Praveen Rao

PRIX: indexing and querying XML using prufer sequences

We propose a new way of indexing XML documents and processing twig patterns in an XML database. Every XML document in the database can be transformed into a sequence of labels by Prufers method that constructs a one-to-one correspondence between trees and sequences. During query processing, a twig pattern is also transformed into its Prufer sequence. By performing subsequence matching on the set of sequences in the database, and performing a series of refinement phases that we have developed, we can find all the occurrences of a twig pattern in the database. Our approach allows holistic processing of a twig pattern without breaking the twig into root-to-leaf paths and processing these paths individually. Furthermore, we show that all correct answers are found without any false dismissals or false alarms. Experimental results demonstrate the performance benefits of our proposed techniques.

Interannual variability and decadal trend of global fractional vegetation cover from 1982 to 2000

Abstract Fractional vegetation cover (FVC) is one of the most important variables in land surface modeling and also provides a continuous field to complement discrete land cover classification. A global 8-km FVC dataset for 1982–2000 is derived using the NOAA–NASA land Pathfinder normalized difference vegetation index data. The confidence in the dataset is provided by the insensitivity of the algorithm to the data resolution (between 1 and 8 km), the good agreement of the results with the field survey data over Germany, the consistency of the results with previous observational studies over the savannas in North Africa and the forests in Bolivia, and the robustness of the algorithm, as demonstrated by the small interannual variability of FVC over areas where anthropogenic land cover change is expected to be small, based on the 30-m Landsat data analysis. Significant interannual variability is found over shrubland, savanna, and grassland; both positive and negative trends exist over different areas of the ...

Program execution based module cohesion measurement

Module cohesion describes the degree to which different actions performed by a module contribute towards a unified function. High module cohesion is a desirable property of a program. The program modifications during successive maintenance interventions can have negative effect on the structure of the program resulting in less cohesive modules. Therefore, metrics that measure module cohesion are important for software restructuring during maintenance. The existing static slice based module cohesion metrics significantly overestimate cohesion due to the limitations of static slicing. In this paper, we present a novel program execution based approach to measure module cohesion of legacy software. We define cohesion metrics based on definition-use pairs in the dynamic slices of the outputs. Our approach significantly improves the accuracy of cohesion measurement. We implemented our technique and measured module cohesion for several programs. Cohesion measurements using our technique were found to be more insightful than static slice based measurements.

Sequencing XML data and query twigs for fast pattern matching

We propose a new way of indexing XML documents and processing twig patterns in an XML database. Every XML document in the database can be transformed into a sequence of labels by prüfers method that constructs a one-to-one correspondence between trees and sequences. During query processing, a twig pattern is also transformed into its Prüfer sequence. By performing subsequence matching on the set of sequences in the database and performing a series of refinement phases that we have developed, we can find all the occurrences of a twig pattern in the database. Our approach allows holistic processing of a twig pattern without breaking the twig into root-to-leaf paths and processing these paths individually. Furthermore, we show in the article that all correct answers are found without any false dismissals or false alarms. Experimental results demonstrate the performance benefits of our proposed techniques.

Locating XML Documents in a Peer-to-Peer Network Using Distributed Hash Tables

One of the key challenges in a peer-to-peer (P2P) network is to efficiently locate relevant data sources across a large number of participating peers. With the increasing popularity of the extensible markup language (XML) as a standard for information interchange on the Internet, XML is commonly used as an underlying data model for P2P applications to deal with the heterogeneity of data and enhance the expressiveness of queries. In this paper, we address the problem of efficiently locating relevant XML documents in a P2P network, where a user poses queries in a language such as XPath. We have developed a new system called psiX that runs on top of an existing distributed hashing framework. Under the psiX system, each XML document is mapped into an algebraic signature that captures the structural summary of the document. An XML query pattern is also mapped into a signature. The querys signature is used to locate relevant document signatures. Our signature scheme supports holistic processing of query patterns without breaking them into multiple path queries and processing them individually. The participating peers in the network collectively maintain a collection of distributed hierarchical indexes for the document signatures. Value indexes are built to handle numeric and textual values in XML documents. These indexes are used to process queries with value predicates. Our experimental study on PlanetLab demonstrates that psiX provides an efficient location service in a P2P network for a wide variety of XML documents.

Value-based predicate filtering of XML documents

In recent years, publish-subscribe systems based on XML filtering have received much attention in ubiquitous computing environments and Internet applications. The main challenge is to process a large number of content against millions of user subscriptions. Several XML filtering systems focus on the efficient processing of structural matching of user subscriptions represented as XPath twig patterns. However, existing techniques provide limited or no support for twig patterns that contain various operators in the value-based predicates. In this paper, we present the pFiST system that filters XML documents by transforming twig patterns into sequences based on Prufers method. This sequencing idea for XML filtering was first demonstrated by FiST [J. Kwon, P. Rao, B. Moon, S. Lee, FiST: scalable XML document filtering by sequencing twig patterns, in: Proceedings of the 31st VLDB Conference, Trondheim, Norway, 2005, pp. 217-228]. The focus of pFiST is to support value-based predicates in twig patterns in addition to matching their structure. The pFiST system supports equality and non-equality operators, and in addition can handle logical operators such as AND and OR in the value-based predicates. Extensive experimental results show that pFiST provides good performance over data sets with different characteristics.

An Internet-Scale Service for Publishing and Locating XML Documents

In recent years, there has been a growing interest for peer-to-peer (P2P) based computing and applications. One of the most important challenges in P2P environments is to quickly locate relevant data across many participating peers. In this demonstration, we present psiX, which is an Internet-scale service for publishing and locating XML documents. This service runs on several PlanetLab nodes geographically spread across the globe. The psiX system adopts a suite of new techniques for XML indexing and pattern matching in a P2P network, namely, (a) representing XML documents and XPath queries compactly via algebraic signatures, (b) searching signatures of documents and value summaries indexed using distributed hierarchical indexesbuilt over a Distributed Hash Table (DHT), and (c) gracefully adapting to failures while running on the Internet, where failures are a norm rather than an exception.

A Data Parallel Algorithm for XML DOM Parsing

The extensible markup language XML has become the de facto standard for information representation and interchange on the Internet. XML parsing is a core operation performed on an XML document for it to be accessed and manipulated. This operation is known to cause performance bottlenecks in applications and systems that process large volumes of XML data. We believe that parallelism is a natural way to boost performance. Leveraging multicore processors can offer a cost-effective solution, because future multicore processors will support hundreds of cores, and will offer a high degree of parallelism in hardware. We propose a data parallel algorithm called ParDOM for XML DOM parsing, that builds an in-memory tree structure for an XML document. ParDOM has two phases. In the first phase, an XML document is partitioned into chunks and parsed in parallel. In the second phase, partial DOM node tree structures created during the first phase, are linked together (in parallel) to build a complete DOM node tree. ParDOM offers fine-grained parallelism by adopting a flexible chunking scheme --- each chunk can contain an arbitrary number of start and end XML tags that are not necessarily matched. ParDOM can be conveniently implemented using a data parallel programming model that supports map and sort operations. Through empirical evaluation, we show that ParDOM yields better scalability than PXP [23] --- a recently proposed parallel DOM parsing algorithm --- on commodity multicore processors. Furthermore, ParDOM can process a wide-variety of XML datasets with complex structures which PXP fails to parse.

A tool for fast indexing and querying of graphs

We present a tool called GiS for indexing and querying a large database of labeled, undirected graphs. Such graphs can model chemical compounds, represent contact maps constructed from 3D structure of proteins, and so forth. GiS supports exact subgraph matching and approximate graph matching queries. It adopts a suite of new techniques and algorithms for (a) fast construction of disk-based indexes with small index sizes, and (b) efficient query processing with high precision of matching. During the demo, the user can index real graph datasets using a recommendation facility in GiS, pose exact subgraph matching and approximate graph matching queries, and view matching graphs using the Jmol browser.

Fast XML document filtering by sequencing twig patterns

XML-enabled publish-subscribe (pub-sub) systems have emerged as an increasingly important tool for e-commerce and Internet applications. In a typical pub-sub system, subscribed users specify their interests in a profile expressed in the XPath language. Each new data content is then matched against the user profiles so that the content is delivered only to the interested subscribers. As the number of subscribed users and their profiles can grow very large, the scalability of the service is critical to the success of pub-sub systems. In this article, we propose a novel scalable filtering system called iFiST that transforms user profiles of a twig pattern expressed in XPath into sequences using the Prüfers method. Consequently, instead of breaking a twig pattern into multiple linear paths and matching them separately, FiST performs holistic matching of twig patterns with each incoming document in a bottom-up fashion. FiST organizes the sequences into a dynamic hash-based index for efficient filtering, and exploits the commonality among user profiles to enable shared processing during the filtering phase. We demonstrate that the holistic matching approach reduces filtering cost and memory consumption, thereby improving the scalability of FiST.