this paper, we use the terms event logging and message logging interchangeably

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In this paper, we propose a quasi-synchronous checkpointing algorithm and a low-overhead recovery algorithm based on it. The checkpointing algorithm preserves process autonomy by allowing them to take checkpoints asynchronously and uses communication-induced checkpoint coordination for the progression of the recovery line which helps bound rollback propagation during a recovery. Thus, it has the easeness and low overhead of asynchronous checkpointing and the recovery time advantages of synchronous checkpointing. There is no extra message overhead involved during checkpointing and the additional checkpointing overhead is nominal. The algorithm ensures the existence of a recovery line consistent with the latest checkpoint of any process all the time. The recovery algorithm exploits this feature to restore the system to a state consistent with the latest checkpoint of a failed process. The recovery algorithm has no domino effect and a failed process needs only to rollback to its latest ch...

Abstract not found

Consider the problem of transparently recovering an asynchronous distributed computation when one or more processes fail. Basing rollback recovery on optimistic message loggingand replay is desirable for several reasons, including not requiring synchronization between processes during failure-free operation. However, previous optimistic rollback recovery protocols either have required synchronization during recovery, or have permitted a failure at one process to potentially trigger an exponential number of process rollbacks. In this paper, we present an optimistic rollback recovery protocol that provides completely asynchronous recovery, while also reducing the number of times a process must roll back in response to a failure to at most one. This protocol is based on comparing timestampvectors across multiple levels of partial order time.

AbstractÐMobile computing raises many new issues such as lack of stable storage, low bandwidth of wireless channel, high mobility, and limited battery life. These new issues make traditional checkpointing algorithms unsuitable. Coordinated checkpointing is an attractive approach for transparently adding fault tolerance to distributed applications since it avoids domino effects and minimizes the stable storage requirement. However, it suffers from high overhead associated with the checkpointing process in mobile computing systems. Two approaches have been used to reduce the overhead: First is to minimize the number of synchronization messages and the number of checkpoints; the other is to make the checkpointing process nonblocking. These two approaches were orthogonal previously until the Prakash-Singhal algorithm [28] combined them. However, we [8] found that this algorithm may result in an inconsistency in some situations and we proved that there does not exist a nonblocking algorithm which forces only a minimum number of processes to take their checkpoints. In this paper, we introduce the concept of ªmutable checkpoint,º which is neither a tentative checkpoint nor a permanent checkpoint, to design efficient checkpointing algorithms for mobile computing systems. Mutable checkpoints can be saved anywhere, e.g., the main memory or local disk of MHs. In this way, taking a mutable checkpoint avoids the overhead of transferring large amounts of data to the stable storage at MSSs over the wireless network. We present techniques to minimize the number of mutable checkpoints. Simulation results show that the overhead of taking mutable checkpoints is negligible. Based on mutable checkpoints, our nonblocking algorithm avoids the avalanche effect and forces only a minimum number of processes to take their checkpoints on the stable storage. Index TermsÐMobile computing, coordinated checkpointing, causal dependency, nonblocking. æ

This paper presents an index-based checkpointing algorithm for distributed systems with the aim of reducing the total number of checkpoints while ensuring that each checkpoint belongs to at least one consistent global checkpoint (or recovery line). The algorithm is based on an equivalence relation de ned between pairs of successive checkpoints of a process which allows, in some cases, to advance the recovery line of the computation without forcing checkpoints in other processes. The algorithm is well suited for autonomous and heterogeneous environments where each process does not know any private information about other processes and private information of the same type of distinct processes is not related (e.g., clock granularity, localcheckpointing strategy, etc.). We also present asimulation study which compares the checkpointing-recovery overhead of this algorithm to the ones of previous solutions.

A useless checkpoint is a local checkpoint that cannot be part of a consistent global checkpoint. This paper addresses the following important problem. Given a set of processes that take (basic) local checkpoints in an independent and unknown way, the problem is to design a communication-induced checkpointing protocol that directs processes to take additional local (forced) checkpoints to ensure that no local checkpoint is useless. A general and efficient protocol answering this problem is proposed. It is shown that several existing protocols that solve the same problem are particular instances of it. The design of this general protocol is motivated by the use of communication-induced checkpointing protocols in “consistent global checkpoint”-based distributed applications. Detection of stable or unstable properties, rollback-recovery, and determination of distributed breakpoints are examples of such applications.

This paper is an exploration of diskless checkpointing for distributed scientific computations. With the widespread use of the "Network Of Workstation" (NOW) platform for distributed computing, long-running scientific computations need to tolerate the changing and often faulty nature of NOW environments. We present high-performance implementations of several algorithms for distributed scientific computing, including Cholesky factorization, LU factorization, QR factorization, and preconditioned conjugate gradient. These implementations are able to run on PVM networks of at least N processors, and can complete with low overhead as long as any N processors remain functional. We discuss the details of how the algorithms are tuned for fault-tolerance, and present the performance results on a PVM network of SUN workstations, and on the IBM SP2.

Networks of workstations (NOWs) offer a cost effective platform for high-performance, long-running parallel computations. However, these computations must be able to tolerate the changing and often faulty nature of NOW environments. We present high-performance implementations of several fault-tolerant algorithms for distributed scientific computing. The fault-tolerance is based on diskless checkpointing, a paradigm that uses processor redundancy rather than stable storage as the fault-tolerant medium. These algorithms are able to run on clusters of workstations that change over time due to failure, load or availability. As long as there are at least n processors in the cluster, and failures occur singly, the computation will complete in an efficient manner. We discuss the details of how the algorithms are tuned for fault-tolerance and present the performance results on a PVM network of Sun workstations connected by a fast, switched ethernet.