Deadlock

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Both processes need resources to continue execution. P1 requires additional resource R1 and is in possession of resource R2, P2 requires additional resource R2 and is in possession of R1; neither process can continue. Process deadlock.svg
Both processes need resources to continue execution. P1 requires additional resource R1 and is in possession of resource R2, P2 requires additional resource R2 and is in possession of R1; neither process can continue.
Four processes (blue lines) compete for one resource (grey circle), following a right-before-left policy. A deadlock occurs when all processes lock the resource simultaneously (black lines). The deadlock can be resolved by breaking the symmetry. Deadlock at a four-way-stop.gif
Four processes (blue lines) compete for one resource (grey circle), following a right-before-left policy. A deadlock occurs when all processes lock the resource simultaneously (black lines). The deadlock can be resolved by breaking the symmetry.

In concurrent computing, deadlock is any situation in which no member of some group of entities can proceed because each waits for another member, including itself, to take action, such as sending a message or, more commonly, releasing a lock. [1] Deadlocks are a common problem in multiprocessing systems, parallel computing, and distributed systems, because in these contexts systems often use software or hardware locks to arbitrate shared resources and implement process synchronization. [2]

Contents

In an operating system, a deadlock occurs when a process or thread enters a waiting state because a requested system resource is held by another waiting process, which in turn is waiting for another resource held by another waiting process. [3] If a process remains indefinitely unable to change its state because resources requested by it are being used by another process that itself is waiting, then the system is said to be in a deadlock. [4]

In a communications system, deadlocks occur mainly due to loss or corruption of signals rather than contention for resources. [5]

Two processes competing for two resources in opposite order.
A single process goes through.
The later process has to wait.
A deadlock occurs when the first process locks the first resource at the same time as the second process locks the second resource.
The deadlock can be resolved by cancelling and restarting the first process. Two processes, two resources.gif
Two processes competing for two resources in opposite order.
  1. A single process goes through.
  2. The later process has to wait.
  3. A deadlock occurs when the first process locks the first resource at the same time as the second process locks the second resource.
  4. The deadlock can be resolved by cancelling and restarting the first process.

Individually necessary and jointly sufficient conditions for deadlock

A deadlock situation on a resource can arise only if all of the following conditions occur simultaneously in a system: [6]

  1. Mutual exclusion: At least one resource must be held in a non-shareable mode (we are assuming that one resource could have multiple instances); that is, only one process at a time can use the resource. [7] Otherwise, the processes would not be prevented from using the resource when necessary. Only one process can use the resource at any given instant of time. [8]
  2. Hold and wait or resource holding: a process is currently holding at least one resource and requesting additional resources which are being held by other processes.
  3. No preemption: a resource can be released only voluntarily by the process holding it.
  4. Circular wait: each process must be waiting for a resource which is being held by another process, which in turn is waiting for the first process to release the resource. In general, there is a set of waiting processes, P = {P1, P2, ..., PN}, such that P1 is waiting for a resource held by P2, P2 is waiting for a resource held by P3 and so on until PN is waiting for a resource held by P1. [4] [9]

These four conditions are known as the Coffman conditions from their first description in a 1971 article by Edward G. Coffman, Jr. [9]

While these conditions are sufficient to produce a deadlock on single-instance resource systems, they only indicate the possibility of deadlock on systems having multiple instances of resources. [10]

Deadlock handling

Most current operating systems cannot prevent deadlocks. [11] When a deadlock occurs, different operating systems respond to them in different non-standard manners. Most approaches work by preventing one of the four Coffman conditions from occurring, especially the fourth one. [12] Major approaches are as follows.

Ignoring deadlock

In this approach, it is assumed that a deadlock will never occur. This is also an application of the Ostrich algorithm. [12] [13] This approach was initially used by MINIX and UNIX. [9] This is used when the time intervals between occurrences of deadlocks are large and the data loss incurred each time is tolerable.

Ignoring deadlocks can be safely done if deadlocks are formally proven to never occur. An example is the RTIC framework. [14]

Detection

Under the deadlock detection, deadlocks are allowed to occur. Then the state of the system is examined to detect that a deadlock has occurred and subsequently it is corrected. An algorithm is employed that tracks resource allocation and process states, it rolls back and restarts one or more of the processes in order to remove the detected deadlock. Detecting a deadlock that has already occurred is easily possible since the resources that each process has locked and/or currently requested are known to the resource scheduler of the operating system. [13]

After a deadlock is detected, it can be corrected by using one of the following methods:[ citation needed ]

  1. Process termination: one or more processes involved in the deadlock may be aborted. One could choose to abort all competing processes involved in the deadlock. This ensures that deadlock is resolved with certainty and speed.[ citation needed ] But the expense is high as partial computations will be lost. Or, one could choose to abort one process at a time until the deadlock is resolved. This approach has a high overhead because after each abort an algorithm must determine whether the system is still in deadlock.[ citation needed ] Several factors must be considered while choosing a candidate for termination, such as priority and age of the process.[ citation needed ]
  2. Resource preemption: resources allocated to various processes may be successively preempted and allocated to other processes until the deadlock is broken. [15] [ failed verification ]

Prevention

(A) Two processes competing for one resource, following a first-come, first-served policy. (B) Deadlock occurs when both processes lock the resource simultaneously. (C) The deadlock can be resolved by breaking the symmetry of the locks. (D) The deadlock can be prevented by breaking the symmetry of the locking mechanism. Avoiding deadlock.gif
(A) Two processes competing for one resource, following a first-come, first-served policy. (B) Deadlock occurs when both processes lock the resource simultaneously. (C) The deadlock can be resolved by breaking the symmetry of the locks. (D) The deadlock can be prevented by breaking the symmetry of the locking mechanism.

Deadlock prevention works by preventing one of the four Coffman conditions from occurring.

Deadlock avoidance

Similar to deadlock prevention, deadlock avoidance approach ensures that deadlock will not occur in a system. The term "deadlock avoidance" appears to be very close to "deadlock prevention" in a linguistic context, but they are very much different in the context of deadlock handling. Deadlock avoidance does not impose any conditions as seen in prevention but, here each resource request is carefully analyzed to see whether it could be safely fulfilled without causing deadlock.

Deadlock avoidance requires that the operating system be given in advance additional information concerning which resources a process will request and use during its lifetime. Deadlock avoidance algorithm analyzes each and every request by examining that there is no possibility of deadlock occurrence in the future if the requested resource is allocated. The drawback of this approach is its requirement of information in advance about how resources are to be requested in the future. One of the most used deadlock avoidance algorithms is Banker's algorithm. [17]

Livelock

A livelock is similar to a deadlock, except that the states of the processes involved in the livelock constantly change with regard to one another, none progressing.

The term was coined by Edward A. Ashcroft in a 1975 paper [18] in connection with an examination of airline booking systems. [19] Livelock is a special case of resource starvation; the general definition only states that a specific process is not progressing. [20]

Livelock is a risk with some algorithms that detect and recover from deadlock. If more than one process takes action, the deadlock detection algorithm can be repeatedly triggered. This can be avoided by ensuring that only one process (chosen arbitrarily or by priority) takes action. [21]

Distributed deadlock

Distributed deadlocks can occur in distributed systems when distributed transactions or concurrency control is being used.

Distributed deadlocks can be detected either by constructing a global wait-for graph from local wait-for graphs at a deadlock detector or by a distributed algorithm like edge chasing.

Phantom deadlocks are deadlocks that are falsely detected in a distributed system due to system internal delays but do not actually exist. For example, if a process releases a resource R1 and issues a request for R2, and the first message is lost or delayed, a coordinator (detector of deadlocks) could falsely conclude a deadlock (if the request for R2 while having R1 would cause a deadlock).

See also

Related Research Articles

A real-time operating system (RTOS) is an operating system (OS) for real-time computing applications that processes data and events that have critically defined time constraints. An RTOS is distinct from a time-sharing operating system, such as Unix, which manages the sharing of system resources with a scheduler, data buffers, or fixed task prioritization in a multitasking or multiprogramming environments. Processing time requirements need to be fully understood and bound rather than just kept as a minimum. All processing must occur within the defined constraints. Real-time operating systems are event-driven and preemptive, meaning the OS can monitor the relevant priority of competing tasks, and make changes to the task priority. Event-driven systems switch between tasks based on their priorities, while time-sharing systems switch the task based on clock interrupts.

<span class="mw-page-title-main">Mutual exclusion</span> In computing, restricting data to be accessible by one thread at a time

In computer science, mutual exclusion is a property of concurrency control, which is instituted for the purpose of preventing race conditions. It is the requirement that one thread of execution never enters a critical section while a concurrent thread of execution is already accessing said critical section, which refers to an interval of time during which a thread of execution accesses a shared resource or shared memory.

<span class="mw-page-title-main">Process (computing)</span> Particular execution of a computer program

In computing, a process is the instance of a computer program that is being executed by one or many threads. There are many different process models, some of which are light weight, but almost all processes are rooted in an operating system (OS) process which comprises the program code, assigned system resources, physical and logical access permissions, and data structures to initiate, control and coordinate execution activity. Depending on the OS, a process may be made up of multiple threads of execution that execute instructions concurrently.

<span class="mw-page-title-main">Semaphore (programming)</span> Variable used in a concurrent system

In computer science, a semaphore is a variable or abstract data type used to control access to a common resource by multiple threads and avoid critical section problems in a concurrent system such as a multitasking operating system. Semaphores are a type of synchronization primitive. A trivial semaphore is a plain variable that is changed depending on programmer-defined conditions.

In computing, scheduling is the action of assigning resources to perform tasks. The resources may be processors, network links or expansion cards. The tasks may be threads, processes or data flows.

In computer science, a lock or mutex is a synchronization primitive that prevents state from being modified or accessed by multiple threads of execution at once. Locks enforce mutual exclusion concurrency control policies, and with a variety of possible methods there exist multiple unique implementations for different applications.

<span class="mw-page-title-main">Dining philosophers problem</span> Problem used to illustrate synchronization issues and techniques for resolving them

In computer science, the dining philosophers problem is an example problem often used in concurrent algorithm design to illustrate synchronization issues and techniques for resolving them.

In computer science, an algorithm is called non-blocking if failure or suspension of any thread cannot cause failure or suspension of another thread; for some operations, these algorithms provide a useful alternative to traditional blocking implementations. A non-blocking algorithm is lock-free if there is guaranteed system-wide progress, and wait-free if there is also guaranteed per-thread progress. "Non-blocking" was used as a synonym for "lock-free" in the literature until the introduction of obstruction-freedom in 2003.

In computer science, the ostrich algorithm is a strategy of ignoring potential problems on the basis that they may be exceedingly rare. It is named after the ostrich effect which is defined as "to stick one's head in the sand and pretend there is no problem". It is used when it is more cost-effective to allow the problem to occur than to attempt its prevention.

Concurrent computing is a form of computing in which several computations are executed concurrently—during overlapping time periods—instead of sequentially—with one completing before the next starts.

Commitment ordering (CO) is a class of interoperable serializability techniques in concurrency control of databases, transaction processing, and related applications. It allows optimistic (non-blocking) implementations. With the proliferation of multi-core processors, CO has also been increasingly utilized in concurrent programming, transactional memory, and software transactional memory (STM) to achieve serializability optimistically. CO is also the name of the resulting transaction schedule (history) property, defined in 1988 with the name dynamic atomicity. In a CO compliant schedule, the chronological order of commitment events of transactions is compatible with the precedence order of the respective transactions. CO is a broad special case of conflict serializability and effective means to achieve global serializability across any collection of database systems that possibly use different concurrency control mechanisms.

In computer science, synchronization is the task of coordinating multiple of processes to join up or handshake at a certain point, in order to reach an agreement or commit to a certain sequence of action.

Banker's algorithm is a resource allocation and deadlock avoidance algorithm developed by Edsger Dijkstra that tests for safety by simulating the allocation of predetermined maximum possible amounts of all resources, and then makes an "s-state" check to test for possible deadlock conditions for all other pending activities, before deciding whether allocation should be allowed to continue.

In computer science, a lock convoy is a performance problem that can occur when using locks for concurrency control in a multithreaded application.

In computer science, resource contention is a conflict over access to a shared resource such as random access memory, disk storage, cache memory, internal buses or external network devices. A resource experiencing ongoing contention can be described as oversubscribed.

<span class="mw-page-title-main">Wait-for graph</span>

A wait-for graph in computer science is a directed graph used for deadlock detection in operating systems and relational database systems.

In computing, a hang or freeze occurs when either a process or system ceases to respond to inputs. A typical example is when computer's graphical user interface no longer responds to the user typing on the keyboard or moving the mouse. The term covers a wide range of behaviors in both clients and servers, and is not limited to graphical user interface issues.

A distributed operating system is system software over a collection of independent software, networked, communicating, and physically separate computational nodes. They handle jobs which are serviced by multiple CPUs. Each individual node holds a specific software subset of the global aggregate operating system. Each subset is a composite of two distinct service provisioners. The first is a ubiquitous minimal kernel, or microkernel, that directly controls that node's hardware. Second is a higher-level collection of system management components that coordinate the node's individual and collaborative activities. These components abstract microkernel functions and support user applications.

In computer science, deadlock prevention algorithms are used in concurrent programming when multiple processes must acquire more than one shared resource. If two or more concurrent processes obtain multiple resources indiscriminately, a situation can occur where each process has a resource needed by another process. As a result, none of the processes can obtain all the resources it needs, so all processes are blocked from further execution. This situation is called a deadlock. A deadlock prevention algorithm organizes resource usage by each process to ensure that at least one process is always able to get all the resources it needs. One such example of deadlock algorithm is Banker's algorithm.

The Chandy–Misra–Haas algorithm resource model checks for deadlock in a distributed system. It was developed by K. Mani Chandy, Jayadev Misra and Laura M Haas.

References

  1. Coulouris, George (2012). Distributed Systems Concepts and Design. Pearson. p. 716. ISBN   978-0-273-76059-7.
  2. Padua, David (2011). Encyclopedia of Parallel Computing. Springer. p. 524. ISBN   9780387097657. Archived from the original on 18 April 2021. Retrieved 16 October 2020.
  3. Falsafi, Babak; Midkiff, Samuel; Dennis, JackB; Dennis, JackB; Ghoting, Amol; Campbell, Roy H; Klausecker, Christof; Kranzlmüller, Dieter; Emer, Joel; Fossum, Tryggve; Smith, Burton; Philippe, Bernard; Sameh, Ahmed; Irigoin, François; Feautrier, Paul; Praun, Christoph von; Bocchino, Robert L.; Snir, Marc; George, Thomas; Sarin, Vivek; Jann, Joefon (2011). "Deadlocks". Encyclopedia of Parallel Computing. Boston, MA: Springer US. pp. 524–527. doi:10.1007/978-0-387-09766-4_282. ISBN   978-0-387-09765-7. S2CID   241456017. A deadlock is a condition that may happen in a system composed of multiple processes that can access shared resources. A deadlock is said to occur when two or more processes are waiting for each other to release a resource. None of the processes can make any progress.
  4. 1 2 3 Silberschatz, Abraham (2006). Operating System Principles (7th ed.). Wiley-India. p. 237. ISBN   9788126509621. Archived from the original on 25 January 2022. Retrieved 16 October 2020.
  5. Schneider, G. Michael (2009). Invitation to Computer Science. Cengage Learning. p. 271. ISBN   978-0324788594. Archived from the original on 18 April 2021. Retrieved 16 October 2020.
  6. Silberschatz, Abraham (2006). Operating System Principles (7 ed.). Wiley-India. p. 239. ISBN   9788126509621. Archived from the original on 18 April 2021. Retrieved 16 October 2020.
  7. Operating System Concepts. Wiley. 2012. p. 319. ISBN   978-1-118-06333-0.
  8. "ECS 150 Spring 1999: Four Necessary and Sufficient Conditions for Deadlock". nob.cs.ucdavis.edu. Archived from the original on 29 April 2018. Retrieved 29 April 2018.
  9. 1 2 3 Shibu, K. (2009). Intro To Embedded Systems (1st ed.). Tata McGraw-Hill Education. p. 446. ISBN   9780070145894. Archived from the original on 18 April 2021. Retrieved 16 October 2020.
  10. "Operating Systems: Deadlocks". www.cs.uic.edu. Archived from the original on 28 May 2020. Retrieved 25 April 2020. If a resource category contains more than one instance then the presence of a cycle in the resource-allocation graph indicates the possibility of a deadlock, but does not guarantee one. Consider, for example, Figures 7.3 and 7.4 below:
  11. Silberschatz, Abraham (2006). Operating System Principles (7 ed.). Wiley-India. p. 237. ISBN   9788126509621. Archived from the original on 18 April 2021. Retrieved 16 October 2020.
  12. 1 2 Stuart, Brian L. (2008). Principles of operating systems (1st ed.). Cengage Learning. p. 446. ISBN   9781418837693. Archived from the original on 18 April 2021. Retrieved 16 October 2020.
  13. 1 2 Tanenbaum, Andrew S. (1995). Distributed Operating Systems (1st ed.). Pearson Education. p. 117. ISBN   9788177581799. Archived from the original on 18 April 2021. Retrieved 16 October 2020.
  14. "Preface - Real-Time Interrupt-driven Concurrency". Archived from the original on 18 September 2020. Retrieved 1 October 2020.
  15. "IBM Knowledge Center". www.ibm.com. Archived from the original on 19 March 2017. Retrieved 29 April 2018.
  16. Silberschatz, Abraham (2006). Operating System Principles (7 ed.). Wiley-India. p. 244. ISBN   9788126509621. Archived from the original on 18 April 2021. Retrieved 16 October 2020.
  17. "Deadlock Avoidance Algorithms in Operating System (OS)". Electronics Mind. 26 January 2022.
  18. Ashcroft, E.A. (1975). "Proving assertions about parallel programs". Journal of Computer and System Sciences. 10: 110–135. doi: 10.1016/S0022-0000(75)80018-3 .
  19. Kwong, Y. S. (1979). "On the absence of livelocks in parallel programs". Semantics of Concurrent Computation. Lecture Notes in Computer Science. Vol. 70. pp. 172–190. doi:10.1007/BFb0022469. ISBN   3-540-09511-X.
  20. Anderson, James H.; Yong-jik Kim (2001). "Shared-memory mutual exclusion: Major research trends since 1986". Archived from the original on 25 May 2006.
  21. Zöbel, Dieter (October 1983). "The Deadlock problem: a classifying bibliography". ACM SIGOPS Operating Systems Review. 17 (4): 6–15. doi: 10.1145/850752.850753 . ISSN   0163-5980. S2CID   38901737.

Further reading