4781028
Merging R-Trees: Efficient Strategies for Local Bulk Insertion
A lot of recent work has focussed on bulk loading of data into multidimensional index structures in order to efficiently construct such structures for large datasets. In this paper, we address this problem with particular focus on R-trees—which are an important class of index structures used widely in commercial database systems. We propose a new technique, which as opposed to the current technique of inserting data one by one, bulk inserts entire new datasets into an active R-tree. This technique, called STLT (for small-tree-large-tree), considers the new dataset as an R-tree itself (small tree), identifies and prepares a suitable location in the original R-tree (large tree) for insertion, and lastly performs the insert of the small tree into the large tree. Besides an analytical cost model of STLT, extensive experimental studies both on synthetic and real GIS data sets are also reported. These experiments not only compare STLT against the conventional technique, but also evaluate the suitability and limitations of STLT under different conditions, such as varying buffer sizes, ratio between existing and new data sizes, and skewness of new data with respect to the whole spatial region. We find that STLT does much better (in average, about 65%) than the existing technique for skewed datasets as well for large sizes of both the large tree and the small tree in terms of insertion time, while keeping comparable query tree quality. STLT consistently outperforms the alternate technique in all other circumstances in terms of bulk insertion time, especially, even up to 2,000% for the cases when the area of new data sets covers up to 4% of the global region covered by the existing index tree; however, at the cost of a deteriorating resulting tree quality.
4784687
SERF: ODMG-based generic re-structuring facility
The age of information management and with it the advent of increasingly sophisticated technologies have kindled a need in the database community and others to re-structure existing systems and move forward to make use of these new technologies. Legacy application systems are being transformed to newer state-of-the-art systems, information sources are being mapped from one data model to another, a diversity of data sources are being transformed to load, cleanse and consolidate data into modern data-warehouses [CR99].
Re-structuring is thus a critical task for a variety of applications. For this reason, most object-oriented database systems (OODB) today support some form of re-structuring support [Tec94, Obj93, BKKK87]. This existing support of current OODBs [BKKK87, Tec94, Obj93] is limited to a pre-defined taxonomy of simple fixed-semantic schema evolution operations. However, such simple changes, typically to individual types only, are not sufficient for many advanced applications [Bré96]. More radical changes, such as combining two types of redefining the relationship between two types, are either very difficult or even impossible to achieve with current commercial database technology [Tec94, Obj93]. In fact, most OODBs would typically require the user to write ad-hoc programs to accomplish such transformations. Research that has begun to look into the issue of complex changes [Bré96, Ler96] is still limited by providing a fixed set of some selected (even if now more complex) operations.
To address these limitations of the current restructuring technology, we have proposed the SERF framework which aims at providing a rich environment for doing complex user-defined transformations flexibly, easily and correctly [CJR98b]. The goal of our work is to increase the usability and utility of the SERF framework and its applicability to re-structuring problems beyond OODB evolution. Towards that end, we provide re-usable transformations via the notion of SERF Templates that can be packaged into libraries, thereby increasing the portability of these transformations. We also now have a first cut at providing an assurance of consistency for the users of this system, a semantic optimizer that provides some performance improvements via enhanced query optimization techniques with emphasis on the re-structuring primitives [CNR99]. In this demo we give an overview of the SERF framework, its current status and the enhancements that are planned for the future. We also present an example of the application of SERF to a domain other than schema evolution, i.e., the web restructuring.
4779943
SERFing the Web: web site management made easy
In the era of electronic publishing, there is a need for a comprehensive Web Site Management System (WSMS) that provides an end-to-end solution ranging from integration of web sites to re-structuring and maintenance of new customized web views. Today, while many research efforts focus on generating diversified web sites, our Re-Web system [CRCK98] is the first to look at easing this process for end-users by providing libraries of pre-defined generic t ransformations for web re-structuring and visual tools for the generation and browsing of such transformations. Re-Web translates web information to an OO schema and data, re-structures and integrates information at the OODB level (SERF [CR99]) and finally generates web pages from the information in the database. The Re-Web system uses JDK1.2, Java Swing, and PSE Pro6.0 as its persistent storage. We use LotusXSL and IBM's XML parser for the web generation module. Re-Web system (Figure 1) has been implemented and tested on WinNT and Solaxis. I t provides tools for generating, restructuring and maintaining web sites.
4773437
XCache: a semantic caching system for XML queries
A wide range of Web applications retrieve desired information from remote XML data sources across the Internet, which is usually costly due to transmission delays for large volumes of data. Therefore we propose to apply the ideas of semantic caching to XML query processing systems [2], in particular the XQuery engine. Semantic caching [3] implies view-based query answering and cache management. While it is well studied in the traditional database context, query containment for XQuery is left unexplored due to its complexity coming with the powerful expressiveness of hierarchy, recursion and result construction. We hence have developed the first solution for XQuery processing using cached views.We exploit the connections between XML and tree automata, and use subtype relations between two regular expression types to tackle the XQuery containment mapping problem. Inspired by XDuce [1], which explores the use of tree-automata-based regular expression types for XML processing, we have designed a containment mapping process to incorporate type inference and subtyping mechanisms provided by XDuce to establish containment mappings between regular-expression-type-based pattern variables of two queries. We have implemented a semantic caching system called XCache (see Figure 1), to realize the proposed containment and rewriting techniques for XQuery.The main modules of XCache include: (1) Query Decomposer. An input query is is decomposed into source-specific subqueries explicitly represented by matching patterns and return structures. (2) Query Pattern Register. By registering a few queries into semantic regions, we warm up XCache at its initialization phase. (3) Query Containment Mapper. The XDuce subtyper is incorporated into the containment mapper for establishing query containment mappings between variables of a new query and each cached query. (4) Query Rewriter. We implement the classical bucket algorithm and further apply heuristics to decide on an "optimal" rewriting plan if several valid ones exist. (5) Replacement Manager. We free space for new regions by both complete and partial replacement. (6) Region Coalescer. We apply a coalescing strategy to control the region granularity over time.
4775385
A fine-grained replacement strategy for XML query cache
Caching popular queries and reusing results of previously computed queries is one important query optimization technique, especially in modern distributed environments such as the WWW. Based on the recent proliferation of XML data and the emergence of the XQuery language, we are thus developing a query- based caching system for XQuery queries, called ACE-XQ. ACE-XQ applies innovative query containment and rewriting strategies to answer incoming user queries based on the cached XQueries, whenever possible, instead of accessing remote XML data sources.To manage the space of the cache, a straightforward application of traditional replacement strategies would correspond to removing a complete cached query and its derived XML document as a whole when space needs to be freed. This coarse granularity however does not match well with the typical access pattern of web searches where new queries often partially overlap with cached queries.In this paper, we propose a novel replacement strategy appropriate for such query-based XML caching systems. In particular, we collect user access statistics at the granularity of the XML path structure instead of the complete XML query regions. We then apply a more fine-grained replacement strategy that purges XML fragments off a cached region instead of the whole XML document and accordingly adjusts the query descriptor. This may better capture the user access patterns since more frequently used XML document fragments are likely to remain in the cache while other less beneficial parts are purged. This approach has been implemented in our ACE-XQ System. Preliminary experiment results illustrate the performance improvement achievable by our fine-grained replacement strategy over the one which replaces a whole XML view at a time when the cache size is relatively large.
4792658
Active Page Generation via Customizing XML for Data Beans in E-Commerce Applications
In this paper, we analyze enabling technologies for typical e-business applications in terms of their multi-tier system architecture and their Model-Control-View (MCV) programming model. Based on observed limitations of the JSP (Java Server Page) technique commonly adopted for dynamic page generation (the view logic), we instead propose an alternative solution approach, namely, a generic schema mapping strategy to generate XML documents and DTDs from enterprise data beans. First, we describe in detail the XML generation process for the content composition logic. We also outline the XSL processing for the transformation logic. The separation of these two logics results in a generic solution to the bean viewing problem. In particular, it improves the bean reusability via its XML representative compared to the rigid strategy of hard-coding logics into JSP. Our proposed XML mapping solution represents a potentially valuable addition to future versions of the enterprise data beans specification. The trade-off between performance and flexibility of these alternative solutions is discussed. Lastly, we survey the state-of-art research results and emerging stardards related to this XML model mapping approach.
1252625
Supporting self-adaptation in streaming data mining applications
There are many application classes where the users are flexible with respect to the output quality. At the same time, there are other constraints, such as the need for real-time or interactive response, which are more crucial. This paper presents and evaluates a runtime algorithm for supporting adaptive execution for such applications. The particular domain we target is distributed data mining on streaming data. This work has been done in the context of a middleware system called GATES (grid-based adaptive execution on streams) that we have been developing. The self-adaptation algorithm we present and evaluate in this paper has the following characteristics. First, it carefully evaluates the long-term load at each processing stage. It considers different possibilities for the load at a processing stage and its next stages, and decides if the value of an adaptation parameter needs to be modified, and if so, in which direction. To find the ideal new value of an adaptation parameter, it performs a binary search on the specified range of the parameter. To evaluate the self-adaptation algorithm in our middleware, we have implemented two streaming data mining applications. The main observations from our experiments are as follows. First, our algorithm is able to quickly converge to stable values of the adaptation parameter, for different data arrival rates, and independent of the specified initial value. Second, in a dynamic environment, the algorithm is able to adapt the processing rapidly. Finally, in both static and dynamic environments, the algorithm clearly outperforms the algorithm described in our earlier work and an obvious alternative, which is based on linear-updates.
46218447
Parallelizing Progressive Computation for Skyline Queries in Multi-disk Environment
Given a set of d-dimensional points, skyline query returns the points that are not dominated by any other point on all dimensions. In this paper, we study an interesting scenario of skyline retrieval, where multi-dimensional points are distributed among multiple disks. Efficient algorithms for parallelizing progressive skyline computation are developed, using the parallel R-trees. The core of our scheme is to visit more entries from some disks simultaneously and enable effective pruning strategies with dominance checking to prune away the non-qualifying entries. Extensive experiments with synthetic data confirm that our proposed algorithms are both efficient and scalable.
18273444
A system of 3D hair style synthesis based on the wisp model
Hair plays an important role in the image of the human face. However, it is still difficult and time consuming to synthesize realistic 3D CG hair images. In this paper, we present an integrated system for 3D computer graphics (CG) hair image synthesis based on a trigonal prism wisp model. By applying the trigonal prism wisp model, 2D hair distribution maps and other CG techniques to our system, we can successfully and efficiently synthesize realistic CG hair style images. A 3D hair style editing tool (HET) is incorporated into the system to support the creation of 3D hair styles. We have also integrated this system with other research results to construct a system for 3D CG character synthesis.
6229211
Resource allocation in a middleware for streaming data
Increasingly, a number of applications rely on, or can potentially benefit from, analysis and monitoring of <i>data streams.</i> To support processing of streaming data in a grid environment, we have been developing a middleware system called GATES (Grid-based AdapTive Execution on Streams). Our target applications are those involving high volume data streams and requiring distributed processing of data arising from a distributed set of sources.
 This paper addresses the problem of resource allocation in the GATES system. Though resource discovery and resource allocation have been active topics in grid community, the pipelined processing and real-time constraint required by distributed streaming applications pose new challenges. We present a resource allocation algorithm that is based on minimal spanning trees. We evaluate the algorithm experimentally and demonstrate that it results in configurations that are very close to optimal, and significantly better than most other possible configurations.
8727184
Estimating Link Capacity in High Speed Networks
Knowledge of bottleneck capacity of an Internet path is critical for efficient network design, management, and usage. With emerging high speed Internet links, most traditional estimation techniques are limited in providing fast and accurate capacity estimations. In this paper, we propose a new technique, called PBProbe, to estimate high speed links. PBProbe is based on CapProbe; however, instead of solely relying on packet pairs, PBProbe employs a “packet bulk” technique and adapts the bulk length in order to overcome the well known problem with packet pair based approaches, namely the lack of accurate timer resolution. As a result, PBProbe not only preserves the simplicity and speed of CapProbe, but it also correctly estimates link capacities within a much larger range. Using analysis, we evaluate PBProbe with various bulk lengths and network configurations. We then perform emulation and Internet experiments to verify the accuracy and speed of PBProbe on high speed links. The results show that PBProbe is consistently fast and accurate in the great majority of test cases.