Advances in Computer Science – ASIAN 2005. Data Management on the Web

Data integrity is an assurance that data has not been modified in an unknown or unauthorized manner. The goal of this paper is to allow a user to leverage a small amount of trusted client-side computation to achieve guarantees of integrity when interacting with a vulnerable or untrusted database server. To achieve this goal we describe a novel relational hash tree, designed for efficient database processing, and evaluate the performance penalty for integrity guarantees. We show that strong cryptographic guarantees of integrity can be provided in a relational database with modest overhead.

Ontologies have recently become popular in the context of the

Semantic Web

as an appropriate tool for developing a common reference terminology and language in specific application domains. However, the design and specification of an ontology still does not follow a generally accepted methodology, but is considered to be a task based on perception and intuition. This paper tries to remedy this situation by proposing a novel methodology for ontology engineering that is based on the phase model of traditional database design. Accordingly, the design process of an ontology consists of (1) requirements analysis, (2) conceptual design, (3) logical design, and (4) physical design. Detailed design guidelines are given which include continuous evaluation at the end of each phase. The exposition also provides a running example to ease the understanding of the core activities in each stage.

In smart space applications, we usually adopt semantic Web technologies which possess pervasive context-aware ability to process many onerous tasks, e.g., knowledge sharing, context reasoning and interoperability. In order to achieve above purpose, it is necessary to exploit a Shared Ontologies for Pervasive Computing (SO4PC). These ontologies are expressed with standard Ontology Web Language (OWL) and include modular component vocabularies to represent intelligent agents which are associated with beliefs, desires, intentions, time, space, events, user profiles, actions, policies for security and private protection. We discuss how SO4PC can be extended and used to support the applications of Smart Meeting Rooms (SMR) which is a broker-centric agent architecture.

One of the main challenges in building enterprise applications has been to balance between built-in functionality and domain/scenario-specific customization. The lack of formal ways to extract, distill and standardize the embedded domain knowledge has been a barrier to effective and efficient customization. Ontology may provide, as many would hope, the much needed methodology and standard to achieve the objective of building flexible enterprise solutions. This article examines the uses, issues and challenges of using ontology in enterprise applications. We believe that we are seriously lacking in modeling methodology, domain user tools, and lifecycle management methodology for the creation and maintenance of ontology on a large deployable scale. We present the issues based on an ongoing project to build a product ontology for a public procurement system. Through real life scenarios, we are hoping to convey important research directions to better enable ontology.

Schema matching is the task of finding semantic correspondences between elements of two schemas, which plays a key role in many database applications. In this paper, we treat the schema matching problem as a combinatorial problem. First, we propose an internal schema model, i.e., the multi-labeled graph, and transform schemas into multi-labeled graphs. Secondly, we discuss a generic graph similarity measure, and propose an optimization function based on multi-labeled graph similarity. Then, we cast schema matching problem into a multi-labeled graph matching problem, which is a classic combinational problem. Finally, we implement a greedy algorithm to find the feasible matching results.

A dynamic hybrid DVE architecture is presented in this paper. It’s an extension of client-server architecture. It combines the advantages of client-server architecture and peer-to-peer architecture. By utilizing users’ hardware resources system can support more users. Compaired with the traditional multi-server architecture it holds lower system cost. Theory analysis and simulation results prove its correctness and validity. The flaws of this architecture are also checked and the settlement is discussed.

Replication on geographically distributed, unreliable, P2P interconnecting nodes can offer high data availability and low network latency for replica access. The challenge is how to take good control of the number of replicas and their distribution over well-chosen nodes to get a good replica access performance. We observe that, there exists such a

logical node cluster overlay

over any P2P data-store’s underlying network topology that the replica transmission delay of

inter-cluster

is much greater than that of

intra-cluster

because of geographical distance or bandwidth sharing between nodes in different

clusters

. Based on

nodes-clustering

, we propose a decentralized algorithm

ACB-R

to direct the data replication, which can adapt dynamically to the changing replica access patterns or network topologies. The experiment shows that

ACB-R

can benefit much of the access requests at the price of negligible

intra-cluster

replica transmission and consequently achieves a good average replica access performance.

This paper addresses the efficient top-

k

queries in pure peer-to-peer (P2P) networks. Top-

k

receives much attention in the search engine and gains great success. However, processing top-

k

query in pure P2P network is very challenging due to unique characteristics of P2P environments, for example, skewed collection statistics, and higher communication costs. Inspired by the success of ranking algorithms in Web search engine, we propose a decentralized algorithm to answer top-

k

queries in pure peer-to-peer networks which makes use of local rankings, rank merging, and minimizes both answer set size and network traffic among peers.

As a decentralized technology, P2P architecture arises as a new model for distributed computing and transaction in the last few years, consequently there is a need for a scheme to incorporate payment services to enable electronic payment via P2P systems. In this paper, a new optimistic fair scheme is proposed for multi-party chained P2P transaction, which can ensure that every middleman and digital content owner can obtain the payments due to them. The disputes that might occur are analyzed and handling solution is proposed. The trusted third party need not be involved unless disputes have occurred. The optimistic payment scheme is fair, efficient, practical and suitable for multi-party chained P2P transaction.

This paper presents a practical approach to automatically tuning the parameters of the Apache Web server. In particular, two significant parameters,

KeepAliveTimeout

and

MaxClients

, are dealt with. The notable features of our approach are twofold. First, it is easy to deploy because no modifications to Apache or the underlying operating system are required. Second, our approach is based on the detailed analysis on how each parameter affects the server’s behavior. Experimental results demonstrate that our prototype works well on different workloads; it can discover almost optimal values and quickly adapt to workload changes.

A dramatic increase in the development of technology-based teaching and learning has been witnessed in the past decade. Many universities and corporations started rethinking the design and implementation of the learning systems. Due to the network infrastructure limitations in the traditional systems, it is difficult to provide an efficient and effective approach for delivering personalized course materials to individual student anytime anywhere. To take advantage from the emergence of the Internet, it provides an inexpensive and flexible infrastructure that can greatly enhance the communication among e-Learning system and students. In this paper, we introduce a SMIL-based approach to manage text, graphics, audio, and video for presenting the personalized media-based lesson on the Web. The facilities and capabilities of Web-based architecture, user profiles, XML, and SMIL are incorporated and utilized in a prototype system in our discussion.

We present a method for the multiple two-dimensional pattern matching problem and its application in image database systems. In this problem, we are given a set

S

= {

T

1

,

T

2

, ⋯,

T

N

} of two-dimensional matrices and another two-dimensional matrix

P

, called the pattern, and we want to find all occurrences of the pattern

P

in the set

S

. The main idea behind our method is to represent two-dimensional matrices with one-dimensional strings (called

fingerprint strings

or simply

fingerprints

) thus reducing the two-dimensional matrix matching problem into a one-dimensional string matching problem. We use a data structure, called

the generalized suffix array

, as our index structure to organize the fingerprints of the set

S

. The construction of the index (including converting the matrices in the set

S

into fingerprint strings) takes

O

(

M

log

n

) time and the index occupies

O

(

M

) space ,where

M

denotes the total number of elements in all matrices in

S

and

n

the width of the widest matrix in

S

. Once the index is available, a query for the occurrences of an

m

×

m

pattern in the set

S

can be answered in

O

(

m

2

+ log

M

) time. The reduction of the two-dimensional matrix problem into a one-dimensional string problem, however, can introduce errors, called

false matches

. A false match occurs if the algorithm claims a “match” between the pattern

P

and some submatrix of some matrix in the set

S

while they are actually not equal. But as will be seen, the probability that a false match can occur is negligible. For instance, suppose our patterns are 512 × 512 images. Then the probability that a “match” that is claimed by our algorithm is a false one is less than 2.39 × 10

− 7

.

We systematically propose a dual-phase algorithm, DualRank, to mine the optimal profit in retailing market. DualRank algorithm has two major phases which are called mining general profit phase and optimizing profit phase respectively. In the first phase, the novel sub-algorithm, ItemRank, integrates the random distribution of items into profit mining to improve the performance of item order. In the other phase, two novel optimizing sub-algorithms are proposed to ameliorating results generated in the first phase. According to the cross-selling effect and the self-profit of items, DualRank algorithm could solve the problem of item order objectively and mechanically. We conduct detailed experiments to evaluate DualRank algorithm and experiment result confirms that the new method has an excellent ability for profit mining and the performance meets the condition which requires better quality and efficiency.

The structure queries of XQuery result in structural joins of various relationships. While several efficient algorithms have been proposed in evaluating ancestor–descendant and parent–child relationships, few efforts are put on the study on sibling relationship. In this paper, we study the structural joins of preceding-sibling–following-sibling relationship. To accelerate structural joins of parent–child and preceding-sibling–following-sibling relationships, optimizing techniques are employed to filter out and minimize unnecessary reads of elements using parent’s structural information. Then, two efficient structural join algorithms in evaluating sibling relationship are proposed, in which nodes that do not participate in the join can be judged beforehand and then skipped using B+-tree index. Besides, each element list joined is scanned sequentially once at most. Furthermore, output of join results is sorted in document order. Our experimental results not only demonstrate the effectiveness of our optimizing techniques for sibling axes, but also validate the efficiency of our algorithms. To the best of our knowledge, this is the first effort that addresses this problem.

Answering structural queries of XML with index is an important approach of efficient XML query processing. Among existing structural indexes for XML data, F&B index is the smallest index that can answer all branching queries. However, an F&B index for less regular XML data often contains a large number of index nodes, and hence a large amount of main memory. If the F&B index cannot be accommodated in the available memory, its performance will degrade significantly. This issue has practically limited wider application of the F&B index.

In this paper, we propose a disk organization method for the F&B index which shift part of the leave nodes in the F&B index to the disk and organize them judiciously on the disk. Our method is based on the observation that the majority of the nodes in a F&B index is often the leaf nodes, yet their access frequencies are not high.

We select some leaves to output to disk. With the support of reasonable storage structure in main memory and in disk, we design efficient query processing method). We further optimize the design of the F&B index based on the query workload . Experimental results verified the effectiveness of our proposed approach.

This paper presents a wireless streaming method for XML data which supports energy-efficient processing of queries over the stream in mobile clients. We propose new stream organizations for XML data which have different kinds of addresses to related data in the stream. We describe event-driven stream generation algorithms for the proposed stream structures and provide search algorithms for simple XML path queries which leverage the access mechanisms incorporated in the stream. Experimental results show that our approach can effectively improve the tuning time performance of user queries in a wireless broadcasting environment.

The load shedding problem is vital to a Data Stream Management System (DSMS). This paper presents the design, implementation, and evaluation of a load shedding method under the guide of the feedback control theory, in order to solve practical problems in medical environment. Thus, the using of operator selectivity, which has been proven not stable enough, is avoided. This paper focuses on the restriction of memory resource, this prevents the overflow of both CUP and memory resource. Our method can well support ad-hoc queries, while it is not so in a DSMS using current load shedding method because of the instability of operator selectivity. Our method also ensures a higher query precision when the system is over loaded and is easy to be implemented. The analytical and experimental results show that our method can be applied to medical data stream systems efficiently.

Active DDoS Defense System (ADDS) compensates the deficiencies of isolated defenses made by routers, firewalls or kernel defense programs, and ADDS implements technique of net traffics analysis to control routers for optimizing net traffics distribution. The use of neural network made ADDS the capacity of automatic learning, and ADDS filters DDoS attack traffics automatically according the intensity of attacks in each router; the use of accelerated arithmetic of iteration made ADDS the capacity of quick response.

The spatial object fusion problem occurred in geographic information system is also met in spatial data warehouses, and it plays an important role in the spatial data preprocessing. A novel, equity-based and cell-based spatial object fusion method in spatial data warehouses, which only uses locations of objects and few computes distance among objects, is proposed and its efficiency and effectiveness are measured in terms of

Recall

and

Precision

in this paper. Especially, this method is very suitable for the cases, whose targets can be abstracted into point objects, such as the study about representative plants, animals and landscapes living in special environment. Our work extends the research about this field.

Currently, it is difficult to ensure the found services are optimal in web services discovery. Thus, we suggest that the applicant’s requirements be represented with Service Template (ST) in forms of constraint by adding ample semantic description to web services, and then ST is matched with Service Advertisements (SA) which have been published and saved in enhanced UDDI library, so we can get a set of candidate services, at last, we can find a optimal service from this set. This method can greatly improve the precision and efficiency of web services process, and focus more on how to select optimal service rather than to find a suitable one merely.

A formal framework for SMP is important because it facilitates the building of algorithm model and the evaluation of algorithms. First, we propose a formal definition of schema matching that is named multivalent matching, i.e., an individual of source schema can be associated with a set of individuals of target schema. Second, we develop the algebraic framework of multivalent matching that is called schema homomorphism and propose the algorithm model of SMP. Then, we discuss the relations between match cardinality and variants of schema homomorphism.

This paper presents a peer-to-peer based execution model to improve the availability and reliability of Geospatial Web Services (GWS) composition. A service community concept and a QoS model of GWS are proposed to discover the best quality GWS engines in the peer-to-peer network. The engines coordinate other participants in charge of initiating, controlling, monitoring the associated GWS execution, and adopt an alternative approach for failure recovery. The paper also presents the implementation of a peer-to-peer GWS composition system prototype based on JXTA platform.

Service discovery is a key step during

Peer-to-Peer

(P2P) converging with Web Service. In this paper, a semantic-P2P based approach is presented for web service discovery. To enable the semantic web service, service profile is used to describe web service and as the service data source. The service-expertise based model is proposed for service node selection.

In a secure system and for Web services specifically, security measure must be provided by implementers and system’s owner to support maximum level of trust relations by incorporating security product and technologies at all levels. In this paper we discuss some security issues concerning designing, implementing and deploying Web Services.

In this paper, aiming at the semantics description of Web services, a novel approach to the probabilistic graphical modeling of Web services is proposed, and the services Bayesian network is constructed based on the application of the least fixpoint and conditional mutual information. From the deduction and statistics of historical invocations, the inherent dependencies among elementary services are described, and measured qualitatively and quantitatively. Preliminary experiments and analysis show that our approach is effective and feasible.

A new QoS evaluation model for composite Web Services selection is proposed in this paper, which not only takes account of basic QoS properties but also considers relationships between services. This paper proposes a novel mechanism to map a service selection problem into a multistage decision-making problem to utilize global optimization algorithm to solve it.

Data Warehousing and OLAP technologies enable enterprises to achieve Business Intelligence (BI). Since the Web is the largest independent information repository, systematically integrating suitable Web data into a data warehouse will benefit the enterprise. This paper introduces a Web data warehousing system in the MOLAP environment. A transformation approach is proposed to construct a base cube and then aggregates are precomputed over the base cube. To specify the aggregation rules we have developed a SQL style language that uses external functions for retrieving array data, computing aggregates, populating aggregated cubes.

Mining correlation between multi-streams is a significant task. The main contributions of this paper included: (1) Proposes the equivalence model and equivalence theorems to computing correlation coefficient. (2) Designs anti-noise algorithm with sliding windows to compute correlation measure. (3) Gives extensive experiments on real data and shows that new algorithm works very well on the streams with noise in the environment of short size windows.

In this paper, we firstly formulate the concept of “ordering of sets” to represent the relationships between classes of variables. And then a parallel algorithm with little inter-processors communication is proposed based on “ordering of sets”. In our algorithm, the search space is partitioned in an effective way and be distributed to multi-processors to be searched in parallel. The results of experiments show that, compared with traditional greedy DAG search algorithm, our algorithm is more effective, especially for large domains.

In the paper, a new kind of clustering algorithm called GCARD is proposed. Besides the merits of Density-Based clustering analysis and its efficiency, GCARD can capture the shape and extent of clusters by core grid units, and then analyze data based on the references of core grid units. We present a method of RGUBR to improve the accuracy of grid clustering method, so it can be used to discover information in very large databases.

Although query expansion (QE) has been extensively studied to provide more specific and accurate information for user query, little has been explored to study the importance of combined solution which includes extract terms, select terms correlation, and weight terms correl- ation for QE. The experimental results, based on two real Chinese query logs with 8-14 millions queries, show that the precision varies from 10% to 90% of the top 5 expansion terms.

This paper studies the problem of schema conversion from relational schemas to XML DTDs. As functional dependencies play an important role in the schema conversion process, the concept of functional dependency for XML DTDs is proposed and used to preserve the semantics implied by functional dependencies and keys of relational schemas. A conversion method is proposed to convert relational schemas to XML DTDs in the presence of functional dependencies, keys and foreign keys. The methods presented here can preserve the semantics implied by functional dependencies, keys and foreign keys of relational schemas and can convert multiple relational tables to XML DTDs at the same time.

More and more information is distributed in XML format. Information stored in XML documents should be protected by access control policy. An extended MAC model for XML is presented. The subject and object are discussed at first. The labeled XML document model, which includes three rules and one algorithm, is presented allowing for definition and enforcement of access restrictions directly on the structure and content of XML documents. The extended MAC model for XML documents is described in detail by discussing four operations on XML documents. The architecture and some mechanisms used to implement the model are discussed at last.

Since data streams are continuous, unbounded and real-time, continuous queries over data streams are generally based on windows. Windows placed on data streams are maintained by operators themselves for a query in most DSMSs. However, some operators can’t maintain the windows properly, and a lot of redundancy and inconsistency may be incurred because the tuples are heavily copied and operators interfere with each other. In this paper, we thoroughly discuss the query processing mechanism based on windows and analyze the window semantics in a query sentence, then propose a query processing approach

MullayerQuery

that abstract windows into two types, stream window and operator windows. A strategy and some algorithms are given to keep the consistency among windows in a query. The experiments show

MullayerQuery

can’t only maintain the query semantics, but also implement to share data in multiple queries as well as decrease the usage of memory.

MullayerQuery

has been carried out in a prototype system-

RealStream

that is a DSMS for real-time embedded applications.

Detecting changes in data streams is very important for many applications. This paper presents a hybrid method for detecting data stream changes in intensive care unit. In the method, we first use query processing to detect all the potential changes supporting semantics in big granularity, and then perform similarity matching, which has some features such as normalized subsequences and weighted distance. Our approach makes change detection with a better trade-off between sensitivity and specificity. Experiments on ICU data streams demonstrate its effectiveness.

In this paper, we introduce a three-level schema model for querying the web data which have been used in a specific-domain web data engine—SESQ, which can be customized on different domain by defining the different domain ontology.

In this paper, the Logistics Resource Grid (LRG) for complex logistics applications is constructed. Furthermore, a Resource Integration Framework (RIF) of LRG is developed with Globus Toolkit and OGSA-DAI. LRG and RIF provides a logistics resource integration and optimization environment for Third party logistics companies.

This paper proposes a general consistency management methodology within ontology-driven WIS development. The contributions of this paper are follows: 1) introduces the concept structures for representing model ontologies, mappings ontology and their instances. These ontologies and their instances greatly enhance the representation and reasoning capabilities of mapping and also simplify the manipulation 2) Defines and implements a series of general operators to manipulate mapping and model ontologies. 3) Formalizes the consistency management problem and gives an algorithm basing on general operators. 4) Implements a prototype and integrates it with WISE.