J. Wenny Rahayu

Mobile cloud computing

Despite increasing usage of mobile computing, exploiting its full potential is difficult due to its inherent problems such as resource scarcity, frequent disconnections, and mobility. Mobile cloud computing can address these problems by executing mobile applications on resource providers external to the mobile device. In this paper, we provide an extensive survey of mobile cloud computing research, while highlighting the specific concerns in mobile cloud computing. We present a taxonomy based on the key issues in this area, and discuss the different approaches taken to tackle these issues. We conclude the paper with a critical analysis of challenges that have not yet been fully met, and highlight directions for future work. Highlights? Problems in mobile computing can be solved when combined with cloud computing. ? Three types of mobile clouds are; offloading to a remote server, to a local cloudlet, and sharing work in a mobile p2p network. ? Existing research on mobile cloud computing is presented as a taxonomy of issues. ? We identify issues in operational, end user, and service levels, and in security and context awareness.

Voronoi-Based Continuous

Digital ecosystems are formed by “digital organisms” in complex, dynamic, and interrelated ecosystems and utilize multiple technologies to provide cost-efficient digital services and value-creating activities. A distributed wireless mobile network that serves as the underlying infrastructure to digital ecosystems provides important applications to the digital ecosystems, two of which are mobile navigation and continuous mobile information services. Most information and query services in a mobile environment are continuous mobile query processing or continuous k nearest neighbor (CKNN), which finds the locations where interest points or interest objects change while mobile users are moving. These locations are known as “split nodes.” All of the existing works on CKNN divide the query path into segments, which is a segment of road separated by two intersections, and then, the process to find split nodes is applied to each segment. Since there are many segments (due to many intersections, obviously), processing each segment is naturally inefficient. In this paper, we propose an alternative solution to overcome this problem. We use the Voronoi diagram for CKNN [called Voronoi CKNN (VCKNN)]. Our proposed approach does not need to divide the query path into segments, hence improving the overall query processing performance. Our experiment verified the applicability of the VCKNN approach to solve CKNN queries.

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Developing a data warehouse for XML documents involves two major processes: one of creating it, by processing XML raw documents into a specified data warehouse repository; and the other of querying it, by applying techniques to better answer users’ queries. This paper focuses on the first part; that is identifying a systematic approach for building a data warehouse of XML documents, specifically for transferring data from an underlying XML database into a defined XML data warehouse. The proposed methodology on building XML data warehouses covers processes including data cleaning and integration, summarization, intermediate XML documents, and updating/linking existing documents and creating fact tables. In this paper, we also present a case study on how to put this methodology into practice. We utilise the XQuery technology in all of the above processes.

Nearest Neighbor Search in Mobile Navigation

In this paper, we present a taxonomy of indexing schemes in parallel database systems. Index partitioning is not recognized widely as yet. One of the reasons is that most of index structures are trees, not flat structures like tables, and consequently, index partitioning imposes some degree of complexity compared with common data partitioning for tables. We present three parallel indexing schemes, and discuss their maintenance strategies. We also analyze their storage requirements.

A Methodology for Building XML Data Warehouses

The use of ontologies lies at the very heart of the newly emerging era of Semantic Web. They provide a shared conceptual- ization of some domain that may be communicated between people and application systems. A common problem with web ontologies is that they tend to grow large in scale and complexity as a result of ever increasing information requirements. The resulting ontologies are too large to be used in their entirety by one application. Our previous work, M aterialized Ontology V iew E xtractor (MOVE), has addressed this problem by proposing a distributed architecture for the extraction/optimization of a sub-ontology from a large scale base ontology. The extraction process consists of a number of independent optimization schemes that cover various aspects of the optimization process. In this paper, we extend MOVE with a Semantic Complete- ness Optimization Scheme (SCOS), which addresses the issue of the semantic correctness of the resulting sub-ontology. Moreover, we utilize distributed methods to implement SCOS in a cluster environment. Here, a distributed memory architecture serves two purposes: (a). Facilitates the utilization of a cluster environment typical in business organizations, which is in line with our envisaged application of the proposed system and (b). Enhances the performance of the computationally extensive extraction process when dealing with massively sized realistic ontologies.

A Taxonomy of Indexing Schemes for Parallel Database Systems

Previously, exception rules have been defined as association rules with low support and high confidence. Exception rules are important in data mining, as they form rules that can be categorized as an exception. This is the opposite of general association rules in data mining, which focus on high support and high confidence. In this paper, a new approach to mining exception rules is proposed and evaluated. A relationship between exception and positive/negative association rules is considered, whereby the candidate exception rules are generated based on knowledge of the positive and negative association rules in the database. As a result, the exception rules exist in the form of negative, as well as positive, association. A novel exceptionality measure is proposed to evaluate the candidate exception rules. The candidate exceptions with high exceptionality form the final set of exception rules. Algorithms for mining exception rules are developed and evaluated using an exceptionality measurement, the desired performance of which has been proven.

Semantic Completeness in Sub-ontology Extraction Using Distributed Methods

With the wide availability of mobile devices (smart phones, iPhones, etc.), mobile location-based queries are increasingly in demand. One of the most frequent queries is range search which returns objects of interest within a pre-defined area. Most of the existing methods are based on the road network expansion method - expanding all nodes (intersections and objects) and computing the distance of each node to the query point. Since road networks are extremely complex, node expansion approaches are inefficient. In this paper, we propose a method, Voronoi Range Search (VRS) based on the Voronoi diagram, to process range search queries efficiently and accurately by partitioning the road networks to some special polygons. Then we further propose Voronoi Continuous Range (VCR) to satisfy the requirement for continuous range search queries (moving queries) based on VRS. Our empirical experiments show that VRS and VCR surpass all their rivals for both static and moving queries.

Exception rules in association rule mining.

In a decentralised system like P2P where each individual peers are considerably autonomous, the notion of mutual trust between peers is critical. In addition, when the environment is subject to inherent resource constraints, any efficiency efforts are essentially needed. In light of these two issues, we propose a novel trustworthy-based efficient broadcast scheme in a resource-constrained P2P environment. The trustworthiness is associated with the peer@?s reputation. A peer holds a personalised view of reputation towards other peers in four categories namely SpEed, Correctness, qUality, and Risk-freE (SeCuRE). The value of each category constitutes a fraction of the reliability of individual peer. Another factor that contributes to the reliability of a peer is the peer@?s credibility concerning trustworthiness in providing recommendation about other peers. Our trust management scheme is applied in conjunction with our trust model in order to detect malicious and collaborative-based malicious peers. Knowledge of trustworthiness among peers is used in our proposed broadcast model named trustworthy-based estafet multi-point relays (TEMPR). This model is designed to minimise the communication overhead between peers while considering the trustworthiness of the peers such that only trustworthy peer may relay messages to other peers. With our approach, each peer is able to disseminate messages in the most efficient and reliable manner.

Voronoi-based range and continuous range query processing in mobile databases

The new era of semantic Web has enabled users to extract semantically relevant data from the Web. The backbone of the semantic Web is a shared uniform structure which defines how Web information is split up regardless of the implementation language or the syntax used to represent the data. This structure is known as an ontology. As information on the Web increases significantly in size, Web ontologies also tend to grow bigger, to such an extent that they become too large to be used in their entirety by any single application. This has stimulated our work in the area of sub-ontology extraction where each user may extract optimized sub-ontologies from an existing base ontology. Sub-ontologies are valid independent ontologies, known as materialized ontologies, that are specifically extracted to meet certain needs. Because of the size of the original ontology, the process of repeatedly iterating the millions of nodes and relationships to form an optimized sub-ontology can be very extensive. Therefore we have identified the need for a distributed approach to the extraction process. As ontologies are currently widely used, our proposed approach for distributed ontology extraction will play an important role in improving the efficiency of information retrieval.

Trustworthy-based efficient data broadcast model for P2P interaction in resource-constrained wireless environments

EXtensible Markup Language (XML) has emerged as the dominant standard in describing and exchanging data among heterogeneous data sources. The increasing presence of large volumes of data appearing creates the need to investigate XML Document Warehouses as a means of handling the data. In this paper our focus is twofold. First we utilise Object Oriented (OO) concepts to develop and propose a conceptual design formalism to build meaningful XML Document Warehouses (XDW). This includes: (1) XML (warehouse) repository (xFACT) using OO concepts followed by the transformation of XML Schema constructs and (2) Conceptual Virtual Dimensions (VDims) using Conceptual views (Rajugan, Chang, Dillon, & Feng, 2003, 2004). Secondly we address several important outstanding issues related to our proposed design of an XML Document Warehouse. Specifically we note that the xFACT portion is now a complex structure, involving several entities and relationships as opposed to being a simple FACT table as was the case in relational data warehouses, and the notion of Virtual Dimensions (VDims) has considerably greater complexity.