面向对象数据库的蔟集技术

文章给出了对象库的几种蔟集技术，并给出了一组选取具体蔟集技术的原则和性能评价的标准。     

Performance analysis of parallel object-oriented query processing algorithms

Advanced application domains such as computer-aided design, computer-aided software engineering, and office automation are characterized by their need to store, retrieve, and manage large quantities of data having complex structures. A number of object-oriented database management systems (OODBMS) are currently available that can effectively capture and process the complex data. The existing implementations of OODBMS outperform relational systems by maintaining and querying cross-references among related objects. However, the existing OODBMS still do not meet the efficiency requirements of advanced applications that require the execution of complex queries involving the retrieval of a large number of data objects and relationships among them. Parallel execution can significantly improve the performance of complex OO queries. In this paper, we analyze the performance of parallel OO query processing algorithms for various benchmark application domains. The application domains are characterized by specific mixes of queries of different semantic complexities. The performance of the application domains has been analyzed for various system and data parameters by running parallel programs on a 32-node transputer based parallel machine developed at the IBM Research Center at Yorktown Heights. The parallel processing algorithms, data routing techniques, and query management and control strategies have been implemented to obtain accurate estimation of controlling and processing overheads. However, generation of large complex databases for the study was impractical. Hence, the data used in the simulation have been parameterized. The parallel OO query processing algorithms analyzed in this study are based on a query graph approach rather than the traditional query tree approach. Using the query graph approach, a query is processed by simultaneously initiating the execution at several object classes, thereby, improving the parallelism. During processing, the algorithms avoid the execution of time-consuming join operations by making use of the object references among the objects. Further, the algorithms do not generate any temporary data, thereby, reducing disk accesses. This is accomplished by marking the selected objects and by employing a two-phase query processing strategy.     

Performance evaluation of an open distributed platform for realistic traffic generation

Network researchers have dedicated a notable part of their efforts to the area of modeling traffic and to the implementation of efficient traffic generators. We feel that there is a strong demand for traffic generators capable to reproduce realistic traffic patterns according to theoretical models and at the same time with high performance. This work presents an open distributed platform for traffic generation that we called distributed internet traffic generator (D-ITG), capable of producing traffic (network, transport and application layer) at packet level and of accurately replicating appropriate stochastic processes for both inter departure time (IDT) and packet size (PS) random variables. We implemented two different versions of our distributed generator. In the first one, a log server is in charge of recording the information transmitted by senders and receivers and these communications are based either on TCP or UDP. In the other one, senders and receivers make use of the MPI library. In this work a complete performance comparison among the centralized version and the two distributed versions of D-ITG is presented.     

Performance bottleneck of subsequence matching in time-series databases: Observation, solution, and performance evaluation

Subsequence matching is an operation that finds subsequences whose changing patterns are similar to a given query sequence from time-series databases. This paper identifies a performance bottleneck in subsequence matching, and then proposes an effective method that substantially improves the performance of entire subsequence matching by resolving the performance bottleneck. First, we analyze the disk access and CPU processing times required during the index searching and post-processing steps of subsequence matching through preliminary experiments. Based on these results, we show that the post-processing step is a main performance bottleneck in subsequence matching. Then, we argue that the optimization of the post-processing step is a crucial issue overlooked in previous approaches. In order to resolve the performance bottleneck, we propose a simple yet highly effective method for expediting the post-processing step. By rearranging the order of candidate subsequences to be compared with a query sequence, our method completely eliminates the redundancies of disk accesses and CPU processing that occur in the post-processing step. Our method is fairly efficient, and does not incur any false dismissal. We quantitatively demonstrate the superiority of our method through extensive experimentation. The results show that our method produces a significantly faster post-processing step; When using a data set of real-world stock sequences, our method was 43.36-96.75 times faster than previous methods, and when using data sets of large numbers of synthetic sequences, our method was 12.48-26.95 times faster than previous methods. Also, the results show that our method reduces the weight of the post-processing step over entire subsequence matching from more than 97% to less than 67%. This implies that our method successfully resolves the performance bottleneck in subsequence matching. As a result, our method provides excellent performance in entire subsequence matching. Compared with previous methods, our method is 16.17-32.64 times faster when using a data set of real-world stock sequences and 8.64-14.29 times faster when using data sets of large numbers of synthetic sequences.     

Performance evaluation of NoSQL big-data applications using multi-formalism models

Starting with the birth of Web 2.0, the quantity of data managed by large-scale web services has grown exponentially, posing new challenges and infrastructure requirements. This has led to new programming paradigms and architectural choices, such as map-reduce and NoSQL databases, which constitute two of the main peculiarities of the specialized massively distributed systems referred to as Big Data architectures. The underlying computer infrastructures usually face complexity requirements, resulting from the need for efficiency and speed in computing over huge evolving data sets. This is achieved by taking advantage from the features of new technologies, such as the automatic scaling and replica provisioning of Cloud environments. Although performances are a key issue for the considered applications, few performance evaluation results are currently available in this field. In this work we focus on investigating how a Big Data application designer can evaluate the performances of applications exploiting the Apache Hive query language for NoSQL databases, built over a Apache Hadoop map-reduce infrastructure.This paper presents a dedicated modeling language and an application, showing first how it is possible to ease the modeling process and second how the semantic gap between modeling logic and the domain can be reduced, by means of vertical multiformalism modeling.     

异步电路的静态数据流图模型及其性能分析

静态数据流图是异步电路的一种抽象模型,具有灵活性高、易于理解的优点.基于静态数据流图的一种形式化的执行语义,提出了一种适合于性能分析的静态数据流图的Petri网模型,并基于该模型提出了一种性能评价方法.该方法具有速度快、灵活性高的优点,特别适合大规模异步电路设计早期的性能分析.该模型比静态数据流图的传统Petri网模型在规模上小一倍,而且避免了引入非标准的read-arc.通过实验,该模型和性能评价方法的有效性得到了充分的验证.     

Performance evaluation of high-speed interconnects using dense communication patterns

We study the performance of high-speed interconnects using a set of communication micro-benchmarks. The goal is to identify certain limiting factors and bottlenecks with these interconnects. Our micro-benchmarks are based on dense communication patterns with different communicating partners and varying degrees of these partners. We tested our micro-benchmarks on five platforms: an IBM system of 68-node 16-way Power3, interconnected by a SP switch2; another IBM system of 264-node 4-way Power PC 604e, interconnected by an SP switch; a Compaq cluster of 128-node 4-way ES40/EV67 processor, interconnected by an Quadrics interconnect; an Intel cluster of 16-node dual-CPU Xeon, interconnected by an Quadrics interconnect; and a cluster of 22-node Sun Ultra Sparc, interconnected by an Ethernet network. Our results show many limitations of these networks including the memory contention within a node as the number of communicating processors increased and the limitations of the network interface for communication between multiple processors of different nodes.     

Performance evaluation of re-entrant manufacturing system with production loss using mean value analysis

This paper proposes an approximation method based on mean value analysis (MVA) technique for estimating the performance measures of re-entrant manufacturing system with production loss. The model is an extension of the one proposed by Park et al. (Comput. Oper. Res. 29 (2002) 1009). A unique feature in the extended model is that random production losses due to machine failures and yields are considered. Considering such losses is critical in performance evaluation, because it may often cause significant errors in the results compared to the real values if the analysis does not explicitly consider them. However, such random losses substantially increase the complexity of the analysis, due to the fact that even through simulation it requires not only extra modeling efforts, but also a number of replications. As a result, it requires bigger efforts and data, and significantly longer computational times. For an analytical approach, such random losses also prohibit exact analysis of the system. Therefore, a methodology for analyzing the system approximately is proposed using the iterative procedures based upon the MVA and some heuristic adjustments. The performance measures of interest are the steady-state average of the cycle time of each job class, the queue length of each buffer, and the throughput of the system. Numerical tests are presented to show the performance of the proposed approach against the simulation results. Also, the comparisons with the earlier test results summarize the insights from the overall research thus far.     

Performance evaluation of a single-stage two-product manufacturing system operating under pull-type control

This paper presents a model to analyze a manufacturing system that is operating under pull-type control. A Markovian polling model with finite queues is devised to represent the manufacturing system and studied under three cyclic service policies: exhaustive, gated, and a type of limited policy. These polling models are solved by two different methods: an exact approach that requires the complete characterization of the system as a Markov chain and a decomposition approach that reduces the size of the Markov chain. A set of numerical experiments show that the decomposition approach is quite accurate in estimating system performance measures.     

A comparative workload-based methodology for performance evaluation of parallel computers

A practical methodology for evaluating and comparing the performance of distributed memory Multiple Instruction Multiple Data (MIMD) systems is presented. The methodology determines machine parameters and program parameters separately, and predicts the performance of a given workload on the machines under consideration. Machine parameters are measured using benchmarks that consist of parallel algorithm structures. The methodology takes a workload-based approach in which a mix of application programs constitutes the workload. Performance of different systems are compared, under the given workload, using the ratio of their speeds. In order to validate the methodology, an example workload has been constructed and the time estimates have been compared with the actual runs, yielding good predicted values. Variations in the workload are analysed in terms of increase in problem sizes and changes in the frequency of particular algorithm groups. Utilization and scalability are used to compare the systems when the number of processors is increased. It has been shown that performance of parallel computers is sensitive to the changes in the workload and therefore any evaluation and comparison must consider a given user workload. Performance improvement that can be obtained by increasing the size of a distributed memory MIMD system depends on the characteristics of the workload as well as the parameters that characterize the communication speed of the parallel system.     

MANET中节点的运动模型和性能分析

移动自组网的节点运动模型描述了节点的运动情况，采用合适的运动模型对于分析各种协议性能具有重要的意义。该文结合移动自组网络中路由协议的相关属性，提出了邻居节点比率、链路生存时间和平均链路保持时间3种评价指标，并通过大量的模拟实验分析和比较了随机行走运动模型、随机停留运动模型、高斯－马尔可夫运动模型和无边界运动模型4种运动模型，这对于考虑不同运动模型下路由协议的设计十分重要。     

Performance evaluation of a multithreaded RTS using a synchronous reactive model

Synchronous reactive modelling provides an optimal framework for the modular decomposition of programs that engage in complex patterns of deterministic interaction, such as many real-time and communication entities. This paper presents an approach which includes performance modelling techniques in the synchronous reactive modelling method supported by ESTEREL. It defines a methodology based on timing and probabilistic quantitative constructs that complete the synchronous reactive models. A monitoring mechanism allows the computation of performance results during the simulation. This methodology is applied to study a multithreaded runtime system for a distributed functional programming language. Performance metrics are computed and validated with experimental results.     

Performance evaluation of Web proxy cache replacement policies

The continued growth of the World-Wide Web and the emergence of new end-user technologies such as cable modems necessitate the use of proxy caches to reduce latency, network traffic and Web server loads. In this paper we analyze the importance of different Web proxy workload characteristics in making good cache replacement decisions. We evaluate workload characteristics such as object size, recency of reference, frequency of reference, and turnover in the active set of objects. Trace-driven simulation is used to evaluate the effectiveness of various replacement policies for Web proxy caches. The extended duration of the trace (117 million requests collected over 5 months) allows long term side effects of replacement policies to be identified and quantified.

Our results indicate that higher cache hit rates are achieved using size-based replacement policies. These policies store a large number of small objects in the cache, thus increasing the probability of an object being in the cache when requested. To achieve higher byte hit rates a few larger files must be retained in the cache. We found frequency-based policies to work best for this metric, as they keep the most popular files, regardless of size, in the cache. With either approach it is important that inactive objects be removed from the cache to prevent performance degradation due to pollution.     

基于建模的NoC性能评价方法研究

NoC的设计空间非常庞大,并且不同方案间存在巨大的性能差异,所以在设计初期对不同的设计方案进行 性能评价极其重要。以基于建模的NoC性能评价方法为主线,重点分析和对比基于仿真模型和基于分析模型的性能 评价方法的研究现状和评价能力,由此归纳出NoC评价模型的准确度评佑方法。最后,在对面临的挑战进行分析的 基础上,提出基于建模的NoC性能评价的发展方向。     

Performance evaluation of TCP connections in ideal and non-ideal network environments

In this paper, we study the performance of TCP in both ideal and non-ideal network environments. For the ideal environments, we develop a simple analytical model for the throughput and transfer time of TCP as a function of the file size and TCP parameters. Our simulation measurements demonstrate that this model can accurately predict the throughput for ideal TCP connections characterized by no packet loss due to congestion or bit errors. If these ideal conditions are not met, the model gives an upper bound for throughput and lower bound for transfer time. For the non-ideal environments, we concentrate on wireless links. While our ideal model provides an easy to use tool to calculate bounds on the performance of all TCP implementations in such environments, we also show through simulation the relative performance of four well-known TCP implementations. We also present simulation results that demonstrate the dominant factors affecting the performance of wireless TCP.     

基于ofbiz框架的银行绩效考核系统的设计与实现

文章根据银行体系结构,借鉴国外绩效管理系统的成功经验,分析国内绩效管理系统的现状和发展方向,阐述了中国建行新疆分行绩效考核系统分析、设计、实现的过程.系统基于MVC 模式,运用了Ofbiz框架技术保障了系统的稳定性、底层组件的可靠性、数据库访问的高效性,同时大幅提高了项目的开发效率.系统采用xml、递归算法、md5算法、ssl协议等技术,重点解决了考核表的可定制性、高并发访问量、考核数据的安全性问题.不仅保障了系统高效安全的运行,同时满足了客户对考核方式可灵活变化的需要.     

Performance evaluation of parallel iterative deepening A on clusters of workstations

In this paper we investigate the performance of distributed heuristic search methods based on a well-known heuristic search algorithm, the iterative deepening A^* (IDA^*). The contribution of this paper includes proposing and assessing a distributed algorithm for IDA^*. The assessment is based on space, time and solution quality that are quantified in terms of several performance parameters such as generated search space and real execution time among others. The experiments are conducted on a cluster computer system consisting of 16 hosts built around a general-purpose network. The objective of this research is to investigate the feasibility of cluster computing as an alternative for hosting applications requiring intensive graph search. The results reveal that cluster computing improves on the performance of IDA^* at a reasonable cost.     

概念建模研究综述

概念建模是指创建概念模型的行为,这些模型用来描述问题,与具体用于解决问题的技术和策略独立无关。在过去数十年中,大量概念建模方法和工具纷纷涌现,许多理论如本体论、语言学和认知学的引入,增强了概念建模的理论基础。基于本体的概念建模研究得到了充分的重视。本文对概念建模的发展、概念建模语言、基于本体的概念建模以及概念模型的质量评估进行系统的阐述。     

Unraveling the capabilities that enable digital transformation: A data-driven methodology and the case of artificial intelligence

Digital transformation (DT) is prevalent in businesses today. However, current studies to guide DT are mostly qualitative, resulting in a strong call for quantitative evidence of exactly what DT is and the capabilities needed to enable it successfully. With the aim of filling the gaps, this paper presents a novel bibliometric framework that unearths clues from scientific articles and patents. The framework incorporates the scientific evolutionary pathways and hierarchical topic tree to quantitatively identify the DT research topics’ evolutionary patterns and hierarchies at play in DT research. Our results include a comprehensive definition of DT from the perspective of bibliometrics and a systematic categorization of the capabilities required to enable DT, distilled from over 10,179 academic papers on DT. To further yield practical insights on technological capabilities, the paper also includes a case study of 9,454 patents focusing on one of the emerging technologies - artificial intelligence (AI). We summarized the outcomes with a four-level AI capabilities model. The paper ends with a discussion on its contributions: presenting a quantitative account of the DT research, introducing a process-based understanding of DT, offering a list of major capabilities enabling DT, and drawing the attention of managers to be aware of capabilities needed when undertaking their DT journey.