XML data update management in XML-enabled database

With the increasing demand for a proper and efficient XML data storage, XML-Enabled Database (XEnDB) has emerged as one of the popular solutions. It claims to combine the pros and limit the cons of the traditional Database Management Systems (DBMS) and Native XML Database (NXD). In this paper, we focus on XML data update management in XEnDB. Our aim is to preserve the conceptual semantic constraints and to avoid inconsistencies in XML data during update operations. In this current era when XML data interchange mostly occurs in a commercial setting, it is highly critical that data exchanged be correct at all times, and hence data integrity in XML data is paramount. To achieve our goal, we firstly classify different constraints in XML documents. Secondly, we transform these constraints into XML Schema with embedded SQL annotations. Thirdly, we propose a generic update methodology that utilizes the proposed schema. We then implement the method in one of the current XEnDB products. Since XEnDB has a Relational Model as the underlying data model, our update method uses the SQL/XML as a standard language. Finally, we also analyze the processing performance.     

Peer-to-peer bichromatic reverse nearest neighbours in mobile ad-hoc networks

The increasing use of mobile communications has raised many issues of decision support and resource allocation. A crucial problem is how to solve queries of Reverse Nearest Neighbour (RNN). An RNN query returns all objects that consider the query object as their nearest neighbour. Existing methods mostly rely on a centralised base station. However, mobile P2P systems offer many benefits, including self-organisation, fault-tolerance and load-balancing. In this study, we propose and evaluate 3 distinct P2P algorithms focusing on bichromatic RNN queries, in which mobile query peers and static objects of interest are of two different categories, based on a time-out mechanism and a boundary polygon around the mobile query peers. The Brute-Force Search Algorithm provides a naive approach to exploit shared information among peers whereas two other Boundary Search Algorithms filter a number of peers involved in query processing. The algorithms are evaluated in the MiXiM simulation framework with both real and synthetic datasets. The results show the practical feasibility of the P2P approach for solving bichromatic RNN queries for mobile networks.     

A pure peer-to-peer approach for kNN query processing in mobile ad hoc networks

Together with advanced positioning and mobile technologies, P2P query processing has attracted a growing interest number of location-aware applications such as answering kNN queries in mobile ad hoc networks. It not only overcomes drawbacks of centralized systems, for example single point of failure and bottleneck issues, but more importantly harnesses power of peers’ collaboration. In this research, we propose a pure mobile P2P query processing scheme which primarily focuses on the search and validation algorithm for kNN queries. The proposed scheme is designed for pure mobile P2P environments with the absence of the base station support. Compared with centralized and hybrid systems, our system can reduce energy consumption more than six times by making use of data sharing from peers in a reasonable mean latency of processing time for networks with high density of moving objects as can be seen in the simulation results.     

Mobile service oriented architectures for NN-queries

The ever-increasing number of mobile device users has also raised the users’ expectation of mobile services accordingly. This phenomenon has given pressures to the mobile service providers to improve their services in order to stay competitive in the market. The service oriented approach is seen to be a promising scheme for mobile services. This paper presents mobile service oriented architectures for Nearest-Neighbor (NN) queries that are classified into five categories, namely (i) intermittent query mobile services, (ii) continuous query mobile services, (iii) context-aware mobile services, (iv) continuous moving object query mobile services, and (v) data broadcast mobile services. These services incorporate query, location and context-aware services, ontological context model, and broadcast. The proposed architectures are concerned with mobile services for clients on the move requesting services based on their current location, which is arguably the most important feature in a wireless environment. Furthermore, we also discuss the Quality-of-Service (QoS) requirement for mobile services in which request latency time is one of the most important parameters to consider. Some analytical models for query latency measurement are presented and the results are compared with the simulation experiments.     

Ontology as a Service (OaaS): a case for sub-ontology merging on the cloud

Cloud computing is a revolution in the information technology industry. It allows computing services provided as utilities. The traditional cloud services include Software as a Service, Platform as a Service, Hardware/Infrastructure as a Service, and Database as a Service. In this paper, we introduce the notion of Ontology as a Service (OaaS), whereby the ontology tailoring process is a service in the cloud. This is particularly relevant as we are moving toward Cloud 2.0—multi-cloud providers to provide an interoperable service to customers. To illustrate OaaS, in this paper we propose sub-ontology extraction and merging, whereby multiple sub-ontologies are extracted from various source ontologies, and then these extracted sub-ontologies are merged to form a complete ontology to be used by the user. We use the Minimum extraction method to facilitate this. A walkthrough case study using the UMLS meta-thesaurus ontology is elaborated, and its performance in the cloud is also discussed.     

ODAM: An optimized distributed association rule mining algorithm

Association rule mining is an active data mining research area. However, most ARM algorithms cater to a centralized environment. In contrast to previous ARM algorithms, we have developed a distributed algorithm, called optimized distributed association mining, for geographically distributed data sets. ODAM generates support counts of candidate itemsets quicker than the other DARM algorithms and reduces the size of average transactions, data sets, and message exchanges.     

Correction to: AnonSURP: an anonymous and secure ultralightweight RFID protocol for deployment in internet of vehicles systems

The Journal of Supercomputing -     

Ontology tailoring in the Semantic Grid

This paper presents a Service Oriented Architecture (SOA) approach to a distributed framework for reusing, extracting and extending large domain ontologies in the Semantic Grid environment. The conceptual level of the framework describes how sub-ontologies are extracted and extended with new features, while the architectural level of the framework describes the components of the framework. These components allow the sub-ontology extraction and extension process to be performed using shared resources in the Semantic Grid environment. A prototype of the framework is built using Web Services and a complexity evaluation measure is presented. The results of several simulations show that the sub-ontology extraction and extension process in the Semantic Grid is a viable solution and can be optimized by using better quality, initial labeling set.     

Voronoi-based reverse nearest neighbor query processing on spatial networks

The use of Voronoi diagram has traditionally been applied to computational geometry and multimedia problems. In this paper, we will show how Voronoi diagram can be applied to spatial query processing, and in particular to Reverse Nearest Neighbor (RNN) queries. Spatial and geographical query processing, in general, and RNN in particular, are becoming more important, as online maps are now widely available. In this paper, using the concept of Voronoi diagram, we classify RNN into four types depending on whether the query point and the interest objects are the generator points of the Voronoi Polygon or not. Our approach is based on manipulating Network Voronoi Diagram properties and applying a progressive incremental network expansion for finding the polygon inner network distances required to solve RNN queries. Our experimentation results show that our approaches have good response times in answering RNN queries.