https://digital.library.unt.edu/ark:/67531/metadc891681/m2/1/high_res_d/886897.pdf

Survey of sampling-based methods for uncertainty and sensitivity analysis

/pdf/reversibility-and-stochastic-networks-17kl9p5ino.pdf

Reversibility and Stochastic Networks

Optimization of computer simulation models with rare events

In a path-breaking paper last year Pat and Betty O’Neil and Gerhard Weikum pro posed a self-tuning improvement to the Least Recently Used (LRU) buffer management algorithm[l5]. Their improvement is called LRU/k and advocates giving priority to buffer pages baaed on the kth most recent access. (The standard LRU algorithm is denoted LRU/l according to this terminology.) If Pl’s kth most recent access is more more recent than P2’s, then Pl will be replaced after P2. Intuitively, LRU/k for k > 1 is a good strategy, because it gives low priority to pages that have been scanned or to pages that belong to a big randomly accessed file (e.g., the account file in TPC/A). They found that LRU/S achieves most of the advantage of their method. The one problem of LRU/S is the processor

2Q: A Low Overhead High Performance Buffer Management Replacement Algorithm

/pdf/x3-a-low-overhead-high-performance-buffer-management-5endlxecqs.pdf

X3: A Low Overhead High Performance Buffer Management Replacement Algorithm *

The authors present a unified framework for simulating Markovian models of highly dependable systems. It is shown that a variance reduction technique called importance sampling can be used to speed up the simulation by many orders of magnitude over standard simulation. This technique can be combined very effectively with regenerative simulation to estimate measures such as steady-state availability and mean time to failure. Moveover, it can be combined with conditional Monte Carlo methods to quickly estimate transient measures such as reliability, expected interval availability, and the distribution of interval availability. The authors show the effectiveness of these methods by using them to simulate large dependability models. They discuss how these methods can be implemented in a software package to compute both transient and steady-state measures simultaneously from the same sample run. >

A unified framework for simulating Markovian models of highly dependable systems

Three aspects of the modeling of multiversion software are considered. First, the beta-binomial distribution is proposed for modeling correlated failures in multiversion software. Second, a combinatorial model for predicting the reliability of a multiversion software configuration is presented. This model can take as inputs failure distributions either from measurements or from a selected distribution (e.g. beta-binomial). Various recovery methods can be incorporated in this model. Third, the effectiveness of the community error recovery method based on checkpointing is investigated. This method appears to be effective only when the failure behaviors of program versions are lightly correlated. Two different types of checkpoint failure are also considered: an omission failure where the correct output is recognized at a checkpoint but the checkpoint fails to correct the wrong outputs and a destructive failure where the good versions get corrupted at a checkpoint. >

Modeling of correlated failures and community error recovery in multiversion software

With the ever-increasing complexity and requirements of highly dependable systems, their evaluation during design and operation is becoming more crucial. Realistic models of such systems are often not amenable to analysis using conventional analytic or numerical methods. Therefore, analysts and designers turn to simulation to evaluate these models. However, accurate estimation of dependability measures of these models requires that the simulation frequently observes system failures, which are rare events in highly dependable systems. This renders ordinary Simulation impractical for evaluating such systems. To overcome this problem, simulation techniques based on importance sampling have been developed, and are very effective in certain settings. When importance sampling works well, simulation run lengths can be reduced by several orders of magnitude when estimating transient as well as steady-state dependability measures. This paper reviews some of the importance-sampling techniques that have been developed in recent years to estimate dependability measures efficiently in Markov and nonMarkov models of highly dependable systems.

/pdf/techniques-for-fast-simulation-of-models-of-highly-3hogjs04fi.pdf

Techniques for fast simulation of models of highly dependable systems

The CLOCK algorithm is a popular buffer replacement algorithm because of its simplicity and its ability to approximate the performance of the Least Recently Used (LRU) replacement policy. The Generalized Clock (GCLOCK) buffer replacement policy uses a circular buffer and a weight associated with each page brought in buffer to decide on which page to replace. We develop an approximate analysis for the GCLOCK policy under the Independent Reference Model (IRM) that applies to many database transaction processing workloads. We validate the analysis for various workloads with data access skew. Comparison with simulations shows that in all cases examined the error is extremely small (less than 1%). To show the usefulness of the model we apply it to a Transaction Processing Council benchmark A (TPC-A) like workload. If knowledge of the different data partitions in this workload is assumed, the analysis shows that, with appropriate choice of weights, the performance of the GCLOCK algorithm can be better than the LRU policy. Performance very close to that for optimal (static) buffer allocation can be achieved by assigning sufficiently high weights, and can be implemented with a reasonably low overhead. Finally, we outline how the model can be extended to capture the effect of page invalidation in a multinode system.

/pdf/analysis-of-the-generalized-clock-buffer-replacement-scheme-277yiacd6e.pdf

Victor F. Nicola

Papers

A unified framework for simulating Markovian models of highly dependable systems

Modeling of correlated failures and community error recovery in multiversion software

Techniques for fast simulation of models of highly dependable systems

Analysis of the generalized clock buffer replacement scheme for database transaction processing

On modelling the performance and reliability of multimode computer systems