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Deadlocks in Distributed Systems

Deadlocks in Distributed Systems. Ryan Clemens, Thomas Levy, Daniel Salloum , Tagore Kolluru , Mike DeMauro. Outline. Distributed systems Deadlock basics Strategies Algorithms Simulation. What is a distributed system?. A collection of sites which communicate via message passing.

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Deadlocks in Distributed Systems

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  1. Deadlocks in Distributed Systems Ryan Clemens, Thomas Levy, Daniel Salloum, Tagore Kolluru, Mike DeMauro

  2. Outline • Distributed systems • Deadlock basics • Strategies • Algorithms • Simulation

  3. What is a distributed system? • A collection of sites which communicate via message passing. • Centralized • Decentralized

  4. What is a deadlock? • A deadlock occurs when all elements of a set, comprised of multiple processes, request a resource which is held by another process in the set. • In distributed systems, a deadlock may arise when waiting for messages in addition to resources.

  5. Conditions for a Deadlock • Necessary • Mutual Exclusion • Hold and Wait • No Preemption  • Sufficient • Circular Wait

  6. Mutual Exclusion • When one process enters its critical state while accessing a resource no other process can enter their critical state to access the same resource. • Without this, multiple processes could access the same resource, which would mean they would not have to wait, which would prevent the deadlock. • This would cause data corruption. • When messages are the resources, mutual exclusion is guaranteed.

  7. Hold and Wait • Occurs when a process gathers and retains certain resources, but is still awaiting other resources before it can continue execution. • Without this, there could be no deadlocks because if process A is waiting on a resource held by process B, process B is guaranteed to be able to proceed. • This limits what we can program.

  8. No Preemption • No process can take resources held by another process. • If preemption is allowed and mutual exclusion is maintained, once a resource has been preempted, the process which previously had the resource needs to be placed in a state where it no longer has it. • This may mean killing the process. • If there is no mutual exclusion, there can be no concept of preemption.

  9. Circular Wait • A set of nodes with transitive relationship are in circular wait if the dependency chain of a node leads back to itself. • Without this, the dependency graph becomes a directed acyclic graph, which will have a sink which can continue. • The standard way of preventing circular wait is to create a partial ordering of the resources and only allow a process to request resources which are higher in the ordering than the current highest held. • This is inconvenient if the resources needed by a process are not known beforehand.

  10. Prevention • Prevention is preventing a process from requesting a resource which would lead to a deadlock. • A standard method of prevention is to force processes to acquire all their required resources before execution. • Another method is to remove one of the four conditions for deadlocks.

  11. Avoidance • Avoidance is when a resource is granted to a process only when the resulting state is safe. • A safe state if there is an execution sequence which does not lead to a deadlock. • Banker’s algorithm: This algorithm needs to know the current amount of available resources the system has free, the amount of resources each process has, and an upper bound on the amount of resources each process will hold during its execution. It will only grant a request for resources to a process if it leaves the system with enough resources to fulfill the biggest possible request for resources for at least one process.

  12. Detection • No resource checking done in advance • State is stored in some fashion • Periodically checks state for deadlocks

  13. Graphs • a) Resource Allocation Graph (Transaction Wait For) • b) Wait For Graph (WFG)

  14. Recovery • Kill Member of Detected Deadlock • Random Kill • Priority Kill • Kill Youngest • Time-out approach

  15. Distributed Issues • False (Phantom) Deadlock • Detection

  16. Algorithm Considerations • Message Passing • Traffic • Length • Resolution Efficiency

  17. Resource Models • Single-resource • AND • OR • AND-OR

  18. Detection Algorithm Classes • Path-Pushing • Edge-Chasing (probe based) • Diffusing Computations • Global State Detection

  19. Selected Algorithms • Obermarck’s • Path-Pushing • AND model • Obsoleted for inaccurate WFG • Hermann and Chandy’s • AND-OR • Diffusing computation • Bracha and Toueg’s • AND-OR • Global state detection

  20. Algorithms • Mitchell and Merritt’s • Single-Resource • Edge chasing • Benefits • Simple • Only one cycle detects deadlock • Not always phantom deadlocks • Complexity – O(s(s-1)/2)

  21. Chandy and Misra’s Algorithm • Multiple Resource • Diffusing computation • AND Model • Complexity: O(N(N-1))

  22. Algorithms • Probe-based Algorithms • Chandy-Mirsa-Haas • Roesler • Hierarchical Algorithms • Ho-Ramamoorthy

  23. Algorithms (cont) • Online deadlock detection (Isloor-Marsland) • Immediate deadlock detection

  24. Difficulty of Proof • TWF graphs can form in many ways, which makes it difficult to study all situations • Deadlocks are sensitive to the timing of requests • In distributed systems, message latency is unpredictable and there is no global memory

  25. Requirements foralgorithm correctness • At least one process can proceed • No process will be restarted an indefinite number of times

  26. Simulation • Partial reversion of process instead of killing it • Uses a WFG of the entire system to detect deadlocks • This algorithm honors mutual exclusion and implements preemption. • Causes more data corruption than simply killing the youngest process. • A solution to this is programmers writing their code anticipating the possibility of a reversion.

  27. References • Knapp, Edgar. Deadlock detection in distributed databases, ACM Computing Surveys, Volume 19 Issue 4, Dec. 1987 • NatalijaKrivokapić, Alfons Kemper, Ehud Gudes. Deadlock detection in distributed database systems: a new algorithm and a comparative performance analysis. The VLDB Journal — The International Journal on Very Large Data Bases , Volume 8 Issue 2, October 1999 • doi:10.1007/s007780050075 • URL: http://portal.acm.org/citation.cfm?id=765509.765510&coll=DL&dl=ACM&CFID=17423245&CFTOKEN=33985983 • Singhal, M.; , "Deadlock detection in distributed systems," Computer , vol.22, no.11, pp.37-48, Nov 1989 • doi: 10.1109/2.43525URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=43525&isnumber=1667

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