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We present a method to evaluate path queries based on the novel concept of partial path instances. Our method (1) maximizes performance by means of sequential scans or asynchronous I/O, (2) does not require a special storage format, (3) relies on simple navigational primitives on trees, and (4) can be complemented by existing logical and physical optimizations such as duplicate elimination, duplicate prevention and path rewriting.We use a physical algebra which separates those navigation operations that require I/O from those that do not. All I/O operations necessary for the evaluation of a path are isolated in a single operator, which may employ efficient I/O scheduling strategies such as sequential scans or asynchronous I/O.Performance results for queries from the XMark benchmark show that reordering the navigation operations can increase performance up to a factor of four.

While indoor positioning systems based on 802.11 and fingerprinting work pretty well, it is unknown how to distribute a large amount of fingerprint data to mobile devices. Even worse, many mobile devices are restricted in terms of memory. In this demo proposal, we present two distribution approaches for fingerprints that fill this gap: the Strongest Access Point (SAP) and the Intersection of Access Points (IAP) algorithms. These approaches utilize the 802.11 infrastructure to download only a subset of the complete fingerprint data to a mobile device. The subset covers the area close to the actual position of the mobile device in such a way that position estimates can be computed.For the MDM 2007 demo session, we offer to demonstrate how these distribution approaches for fingerprint data work. The demo will include live indoor positioning of visitors using mobile devices while concurrently displaying the distribution of fingerprint data.

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This paper describes a number of XQuery-related projects. Its goal is to show that XQuery is a useful tool for many different application scenarios. In particular, this paper tries to correct a common myth that XQuery is merely a query language and that SQL is the better query language. Instead, XQuery is a full-fledged programming language for Web applications and services. Furthermore, this paper tries to correct a second myth that XQuery is slow. This paper gives an overview of the state-of-the-art in XQuery implementation and optimization techniques and discusses one particular open-source XQuery processor, Zorba, in more detail. Among others, this paper presents an XQuery Benchmark Service which helps practitioners and XQuery processor vendors to find performance problems in an XQuery processor.

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