模块化本体缓存方案

该文提出了一种模块化本体缓存方案,使用该方案能够缩短本体推理的平均时间。给出了缓存的对象和缓存一致性检查方法,通过中断方式和增量模式传递知识更新信息,能够减少通信量和提高更新的效率。     

Autonomic self healing and recovery informed by environment knowledge

An important goal of autonomic computing is the development of computing systems that are capable of self healing with a minimum of human intervention. Typically, recovery from even a simple fault will require knowledge of the environment in which a computing system operates. To meet this need, we present an approach to self healing and recovery informed by environment knowledge that combines case based reasoning (CBR) and rule based reasoning. Specifically, CBR is used for fault diagnosis and rule based reasoning for fault remediation, recovery, and referral. We also show how automated information gathering from available sources in a computing system’s environment can increase problem solving efficiency and help to reduce the occurrence of service failures. Finally, we demonstrate the approach in an intelligent system for fault management in a local printer network.     

基于不变量查找的German协议验证

提出了一种通过查找缓存一致性协议不变量来验证带参协议正确性的新方法.缓存一致性协议验证的难点在于必须证明协议对于任意大小的带参系统都成立.我们通过寻找不变量和协议规则之间的对应关系来计算辅助不变量,从而帮助推导验证缓存一致性协议.我们设计实现了一个不变量查找工具并将该工具应用到German协议上计算它们的辅助不变量并成功地验证了协议的安全性质.     

Exchange market equilibria with Leontief’s utility: Freedom of pricing leads to rationality

This paper studies the equilibrium property and algorithmic complexity of the exchange market equilibrium problem with concave piecewise linear functions, which include linear and Leontief’s utility functions as special cases. We show that the Fisher model again reduces to the weighted analytic center problem, and the same linear programming complexity bound applies to computing its equilibrium. However, the story for the Arrow–Debreu model with Leontief’s utility becomes quite different. We show that, for the first time, solving this class of Leontief exchange economies is equivalent to solving a linear complementarity problem whose algorithmic complexity is finite but not polynomially bounded.     

A method of learning implication networks from empirical data:algorithm and Monte-Carlo simulation-based validation

The paper describes an algorithmic means for inducing implication networks from empirical data samples. The induced network enables efficient inferences about the values of network nodes if certain observations are made. This implication induction method is approximate in nature as probabilistic network requirements are relaxed in the construction of dependence relationships based on statistical testing. In order to examine the effectiveness and validity of the induction method, several Monte Carlo simulations were conducted, where theoretical Bayesian networks were used to generate empirical data samples-some of which were used to induce implication relations, whereas others were used to verify the results of evidential reasoning with the induced networks. The values in the implication networks were predicted by applying a modified version of the Dempster-Shafer belief updating scheme. The results of predictions were, furthermore, compared to the ones generated by Pearl's (1986) stochastic simulation method, a probabilistic reasoning method that operates directly on the theoretical Bayesian networks. The comparisons consistently show that the results of predictions based on the induced networks would be comparable to those generated by Pearl's method, when reasoning in a variety of uncertain knowledge domains-those that were simulated using the presumed theoretical probabilistic networks of different topologies     

动态调整移动数据库中失效报告时间窗口的大小

在移动计算环境中，如何维护移动客户机中数据缓存的一致性，是研究的一个热点．广播失效报告是一种有效的方法，但由于不同的环境，不同的时期各种参数的变化，失效报告时间窗口ω的大小如何确定是一个难点．时间窗口ω应随各种参数的变化而不断地进行调整，才能保证网络系统的传输工作在最有效的状态．从理论上推导了失效报告时间窗口ω的计算公式，分析了ω的合理取值，并给出了具体实现的算法．     

Scientific computation for simulations on programmable graphics hardware

Graphics processor units (GPUs) have emerged as powerful parallel processors in recent years. Although floating point computations and high level programming languages are now available, the efficient use of the enormous computing power of GPUs still requires a significant amount of graphics specific knowledge.The paper explains how to use GPUs for scientific computations without graphics specific terminology. It offers an algorithmic view on GPUs with comparisons to cache aware and parallel programming of CPUs. Two typical simulation techniques, namely grid based and particle based methods are discussed.     

Optimizing graph algorithms for improved cache performance

We develop algorithmic optimizations to improve the cache performance of four fundamental graph algorithms. We present a cache-oblivious implementation of the Floyd-Warshall algorithm for the fundamental graph problem of all-pairs shortest paths by relaxing some dependencies in the iterative version. We show that this implementation achieves the lower bound on processor-memory traffic of /spl Omega/(N/sup 3///spl radic/C), where N and C are the problem size and cache size, respectively. Experimental results show that this cache-oblivious implementation shows more than six times the improvement in real execution time over that of the iterative implementation with the usual row major data layout, on three state-of-the-art architectures. Second, we address Dijkstra's algorithm for the single-source shortest paths problem and Prim's algorithm for minimum spanning tree problem. For these algorithms, we demonstrate up to two times the improvement in real execution time by using a simple cache-friendly graph representation, namely adjacency arrays. Finally, we address the matching algorithm for bipartite graphs. We show performance improvements of two to three times in real execution time by using the technique of making the algorithm initially work on subproblems to generate a suboptimal solution and, then, solving the whole problem using the suboptimal solution as a starting point. Experimental results are shown for the Pentium III, UltraSPARC III, Alpha 21264, and MIPS R12000 machines.     

Large‐Scale Integer Linear Programming for Orientation Preserving 3D Shape Matching

We study an algorithmic framework for computing an elastic orientation‐preserving matching of non‐rigid 3D shapes. We outline an Integer Linear Programming formulation whose relaxed version can be minimized globally in polynomial time. Because of the high number of optimization variables, the key algorithmic challenge lies in efficiently solving the linear program. We present a performance analysis of several Linear Programming algorithms on our problem. Furthermore, we introduce a multiresolution strategy which allows the matching of higher resolution models.     

An energy efficient re-access scheme for data caching in data broadcast of a mobile computing environment

Data caching is used to improve the response time and the power consumption of a mobile client in a mobile computing environment. To enhance the performance of data caching, one needs to improve the hit ratio and to reduce the cost in processing a cache miss. In a mobile computing environment, a cached data item of a mobile client needs to remain up-to-date with respect to its corresponding data item in the server. A cached data item which is out of date is called a cached invalidated data item. Accessing a cached invalidated data item can be regarded as processing a cache miss. To access a cached invalidated data item, a mobile client needs to download the new content of the data item from the broadcast channel. This operation is called a re-access operation in this paper. Re-accessing a cached invalidated data item incurs large tuning time overhead. In this paper, we propose a re-access scheme that reduces this overhead by allowing a mobile client to access a cached invalidated data item from the broadcast channel without accessing indices. We analyze the performance of the proposed scheme and validate the analysis through experiments. The experiments showed that the proposed scheme significantly reduces the tuning time of a mobile client. Furthermore, the proposed scheme is robust in the sense that it allows changes on the broadcast structure in data broadcasting.     

Temporal Bayesian Knowledge Bases – Reasoning about uncertainty with temporal constraints

Time is ubiquitous. Accounting for time and its interaction with change is crucial to modeling the dynamic world, especially in domains whose study of data is sensitive to time such as in medical diagnosis, financial investment, and natural language processing, to name a few. We present a framework that incorporates both uncertainty and time in its reasoning scheme. It is based on an existing knowledge representation called Bayesian Knowledge Bases. It provides a graphical representation of knowledge, time and uncertainty, and enables probabilistic and temporal inferencing. The reasoning scheme is probabilistically sound and the fusion of temporal fragments is well defined. We will discuss some properties of this framework and introduce algorithms to ensure groundedness during the construction of the model. The framework has been applied to both artificial and real world scenarios.     

An expiration age-based document placement scheme for cooperative Web caching

The sharing of caches among proxies is an important technique to reduce Web traffic, alleviate network bottlenecks, and improve response time of document requests. Most existing work on cooperative caching has been focused on serving misses collaboratively. Very few have studied the effect of cooperation on document placement schemes and its potential enhancements on cache hit ratio and latency reduction. We propose a new document placement scheme which takes into account the contentions at individual caches in order to limit the replication of documents within a cache group and increase document hit ratio. The main idea of this new scheme is to view the aggregate disk space of the cache group as a global resource of the group and uses the concept of cache expiration age to measure the contention of individual caches. The decision of whether to cache a document at a proxy is made collectively among the caches that already have a copy of this document. We refer to this new document placement scheme as the Expiration Age-based scheme (EA scheme). The EA scheme effectively reduces the replication of documents across the cache group, while ensuring that a copy of the document always resides in a cache where it is likely to stay for the longest time. We report our study on the potentials and limits of the EA scheme using both analytic modeling and trace-based simulation. The analytical model compares and contrasts the existing (ad hoc) placement scheme of cooperative proxy caches with our new EA scheme and indicates that the EA scheme improves the effectiveness of aggregate disk usage, thereby increasing the average time duration for which documents stay in the cache. The trace-based simulations show that the EA scheme yields higher hit rates and better response times compared to the existing document placement schemes used in most of the caching proxies.     

Probabilistic knowledge representation using the principle of maximum entropy and Gröbner basis theory

An often used methodology for reasoning with probabilistic conditional knowledge bases is provided by the principle of maximum entropy (so-called MaxEnt principle) that realises an idea of least amount of assumed information and thus of being as unbiased as possible. In this paper we exploit the fact that MaxEnt distributions can be computed by solving nonlinear equation systems that reflect the conditional logical structure of these distributions. We apply the theory of Gröbner bases that is well known from computational algebra to the polynomial system which is associated with a MaxEnt distribution, in order to obtain results for reasoning with maximum entropy. We develop a three-phase compilation scheme extracting from a knowledge base consisting of probabilistic conditionals the information which is crucial for MaxEnt reasoning and transforming it to a Gröbner basis. Based on this transformation, a necessary condition for knowledge bases to be consistent is derived. Furthermore, approaches to answering MaxEnt queries are presented by demonstrating how inferring the MaxEnt probability of a single conditional from a given knowledge base is possible. Finally, we discuss computational methods to establish general MaxEnt inference rules.     

On‐demand data co‐allocation with user‐level cache for grids

Conventional remote data access middlewares usually provide client applications with either a pre‐staging scheme or an on‐demand access scheme to fetch data. The pre‐staging scheme uses parallel downloads to fetch a completed input file from multiple data sources, even when only a tiny file fragment is required. Such a transfer scheme consumes unnecessary data transmission time and storage space. In contrast, the on‐demand scheme downloads only the required data blocks from a single data source and does not fully utilize the downstream bandwidth of the computing nodes. This paper presents a middleware called ‘Spigot’ that facilitates legacy (grid‐unaware) applications to transparently access remote data by using native I/O function calls. Spigot uses the on‐demand concept to avoid unnecessary data transfer and adopts a co‐allocation download algorithm to improve the data transfer performance. Moreover, it uses the pre‐fetching strategy to reduce the data waiting time by overlapping data acquisition and data processing. It also provides the client application with its own user‐level cache, which is advantageous since a larger cache space is available in comparison with the kernel‐level cache. Further, it is easy to maintain data consistency between Spigot nodes. The experimental results indicate that Spigot achieves superior performance in reducing the data waiting time than the pre‐staging and the on‐demand access schemes. Copyright © 2010 John Wiley & Sons, Ltd.     

一种基于移动环境的语义缓存一致性维护技术

在深入研究缓存失效广播技术和语义缓存的基础上，提出了一种新的基于移动环境的语义缓存一致性维护技术——基于语义缓存的异步有状态（BSCAS）技术。BSCAS技术可以支持移动客户的各种断接方式，减少无线通信的开销，让移动客户有更好的自治性。     

基于支持度理论的广义Modus Ponens问题的最优解

为了将模糊推理纳入逻辑的框架并从语构和语义两个方面为模糊推理奠定严格的逻辑基础,通过将模糊推理形式化的方法移植到经典命题逻辑系统中,把FMP(fuzzy modus ponens)问题转化为GMP(generalized modus ponens)问题,并基于公式的真度概念提出了公式之间的支持度,进一步利用支持度的思想引入了GMP问题以及CGMP(collective generalized modus ponens)问题的一种新型最优求解机制.证明了最优解的存在性,同时指出,在经典命题逻辑系统中存在着与模糊逻辑完全相似的推理机制.该方法是一种程度化的方法,这就使得求解过程从算法上实现成为可能,并对知识的程度化推理有所启示.     

集群协作缓存机制研究

计算机集群中的节点使用内存一般不均衡,往往有些节点使用太多内存,而其他节点又有较多的空闲内存.为了改进集群操作系统,将集群节点的内存作全局分布的资源使用,我们首先提出一个内存互操作高速缓存方案:通过使用集群范围内的内存作文件高速缓存,从其他节点的高速缓存中读文件,可以避免很多低速的磁盘访问,改进集群文件系统的总体吞吐量.然后利用我们提出的缓存页面代替策略GCAR来支持这种内存互操作的高速缓存方案.该算法与CAR相比,对缓存中被"经常"使用的页面的管理粒度更细,更适合集群协作缓存的计算环境.实验结果表明,GCAR对本地缓存的命中率比CAR略好,在集群协作缓存下能取得更好的缓存命中率.     

Transfer of problem-solving strategy using Covlan

Psychological evidence suggests that humans use visual knowledge and reasoning in solving complex problems. We present Covlan, a visual knowledge representation language for representing visual knowledge and supporting visual reasoning. We describe Galatea, a computer program that uses Covlan for analogical transfer of problem-solving procedures from known analogs to new problems. We present the use of Galatea to model analogical visual problem solving by four human experimental participants, and describe one of the four cases in detail. The Galatea model of human problem solving suggests that problem-solving procedures can be effectively represented with Covlan.     

Dynamic cache partitioning based on hot page migration

Static cache partitioning can reduce inter-application cache interference and improve the composite performance of a cache-polluted application and a cache-sensitive application when they run on cores that share the last level cache in the same multi-core processor. In a virtualized system, since different applications might run on different virtual machines (VMs) in different time, it is inapplicable to partition the cache statically in advance. This paper proposes a dynamic cache partitioning scheme that makes use of hot page detection and page migration to improve the composite performance of co-hosted virtual machines dynamically according to prior knowledge of cache-sensitive applications. Experimental results show that the overhead of our page migration scheme is low, while in most cases, the composite performance is an improvement over free composition.