F will be replaced by wait(mutex); … body of F; … if (next_count > 0) signal(next) else signal(mutex); Mutual exclusion within a monitor is ensured  Monitor Implementation – Condition Variables For each condition variable x, we have: semaphore x_sem; // (initially = 0) int x_count = 0; The operation x.wait can be implemented as: x_count++; if (next_count > 0) signal(next); else signal(mutex); wait(x_sem); x_count--;  Monitor Implementation (Cont.) The operation x.signal can be implemented as: if (x_count > 0) { next_count++; signal(x_sem); wait(next); next_count--; }  Resuming Processes within a Monitor If several processes queued on condition x, and x.signal() executed, which should be resumed? FCFS frequently not adequate conditional-wait construct of the form x.wait(c)  Where c is priority number  Process with lowest number (highest priority) is scheduled next  Single Resource allocation Allocate a single resource among competing processes using priority numbers that specify the maximum time a process plans to use the resource R.acquire(t);... access the resurce;... R.release; Where R is an instance of type ResourceAllocator A Monitor to Allocate Single Resource monitor ResourceAllocator { boolean busy; condition x; void acquire(int time) { if (busy) x.wait(time); busy = TRUE; } void release() { busy = FALSE; x.signal(); } initialization code() { busy = FALSE; } }