643 research outputs found

    Design of deadlock detection and prevention algorithms in distributed systems

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    A distributed system consists of a collection of processes which communicate with each other by exchanging messages to achieve a common goal. One of the key problems in distributed systems is the possibility of deadlock. Processes are said to be deadlocked when some processes are blocked on resource requests that can never be satisfied unless drastic systems action is taken. Two distributed deadlock detection algorithms handling multiple outstanding requests is proposed and are proven to be correct: it detects all cycles and does not detect false deadlocks. The algorithms are based on the concept of chasing the edge of the waitfor graph (probe-based). Simulation results show that the proposed algorithm performs very well compared to some existing algorithms. A deadlock prevention algorithm based on the notion of coloring the nodes of the waitfor graph is also proposed. Rollback is quite less compared to some existing algorithms

    Global state predicates in rough real-time

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    Distributed systems are characterized by the fact that the constituent processes have neither common memory nor a common system clock. These processes communicate solely via message passing. While providing a number of benefits such as increased reliability, increased computational power, and geographic dispersion, this architecture significantly complicates many of the tasks of software development and verification, including evaluation of the program state. In the case of distributed systems, the program state is comprised of the local states of the constituent processes, as well as the state of the channels between processes, and is called the global state.;With no common system clock, many distributed system protocols rely on the global ordering of local process events imposed by the message passing that occurs between processes. This leads to a partial global ordering of local process events, which can then be used to determine which process states could (or could not) have occurred simultaneously.;Traditional predicate evaluation protocols evaluate predicates on the global state of a distributed computation using consistent global states. This evaluation is complicated by the fact that the event ordering imposed by message passing is only partial. A complete history of the global states that occurred during an execution cannot always be constructed. This introduces inefficiency into predicate detection protocols and prohibits detection of certain predicates.;This dissertation explores the use of this rough global time base for global state predicate evaluation within distributed systems. By structuring the evaluation on the assumption that a global time base exists, we can develop simple and efficient protocols for both stable and unstable predicate evaluation. Further, we can evaluate certain predicates which are not easily evaluated using consistent global states. We demonstrate these advantages by developing protocols for detection of distributed termination, distributed deadlock detection, and detection of certain unstable predicates as they occur. as the global time base is rough, we can only detect unstable predicates which remain true for a sufficient duration. We additionally develop several formalizations which assist the protocol developer in dealing with the fact that the global time base is not perfect. We demonstrate the application of these formalizations within the protocols that we develop

    Performance measurements of distributed simulation strategies

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    Journal ArticleA multiprocessor-based, distributed simulation testbed is described that facilitates controlled experimentation with distributed simulation algorithms. The performance of simulation strategies using deadlock avoidance and deadlock detection and recovery techniques are examined using various synthetic and actual workloads. The distributed simulators are compared with a uniprocessor-based event list implementation. Results of a series of experiments demonstrate that message population and the degree to which processes can look ahead in simulated time play critical roles in the performance of distributed simulators using these algorithms. An "avalanche" phenomenon was observed in the deadlock detection and recovery simulator, and was found to be a necessary condition for achieving good performance. The central server queueing model was also examined. The poor behavior of this test case that has been observed by others is reproduced in the testbed, and explained in terms of message population and lookahead. Based on these observations, a modification to the server process program is suggested that improves performance by as much as an order of magnitude when firstcome- first-serve (FCFS) servers are used. These results demonstrate that conservative distributed simulation algorithms using deadlock avoidance or detection and recovery techniques can provide significant speedups over sequential event list implementations for some workloads, even in the presence of only a moderate amount of parallelism and many feedback loops. However, a moderate to high degree of parallelism is not sufficient to guarantee good performance

    A comparative study of concurrency control algorithms for distributed databases

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    The declining cost of computer hardware and the increasing data processing needs of geographically dispersed organizations have led to substantial interest in distributed data management. These characteristics have led to reconsider the design of centralized databases. Distributed databases have appeared as a result of those considerations. A number of advantages result from having duplicate copies of data in a distributed databases. Some of these advantages are: increased data accesibility, more responsive data access, higher reliability, and load sharing. These and other benefits must be balanced against the additional cost and complexity introduced in doing so. This thesis considers the problem of concurrency control of multiple copy databases. Several synchronization techniques are mentioned and a few algorithms for concurrency control are evaluated and compared

    Distributed discrete-event simulation in Concurrent C

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    Call number: LD2668 .T4 CMSC 1989 V67Master of ScienceComputing and Information Science

    Real-Time Concurrency Control Protocol Based on Accessing Temporal Data

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    RITSim: distributed systemC simulation

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    Parallel or distributed simulation is becoming more than a novel way to speedup design evaluation; it is becoming necessary for simulating modern processors in a reasonable timeframe. As architectural features become faster, smaller, and more complex, designers are interested in obtaining detailed and accurate performance and power estimations. Uniprocessor simulators may not be able to meet such demands. The RITSim project uses SystemC to model a processor microarchitecture and memory subsystem in great detail. SystemC is a C++ library built on a discrete-event simulation kernel. Many projects have successfully implemented parallel discrete-event simulation (PDES) frameworks to distribute simulation among several hosts. The field promises significant simulation speedup, possibly leading to faster turnaround time in design space exploration and commercial production. However, parallel implementation of such simulators is not an easy task. It requires modification of the simulation kernel for effective partitioning and synchronization. This thesis explores PDES techniques and presents a distributed version of the SystemC simulation environment. With minimal user interaction, SystemC models can executed on a cluster of workstations using a message-passing library such as the Message Passing Interface (MPI). The implementation is designed for transparency; distribution and synchronization happen with little intervention by the model author. Modification of SystemC is fashioned to promote maintainability with future releases. Furthermore, only freely available libraries are used for maximum flexibility and portability

    Transaction processing in real-time database systems

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    Scheduling transactions in a real-time database requires an integrated approach in which the schedule does not only guarantee execution before the deadline, but also maintains data consistency. The problem has been studied under a common framework which considers both concurrency control issues and the real-time constraints in centralized and distributed transaction processing. A real-time transaction processing model has been defined for a centralized system. The proposed protocols use a unified approach to maximize concurrency while meeting real-time constraints at the same time. In order to test the behavior of the model and the proposed protocols, a real-time transaction processing testbed has been developed using discrete event simulation techniques. The results indicate that different protocols work better under different load scenarios and that the overall performance can be significantly enhanced by modifying the underlying system configuration. Among other system and transaction parameters, the effect of data partitioning, buffer management, preemption, disk contention, locking mode and multiprocessing has been studied;For the distributed environment, new concepts of real-time nested transactions and priority propagation have been proposed. Real-time nested transactions incorporate the deadline requirements in the hierarchical structure of nested transactions. Priority propagation addresses the issues related to transaction aborts in real-time nested transaction processing. The notion of priority ceiling has been used to avoid the priority inversion problem. The proposed protocols exhibit freedom from deadlock and have tightly bounded waiting period. Both of these properties make them very suitable for distributed real-time transaction processing environment
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