Improving database performance with a mixed fragmentation design

The performance of database operations can be enhanced with an efficient storage structure design using attribute partitioning and/or tuple clustering. Previous research deals mostly with attribute partitioning. We address here the combined problem of attribute partitioning and tuple clustering. We propose a novel approach for this mixed fragmentation problem by applying a genetic algorithm iteratively to attribute partitioning and tuple clustering sub-problems. We compared our results to attribute-only partitioning and random search solution, resulting in a database access cost reduction of upto 70% and 67% respectively. We analyzed the effect of varying genetic parameters on the optimal solution through experimentation.     

SecSpaces: a Data-driven Coordination Model for Environments Open to Untrusted Agent

In this paper we initiate an investigation about security problems which occur when exploiting a Linda-like data driven coordination model in an open environment. In this scenario, there is no guarantee that all the agents accessing the shared tuple space are trusted. Starting from the analysis of the few proposals already available in the literature, we present a novel coordination model which provides mechanisms to manage tuple access control. The first mechanism supports logical partitions of the shared repository: in this way we can restrict the access to tuples inside a partition, simply by limiting the access to the partition itself. The second mechanism consists of adding to the tuples some extra information which exploit asymmetric cryptography in order, e.g., to authenticate the producer of a tuple or to identify its reader/consumer. Finally, we support the possibility to define access control policies based on the kind of operations an agent performs on a tuple, thus discriminating between (destructive) input and (non-destructive) read operations.     

Improving performance by creating a native join-index for OLAP

The performance of online analytical processing (OLAP) is critical for meeting the increasing requirements of massive volume analytical applications. Typical techniques, such as in-memory processing, column-storage, and join indexes focus on high performance storage media, efficient storage models, and reduced query processing. While they effectively perform OLAP applications, there is a vital limitation: mainmemory database based OLAP (MMOLAP) cannot provide high performance for a large size data set. In this paper, we propose a novel memory dimension table model, in which the primary keys of the dimension table can be directly mapped to dimensional tuple addresses. To achieve higher performance of dimensional tuple access, we optimize our storage model for dimension tables based on OLAP query workload features. We present directly dimensional tuple accessing (DDTA) based join (DDTAJOIN), a technique to optimize query processing on the memory dimension table by direct dimensional tuple access. We also contribute by proposing an optimization of the predicate tree to shorten predicate operation length by pruning useless predicate processing. Our experimental results show that the DDTA-JOIN algorithm is superior to both simulated row-store main memory query processing and the open-source column-store main memory database MonetDB, thanks to the reduced join cost and simple yet efficient query processing.     

大规模分布式系统中的多属性查询处理

大规模分布式系统中的复杂查询处理是将对等计算技术运用于关键应用中的重要问题,是学术界与工业界所共同关注的研究问题.文中介绍了一种高效、可伸缩的通用的基于类Chord协议的多属性查询处理技术GChord.它既支持匹配查询也支持范围查询.和现有其它技术相比,对于任何数据元组,GChord只需要对其编码和索引一次,且能将查询处理的代价限制在一个很小的范围内.因此,它能在索引维护代价和查询效率之间达到平衡.GChord还提供优化技术以进一步提升性能.实验证实了GChord具有较高的查询处理效率以及较低的索引维护代价.     

An incremental clustering scheme for data de-duplication

We propose an incremental technique for discovering duplicates in large databases of textual sequences, i.e., syntactically different tuples, that refer to the same real-world entity. The problem is approached from a clustering perspective: given a set of tuples, the objective is to partition them into groups of duplicate tuples. Each newly arrived tuple is assigned to an appropriate cluster via nearest-neighbor classification. This is achieved by means of a suitable hash-based index, that maps any tuple to a set of indexing keys and assigns tuples with high syntactic similarity to the same buckets. Hence, the neighbors of a query tuple can be efficiently identified by simply retrieving those tuples that appear in the same buckets associated to the query tuple itself, without completely scanning the original database. Two alternative schemes for computing indexing keys are discussed and compared. An extensive experimental evaluation on both synthetic and real data shows the effectiveness of our approach.     

一种数据仓库联机维护算法

数据仓库通常以离散的方式进行刷新,这样就不能向用户提供连接的查询服务。文章提出了一种适合数据仓库联机维护的算法－ＳＴＮＬ算法,它消除了２ＶＮＬ,ＭＶＮＬ等联机维护算法需要对元组暂时锁定的缺点,并且更容易实现。     

The design and implementation of a scheme for large ordered indices

Consider a very large ordered collection of indices for an index organization of a dynamically changing random access file. In this paper, we propose a technique for compressing keys from the collection of indices into the minimal set, and hence reducing tremendously the storage space requirement. A set of criteria is given for considering whether the application of this compression technique on keys can meet the minimal space requirement. We also propose the storage structure design for these compressed indices with a view to tackling the key redundancy problem, supporting a general algorithm for retrieving the keys and minimizing costs for updating and maintenance of indices. Finally, we give a comparison between the use of ON KEY interruption implemented in PL/1 and the use of the key compression technique and the hierarchical tree structure as our alternative in dealing with indexed sequential files.     

Inverted index maintenance strategy for flashSSDs: Revitalization of in-place index update strategy

An inverted index is a core data structure of Information Retrieval systems, especially in search engines. Since the search environments have become more dynamic, many on-line index maintenance strategies have been proposed. Previous strategies were designed for HDDs. Consequently, in order to avoid expensive random access cost, Merge-based strategies have been preferred to In-place index update strategies on HDDs. However, flashSSDs have become solid alternatives to HDDs. FlashSSDs currently are adopted in a wide range of areas due to their superior features such as the short access latency, energy efficiency, and high bandwidth. In this article, we first reexamined potentials of In-place index update strategies on flashSSDs. Thanks to the insignificant access latency of flashSSDs, we discovered that In-place index update strategies outperform Merge-based strategies, since In-place index update strategies generate much less amount of I/O than Merge-based strategies despite inducing frequent random accesses. Based on this discovery, we suggest a new inverted index maintenance strategy based on an In-place index update strategy for flashSSDs, called Multipath Flash In-place Strategy (MFIS). To enhance the index maintenance performance, MFIS stores the posting list of each term non-contiguously and exploits the internal parallelism of flashSSDs. Thus, MFIS not only induces the minimum amount of I/O but also utilizes the maximum bandwidth of flashSSDs. Furthermore, MFIS is designed to show high query processing performance by utilizing the internal parallelism of flashSSDs even though the posting list of each term is stored non-contiguously. In our experiments, the index maintenance performance of MFIS was considerably better than other previous maintenance strategies. The index maintenance performance was up to 14.93, 4.04, 5.12, and 2.33 times higher than Merge-based strategies such as Immediate Merge, Geometric Partitioning, Hybrid, and SSD-aware Hybrid, respectively. The query processing performance of MFIS was up to 1.62 times higher than non-contiguous In-place. In addition, MFIS showed almost the best query processing performance as Merge-based strategies did. In conclusion, MFIS is the best on-line inverted index maintenance strategy on flashSSDs in terms of both index maintenance and query processing performance.     

Mobile Agent Coordination for Distributed Network Management

Mobile agents are a promising technology to face the problems raised by the increasing complexity and size of today's networks. In particular, in the area of network management, mobile agents can lead to a fully distributed paradigm to overcome the limits of traditional centralized approaches. A basic requirement for the management of a complex network is the definition of high-level and flexible models to coordinate the accesses to the resources—data and services—provided by the network nodes. On this basis, this paper describes the MARS coordination architecture for mobile agents. MARS is based on the definition of programmable tuple spaces associated with the network nodes: mobile agents can access the local resources and services via the tuple space, thus adopting a standard and high-level interface. The network administrator—via mobile agents—can dynamically program the behavior of the tuple space in reaction to the agents' access to the tuple space, thus leading to a flexible network model. Several examples show the effectiveness of the MARS approach in supporting network management activities.     

Branch-and-bound processing of ranked queries

Despite the importance of ranked queries in numerous applications involving multi-criteria decision making, they are not efficiently supported by traditional database systems. In this paper, we propose a simple yet powerful technique for processing such queries based on multi-dimensional access methods and branch-and-bound search. The advantages of the proposed methodology are: (i) it is space efficient, requiring only a single index on the given relation (storing each tuple at most once), (ii) it achieves significant (i.e., orders of magnitude) performance gains with respect to the current state-of-the-art, (iii) it can efficiently handle data updates, and (iv) it is applicable to other important variations of ranked search (including the support for non-monotone preference functions), at no extra space overhead. We confirm the superiority of the proposed methods with a detailed experimental study.     

WCL: A co-ordination language for geographically distributed agents

In this paper a tuple space based co-ordination language, and a run-time system which supports it, is described. The co-ordination language is called WCL, and it is designed to support agent co-ordination over the Internet between agents which are geographically distributed. WCL uses tuple spaces as used in Linda. WCL provides a richer set of primitives than traditional tuple space based systems, and provides asynchronous and synchronous tuple space access, bulk tuple primitives, and streaming primitives which, as a whole, provide a complete framework more suited to co-ordination over the Internet compared with the Linda primitives. The primitives emphasise efficiency and location transparency (of data and agents) and this is exploited in the current run-time system used to support WCL. The run-time system described in this paper is distributed and uses location transparency and dynamic analysis of tuple space usage to migrate tuple spaces around the distributed system. Some initial experimental results are given which demonstrate the performance gains of using the tuple space migration. The paper motivates the inclusion of many of the primitives, and demonstrates how a well designed set of primitives provides performance and efficiency. The JavaSpace primitives are used as an example of how the choice of primitives can detrimentally affect the efficiency of the language, and exclude required co-ordination constructs.     

An architecture for tuple‐based coordination of multi‐agent systems

Multi‐agent system development calls for powerful and expressive coordination models and languages, as well as for an effective coordination technology. A good deal of the current research effort focuses on tuple‐based coordination, exploiting its well‐known advantages, such as agent uncoupling and associative access to information, and addressing its limitations in terms of flexibility and control capabilities. In particular, the behaviour of a Linda‐like tuple space is fixed once and for all by the coordination model, and cannot be tailored to the specific application needs. Tuple centres are tuple spaces whose behaviour can be programmed by defining transactional reactions to the basic communication events, allowing coordination laws to be explicitly defined and embedded into the coordination medium. This paper presents the architecture of a run‐time system for tuple‐based coordination, where tuple centres work as an extensible kernel, around which multi‐agent systems can be designed and deployed. After sketching the implementation, the paper shows the advantages that can be achieved from both the design and the performance viewpoints. Copyright © 1999 John Wiley & Sons, Ltd.     

Strategies and protocols for highly parallel Linda servers

The tuple space abstraction is a powerful and general coordination model for parallel and distributed programming. However, this model is based on the abstraction of a global space, difficult to implement in distributed memory parallel systems with high-performance and scalability. The paper discusses the possible distribution strategies to implement a tuple space server and proposes a new replication policy suitable for massively parallel systems. The proposed strategy achieves scalability by organising the system in a hierarchical way and by integrating coherence protocols of limited overhead. Moreover, the chosen organisation encourages the presence of multiple tuple spaces each with a constrained scope. The paper describes and analyses a transputer-based implementation: the hierarchical organisation of the tuple space makes the access time proportional to the locality of the references and bounded by the logarithm of the system size. © 1998 John Wiley & Sons, Ltd.     

基于U-P2P元组空间知识协作模式的中越跨语言查询扩展

针对中国与东盟国家在知识共享过程中的语言障碍问题, 详细阐述跨语言查询扩展元组空间的逻辑结构, 提出U-P2P网络模式下元组空间知识协作的分布式中、越跨语言查询扩展模型。在此基础上, 增加查询扩展代理peer的动作语言规则的定义和元组元操作指令集, 依据强化学习算法提出一种基于加权矩阵的自适应路由选择/查询机制。在Gnutella环境下的实验表明, 相对于传统的集中式查询而言, 该模型对中越两种语言之间的快速翻译和扩展查询具有较好的准确率和召回率, 在不同知识领域的运用中具有通用性和可扩充性。     

Minimal-change integrity maintenance using tuple deletions

We address the problem of minimal-change integrity maintenance in the context of integrity constraints in relational databases. We assume that integrity-restoration actions are limited to tuple deletions. We focus on two basic computational issues: repair checking (is a database instance a repair of a given database?) and consistent query answers [in: ACM Symposium on Principles of Database Systems (PODS), 1999, 68] (is a tuple an answer to a given query in every repair of a given database?). We study the computational complexity of both problems, delineating the boundary between the tractable and the intractable cases. We consider denial constraints, general functional and inclusion dependencies, as well as key and foreign key constraints. Our results shed light on the computational feasibility of minimal-change integrity maintenance. The tractable cases should lead to practical implementations. The intractability results highlight the inherent limitations of any integrity enforcement mechanism, e.g., triggers or referential constraint actions, as a way of performing minimal-change integrity maintenance.     

Data Privacy in Tuple Space Based Mobile Agent Systems

More recently, distributed variants of tuple spaces have been proposed to exploit the Linda model for programming distributed applications over wide area networks, possibly exploiting code mobility. However, the flexibility of the shared tuple space model opens possible security holes; it basically provides no access protection to the shared data. In this paper we investigate some possible scenarios where mobile agents can benefit from our cryptographic tuple space based framework, CryptoKlava, and sketch how to possibly implement such agents in order to keep the privacy of items collected by the mobile agent during its itinerary. The functionalities of the framework are general enough to be applied to other Java frameworks using multiple distributed tuples spaces possibly dealing with code mobility.     

Secure Sharing of Tuple Spaces in Ad Hoc Settings

Security is emerging as a growing concern throughout the distributed computing community. Typical solutions entail specialized infrastructure support for authentication, encryption and access control. Mobile applications executing over ad hoc wireless networks present designers with a rather distinct set of security requirements. A totally open setting and limited resources call for lightweight and highly decentralized security solutions. In this paper we propose an approach that relies on extending an existing coordination middleware for mobility (Lime). The need to continue to offer a very simple model of coordination that assures rapid software development led to limiting extensions solely to password protected tuple spaces and per tuple access control. Password distribution and security are relegated to the application realm. Host level security is ensured by the middleware design and relies on standard support provided by the Java system. Secure interactions among agents across hosts are accomplished by careful exploitation of the interceptor pattern and the use of standard encryption. The paper explains the design strategy used to add security support in Lime and its implications for the development of mobile applications over ad hoc networks.     

Block-oriented compression techniques for large statisticaldatabases

Disk I/O has long been a performance bottleneck for very large databases. Database compression can be used to reduce disk I/O bandwidth requirements for large data transfers. The authors explore the compression of large statistical databases and propose techniques for organizing the compressed data such that standard database operations such as retrievals, inserts, deletes and modifications are supported. They examine the applicability and performance of three methods. Two of these are adaptions of existing methods, but the third, called tuple differential coding (TDC), is a new method that allows conventional access mechanisms to be used with the compressed data to provide efficient access. They demonstrate how the performance of queries that involve large data transfers can be improved with these database compression techniques     

Partial indexing for nonuniform data distributions in relationalDBMS's

It is well known that the effectiveness of relational database systems is greatly dependent on the efficiency of the data access strategies. For this reason, much work has been devoted to the development of new access techniques, supported by adequate access structures such as the B⁺trees. The effectiveness of the B ⁺tree also depends on the data distribution characteristics; in particular, poor performance results when the data show strong key value distribution unbalancing. The aim of this paper is to present the partial index: a new access structure that is useful in such cases of unbalancing, as an alternative to the B⁺tree unclustered indexes. The access structures are built in the physical design phase, and at execution (or compilation) time, the optimizer chooses the most efficient access path. Thus, integration of the partial indexing technique in the design and in the optimization process are also described     

Star Cube--一种高效的数据立方体实现方法

一个具有n个维的数据立方体有2^n个视图,视图越多,用于维护数据立方体的时间也就越长。通过将维分成划分维和非划分维,数据立方体可以转换成star cube．stal cube由一个综合表和那些仅包含划分维的视图组成。star cube使用前缀共享和元组共享技术不仅减少了所需的存储空间,还大大减少了计算和维护时间。在把一个分片限制在一个I/O单位的条件下,star cube的查询响应时间与数据立方体基本相同。实验结果也表明,star cube是一种在时空两方面均有效的数据立方体实现技术。