Increasingly large numbers of situational applications are being created by enterprise business users as a by-product of solving day-to-day problems. In efforts to address the demand for such applications, corporate IT is moving toward Web 2.0 architectures. In particular, the corporate intranet is evolving into a platform of readily accessible data and services where communities of business users can assemble and deploy situational applications. Damia is a web style data integration platform being developed to address the data problem presented by such applications, which often access and combine data from a variety of sources. Damia allows business users to quickly and easily create data mashups that combine data from desktop, web, and traditional IT sources into feeds that can be consumed by AJAX, and other types of web applications. This paper describes the key features and design of Damia's data integration engine, which has been packaged with Mashup Hub, an enterprise feed server currently available for download on IBM alphaWorks. Mashup Hub exposes Damia's data integration capabilities in the form of a service that allows users to create hosted data mashups.

No abstract available.

XML filtering systems aim to provide fast, on-the-fly matching of XML-encoded data to large numbers of query specifications containing constraints on both structure and content. It is now well accepted that approaches using event-based parsing and Finite State Machines (FSMs) can provide the basis for highly scalable structure-oriented XML filtering systems. The XFilter system [Altinel and Franklin 2000] was the first published FSM-based XML filtering approach. XFilter used a separate FSM per path query and a novel indexing mechanism to allow all of the FSMs to be executed simultaneously during the processing of a document. Building on the insights of the XFilter work, we describe a new method, called "YFilter" that combines all of the path queries into a single Nondeterministic Finite Automaton (NFA). YFilter exploits commonality among queries by merging common prefixes of the query paths such that they are processed at most once. The resulting shared processing provides tremendous improvements in structure matching performance but complicates the handling of value-based predicates.In this article, we first describe the XFilter and YFilter approaches and present results of a detailed performance comparison of structure matching for these algorithms as well as a hybrid approach. The results show that the path sharing employed by YFilter can provide order-of-magnitude performance benefits. We then propose two alternative techniques for extending YFilter's shared structure matching with support for value-based predicates, and compare the performance of these two techniques. The results of this latter study demonstrate some key differences between shared XML filtering and traditional database query processing. Finally, we describe how the YFilter approach is extended to handle more complicated queries containing nested path expressions.

Many e-Business applications today are being developed and deployed on multi-tier environments involving browser-based clients, web application servers and backend databases. The dynamic nature of these applications necessitates generating web pages on-demand, making middle-tier database caching an effective approach to achieve high scalability and performance [3]. In the DBCache project, we are incorporating a database cache feature in DB2 UDB by modifying the engine code and leveraging existing federated database functionality. This allows us to take advantage of DB2's sophisticated distributed query processing power for database caching. As a result, the user queries can be executed at either the local database cache or the remote backend server, or more importantly, the query can be partitioned and then distributed to both databases for cost optimum execution.DBCache also includes a cache initialization component that takes a backend database schema and SQL queries in the workload, and generates a middle-tier database schema for the cache. We have implemented an initial prototype of the system that supports table level caching. As DB2's functionality is extended, we will be able to support subtable level caching, XML data caching and caching of execution results of web services.

Workflows are activities involving the coordinated execution of multiple tasks performed by different processing entities, mostly in distributed heterogeneous environments, which are very common in enterprises of even moderate complexity. In current commercial workflow systems, the workflow scheduler is a single centralized component. A distributed workflow enactment service, on the other hand, should contain several schedulers on different nodes of a network, each executing a part of the process instances. Such an architecture would fit naturally into the distributed heterogeneous environments. Further advantages of a distributed enactment service are failure resiliency and increased performance, since a centralized scheduler is a potential bottleneck. In this paper, we present the design and implementation of a distributed workflow enactment service based on the work of M. Singh (1996). By starting with a block-structured workflow specification language, we avoid a very general set of dependencies and their related problems. In this way, it is possible to present a simple algorithm for the distributed scheduling of process instances. Further benefits of the approach are the ease of testing and debugging the system, and the execution efficiency through having a reduced number of messages.

No abstract available.