Producer-Consumer solution using threads in Java - GeeksforGeeks

 

producer consumer problem can be solved using

Jul 11,  · Producer consumer problem is a classical synchronization problem. We can solve this problem by using semaphores. A semaphore S is an integer variable that can be accessed only through two standard operations: wait() and signal(). The wait() 3/5. 7 Producer-Consumer Problem Solving with semaphores: We’ll use counters to track how much data is in the buffer – One counter counts as we add data and stops a producer if there are N objects in the buffer. – A second counter counts as we remove data and stops a consumer if there are 0 in the buffer. Idea: since general semaphores can count for us, we don’t need a. Producer Consumer Problem is a classical concurrency problem and in fact it is one of the concurrency design pattern. In last article we have seen solving Producer Consumer problem in Java using blocking Queue but one of my reader emailed me and requested code example and explanation of solving Producer Consumer problem in Java with wait and notify method as well, Since its often asked as one.


Producer–consumer problem - Wikipedia


In computingthe producer—consumer problem [1] [2] also known as the bounded-buffer problem is a classic example of a multi- process synchronization problem. The problem describes two producer consumer problem can be solved using, the producer and the consumer, who share a common, fixed-size buffer used as a queue. The producer's job is to generate data, put it into the buffer, and start again. At the same time, the consumer is consuming the data i.

The problem is to make sure that the producer won't try to add data into the buffer if it's full and that the consumer won't try to remove data from an empty buffer. The solution for the producer is to either go to sleep or discard data if the buffer is full. The next time the consumer removes an item from the buffer, it notifies the producer, who starts to fill the buffer again. In the same way, the consumer can go to sleep if it finds the buffer empty.

The next producer consumer problem can be solved using the producer puts data into the buffer, it wakes up the sleeping consumer. The solution can be reached by means producer consumer problem can be solved using inter-process communicationtypically using semaphores.

An inadequate solution could result in a deadlock where both processes are waiting to be awakened. The problem can also be generalized to have multiple producers and consumers. To solve the problem, some programmer might come up with a solution shown below.

In the solution two library routines are used, sleep and wakeup. When sleep is called, the caller is blocked until another process wakes it up by using the wakeup routine. The global variable itemCount holds the number of items in the buffer. The problem with this solution is that it contains a race condition that can lead to a deadlock.

Consider the following scenario:. Since both processes will sleep forever, we have run into a deadlock. This solution therefore is unsatisfactory, producer consumer problem can be solved using.

An alternative analysis is that if the programming language does not define the semantics of concurrent accesses to shared variables in this case itemCount with use of synchronization, then the solution is unsatisfactory for that reason, without needing to explicitly demonstrate a race condition. Semaphores solve the problem of lost wakeup calls. In the solution below we use two semaphores, fillCount and emptyCountto solve the problem.

If the producer tries to decrement emptyCount when its value is zero, the producer is put to sleep. The next time an item is consumed, emptyCount is incremented and the producer wakes up. The consumer works analogously.

The solution above works fine when there is only one producer and consumer. With multiple producers sharing the same memory space for the item buffer, or multiple consumers sharing the same memory space, this solution contains a serious race condition that could result in two or more processes reading or writing into the same slot at the same time.

To understand how this is possible, imagine how the procedure putItemIntoBuffer can be implemented. It could contain two actions, one determining the next available slot and the other writing into it. If the procedure can be executed concurrently by multiple producers, then the following scenario is possible:.

To overcome this problem, we need a way to make sure that only one producer is executing putItemIntoBuffer at a time. In other words, we need a way to execute a critical section with mutual exclusion. The solution for multiple producers and consumers is shown below. Notice that the order in which different semaphores are incremented or decremented is essential: changing the order might result in a deadlock. It is important to note here that though mutex seems to work as a semaphore with value of 1 binary semaphorebut there is difference in the fact that mutex has ownership concept.

Ownership means that mutex can only be "incremented" back set to 1 by the same process that "decremented" it set to 0and all other tasks wait until mutex is available for decrement effectively meaning that resource is availablewhich ensures mutual exclusivity and avoids deadlock.

Thus using mutexes improperly can stall many processes when exclusive access is not required, but mutex is used instead of semaphore. The following pseudo code shows a solution to the producer—consumer problem using monitors. Since mutual exclusion is implicit with monitors, producer consumer problem can be solved using, no extra effort is necessary to protect the critical section.

In other words, the solution shown below works with any number of producers and consumers without any modifications. It is also noteworthy that it is less likely for a programmer to write code that suffers from race conditions when using monitors than when using semaphores. The producer—consumer problem, particularly in the case of a single producer and single consumer, strongly relates to implementing a FIFO producer consumer problem can be solved using a channel. The producer—consumer pattern can provide highly efficient data communication without relying on semaphores, mutexes, or monitors for data transfer.

Use of those primitives can give performance issues as they are expensive to implement. Channels and FIFOs are popular just because they avoid the need for end-to-end atomic synchronization. A basic example coded in C is shown below. Note that:. From Wikipedia, the free encyclopedia.

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Producer Consumer Problem with Wait and Notify - Thread Example | Java67

 

producer consumer problem can be solved using

 

7 Producer-Consumer Problem Solving with semaphores: We’ll use counters to track how much data is in the buffer – One counter counts as we add data and stops a producer if there are N objects in the buffer. – A second counter counts as we remove data and stops a consumer if there are 0 in the buffer. Idea: since general semaphores can count for us, we don’t need a. Thus using mutexes improperly can stall many processes when exclusive access is not required, but mutex is used instead of semaphore. Using monitors. The following pseudo code shows a solution to the producer–consumer problem using monitors. Since mutual exclusion is implicit with monitors, no extra effort is necessary to protect the critical. Producer Consumer Problem is a classical concurrency problem and in fact it is one of the concurrency design pattern. In last article we have seen solving Producer Consumer problem in Java using blocking Queue but one of my reader emailed me and requested code example and explanation of solving Producer Consumer problem in Java with wait and notify method as well, Since its often asked as one.