40618061
Transaction Recovery in Distributed DB/DC Systems: A Progressive Approach
10753893
Evaluation of Error Recovery Blocks Used for Cooperating Processes
Three alternatives for implementing recovery blocks (RB's) are conceivable for backward error recovery in concurrent processing. These are the asynchronous, synchronous, and the pseudorecovery point implementations. Asynchronous RB's are based on the concept of maximum autonomy in each of concurrent processes. Consequently, establishment of RB's in a process is made independently of others and unbounded rollback propagations become a serious problem. In order to completely avoid unbounded rollback propagations, it is necessary to synchronize the establishment of recovery blocks in all cooperating processes. Process autonomy is sacrificed and processes are forced to wait for commitments from others to establish a recovery line, leading to inefficiency in time utilization. As a compromise between asynchronous and synchronous RB's we propose to insert pseudorecovery points (PRP's) so that unbounded rollback propagations may be avoided while maintaining process autonomy. We developed probabilistic models for analyzing these three methods under standard assumptions in computer performance analysis, i.e., exponential distributions for related random variables. With these models we have estimated 1) the interval between two successive recovery lines for asynchronous RB's, 2) mean loss in computation power for the synchronized method, and 3) additional overhead and rollback distance in case PRP's are used.
17765159
VLSI Circuit Testing Using an Adaptive Optimization Model
The purpose of testing is to determine the correctness of the unit under test in come optimal way. One difficulty in meeting the optimality requirement is that the stochastic properties of the unit are usually unknown a priori. For instance, one might not know exactly the yield of a VLSI production line before one tests the chips made as a result. Given the probability of unit failure and the coverage of a test, the optimal test period is easy to obtain. However, the probability of failure is not usually known a priori. We therefore develop an optimal sequential testing strategy which estimates the production yield based on ongoing test results, and then use it to determine the optimal test period.
8777661
Adaptive transaction routing in a heterogeneous database environment
The issue of transaction routing in a heterogeneous database environment is examined where transaction characteristics like reference locality implies that certain processing systems can be identified as being, in general, more suitable than others for a given transaction class. Routing which ignores these distinctions in an attempt to balance system load can degrade system performance. An adaptive routing strategy is considered which: (1) estimates the response time based on a steady-state analysis; (2) monitors how well actual response time conforms to the estimate; and (3) adaptively adjusts future estimates through a feedback control based on (2). It is found that the adaptive strategy greatly enhances performance robustness as compared to the results of the strategy without feedback. The feedback process used alleviates the sensitivity to accurate estimations of workload and system parameters. Various simulation studies are used to illustrate the adaptive strategy's robustness.<<ETX>>
8597522
Optimal resource control in periodic real-time environments
Three factors determine the optimum configuration of a multiprocessor at any epoch: the workload, the reward structure, and the state of the computer system. An algorithm is presented for the optimal (more realistically, quasi-optimal) configuration of such systems used in real-time applications with periodic reward rates and workloads. The algorithm is based on Markov decision theory. It is suggested that a change in the workload or the reward structure should be as powerful a motivation for reconfiguration as component failure. Such changes occur naturally over the course of operation: an example of an online transaction processing system with a workload and reward structure that has a period of a day is given.<<ETX>>
11078936
Software architecture supporting integrated real-time systems
To achieve reliability, reusability, and cost reduction, a significant trend in building large complex real-time systems is to integrate separate application modules of different criticalities in a common hardware platform. An essential requirement of integrated real-time systems is to guarantee spatial and temporal partitioning among applications in order te ensure an exclusive access of physical and temporal resources to the applications. In this paper we propose software architecture, implemented as SPIRIT-µKernel, for strongly partitioned integrated real-time systems. The SPIRIT-µKernel has been designed and implemented based on a two-level hierarchical scheduling methodology such that the real-time constraints of each application can be guaranteed. To demonstrate the feasibility of the SPIRIT-µKernel, we have ported two real-time operating systems (RTOS), WindRiver's VxWorks and Cygnus's eCos, on the top of the microkernel. Thus, different RTOS can be applied in various partitions to provide required features for each application. Based on the measured performance results, the SPIRIT-µKernel architecture is practical and appealing due to its low overheads of kernel services and the support for dependable integration of real-time applications via scheduling algorithm.
2543653
Extracting and Learning an Unknown Grammar with Recurrent Neural Networks
Simple second-order recurrent networks are shown to readily learn small known regular grammars when trained with positive and negative strings examples. We show that similar methods are appropriate for learning unknown grammars from examples of their strings. The training algorithm is an incremental real-time, recurrent learning (RTRL) method that computes the complete gradient and updates the weights at the end of each string. After or during training, a dynamic clustering algorithm extracts the production rules that the neural network has learned. The methods are illustrated by extracting rules from unknown deterministic regular grammars. For many cases the extracted grammar outperforms the neural net from which it was extracted in correctly classifying unseen strings.
2928406
Tuning Schema Matching Software using Synthetic Scenarios
Most recent schema matching systems assemble multiple components, each employing a particular matching technique. The domain user must then tune the system: select the right component to be executed and correctly adjust their numerous "knobs" (e.g., thresholds, formula coefficients). Tuning is skill- and time-intensive, but (as we show) without it the matching accuracy is significantly inferior.We describe eTuner, an approach to automatically tune schema matching systems. Given a schema S, we match S against synthetic schemas, for which the ground truth mapping is known, and find a tuning that demonstrably improves the performance of matching S against real schemas. To efficiently search the huge space of tuning configurations, eTuner works sequentially, starting with tuning the lowest level components. To increase the applicability of eTuner, we develop methods to tune a broad range of matching components. While the tuning process is completely automatic, eTuner can also exploit user assistance (whenever available) to further improve the tuning quality. We employed eTuner to tune four recently developed matching systems on several real-world domains. eTuner produced tuned matching systems that achieve higher accuracy than using the systems with currently possible tuning methods, at virtually no cost to the domain user.
10452928
Detecting truncation point in steady-state simulation using chaos theory
In the steady-state simulation, it is important to identify initialization bias for the correct estimates of the simulation model under study. In this paper, the methods from chaos theory are applied to the determination of truncation points in the simulation data for controlling the initial bias. Two methods are proposed and evaluated based on their effectiveness for estimating the average waiting time in M/M/1(/spl infin/) queueing model.
9854601
An effective recovery under fuzzy checkpointing in main memory databases
Abstract In main memory databases, fuzzy checkpointing gives less transaction overhead due to its asynchronous backup feature. However, till now, fuzzy checkpointing has considered only physical logging schemes. The size of the physical log records is very large, and hence it incurs space and recovery processing overhead. In this paper, we propose a recovery method based on a hybrid logging scheme, which permits logical logging under fuzzy checkpointing. The proposed method significantly reduces the size of log data, and hence offers faster recovery processing than other conventional fuzzy checkpointing with physical logging.
14282973
Closing the Gap: Learning-Based Information Extraction Rivaling Knowledge-Engineering Methods
In this paper, we present a learning approach to the scenario template task of information extraction, where information filling one template could come from multiple sentences. When tested on the MUC-4 task, our learning approach achieves accuracy competitive to the best of the MUC-4 systems, which were all built with manually engineered rules. Our analysis reveals that our use of full parsing and state-of-the-art learning algorithms have contributed to the good performance. To our knowledge, this is the first research to have demonstrated that a learning approach to the full-scale information extraction task could achieve performance rivaling that of the knowledge engineering approach.