A software architecture for electro-mobility services: a milestone for sustainable remote vehicle capabilities

To face the tough competition, changing markets and technologies in automotive industry, automakers have to be highly innovative. In the previous decades, innovations were electronics and IT-driven, which increased exponentially the complexity of vehicle’s internal network. Furthermore, the growing expectations and preferences of customers oblige these manufacturers to adapt their business models and to also propose mobility-based services. One other hand, there is also an increasing pressure from regulators to significantly reduce the environmental footprint in transportation and mobility, down to zero in the foreseeable future. This dissertation investigates an architecture for communication and data exchange within a complex and heterogeneous ecosystem. This communication takes place between various third-party entities on one side, and between these entities and the infrastructure on the other. The proposed solution reduces considerably the complexity of vehicle communication and within the parties involved in the ODX life cycle. In such an heterogeneous environment, a particular attention is paid to the protection of confidential and private data. Confidential data here refers to the OEM’s know-how which is enclosed in vehicle projects. The data delivered by a car during a vehicle communication session might contain private data from customers. Our solution ensures that every entity of this ecosystem has access only to data it has the right to. We designed our solution to be non-technological-coupling so that it can be implemented in any platform to benefit from the best environment suited for each task. We also proposed a data model for vehicle projects, which improves query time during a vehicle diagnostic session. The scalability and the backwards compatibility were also taken into account during the design phase of our solution. We proposed the necessary algorithms and the workflow to perform an efficient vehicle diagnostic with considerably lower latency and substantially better complexity time and space than current solutions. To prove the practicality of our design, we presented a prototypical implementation of our design. Then, we analyzed the results of a series of tests we performed on several vehicle models and projects. We also evaluated the prototype against quality attributes in software engineering

Mobile Tour Assistant for Malaysia

Malaysia's tourism industry has seen a rapid growth rate for the past years, and played a significant role in the development of the country's economy. 2007 is a special year for Malaysian tourism since it is called the "Visit Malaysia" year in celebration of 50 years of Independence. Information Technology has made remarkable contributions to the growth of tourism industry in Malaysia. Its efforts to promote tourism range from websites providing information to systems to service tourists. However, while countries with well-developed tourism industry like France and Hong Kong have developed comprehensive tour assistant packages for tourists, Malaysia is yet to do so. Thus, a comprehensive mobile tour package is needed for Malaysia. The objective of the project is to develop a well-designed tour assistant running on PDAs which makes use of current trends in mobile applications such as the adoption of AI technique in scheduling. Due to time and resource constraints, the project focuses on areas within and around Kuala Lumpur and targets on short-stay and transit tourists. Going through a thorough literature review and following the waterfall methodology, the project has successfully developed a full package of mobile tour assistant including the back end and front end. The project also makes contribution to creatively applying Genetic Algorithm, an AI technique in plan auto-scheduling. The author hopes that the package will be of high commercial value and contribute significantly to boosting Malaysia's tourism

Semantic Similarity of Spatial Scenes

The formalization of similarity in spatial information systems can unleash their functionality and contribute technology not only useful, but also desirable by broad groups of users. As a paradigm for information retrieval, similarity supersedes tedious querying techniques and unveils novel ways for user-system interaction by naturally supporting modalities such as speech and sketching. As a tool within the scope of a broader objective, it can facilitate such diverse tasks as data integration, landmark determination, and prediction making. This potential motivated the development of several similarity models within the geospatial and computer science communities. Despite the merit of these studies, their cognitive plausibility can be limited due to neglect of well-established psychological principles about properties and behaviors of similarity. Moreover, such approaches are typically guided by experience, intuition, and observation, thereby often relying on more narrow perspectives or restrictive assumptions that produce inflexible and incompatible measures. This thesis consolidates such fragmentary efforts and integrates them along with novel formalisms into a scalable, comprehensive, and cognitively-sensitive framework for similarity queries in spatial information systems. Three conceptually different similarity queries at the levels of attributes, objects, and scenes are distinguished. An analysis of the relationship between similarity and change provides a unifying basis for the approach and a theoretical foundation for measures satisfying important similarity properties such as asymmetry and context dependence. The classification of attributes into categories with common structural and cognitive characteristics drives the implementation of a small core of generic functions, able to perform any type of attribute value assessment. Appropriate techniques combine such atomic assessments to compute similarities at the object level and to handle more complex inquiries with multiple constraints. These techniques, along with a solid graph-theoretical methodology adapted to the particularities of the geospatial domain, provide the foundation for reasoning about scene similarity queries. Provisions are made so that all methods comply with major psychological findings about people’s perceptions of similarity. An experimental evaluation supplies the main result of this thesis, which separates psychological findings with a major impact on the results from those that can be safely incorporated into the framework through computationally simpler alternatives

Graph Processing in Main-Memory Column Stores

Evermore, novel and traditional business applications leverage the advantages of a graph data model, such as the offered schema flexibility and an explicit representation of relationships between entities. As a consequence, companies are confronted with the challenge of storing, manipulating, and querying terabytes of graph data for enterprise-critical applications. Although these business applications operate on graph-structured data, they still require direct access to the relational data and typically rely on an RDBMS to keep a single source of truth and access. Existing solutions performing graph operations on business-critical data either use a combination of SQL and application logic or employ a graph data management system. For the first approach, relying solely on SQL results in poor execution performance caused by the functional mismatch between typical graph operations and the relational algebra. To the worse, graph algorithms expose a tremendous variety in structure and functionality caused by their often domain-specific implementations and therefore can be hardly integrated into a database management system other than with custom coding. Since the majority of these enterprise-critical applications exclusively run on relational DBMSs, employing a specialized system for storing and processing graph data is typically not sensible. Besides the maintenance overhead for keeping the systems in sync, combining graph and relational operations is hard to realize as it requires data transfer across system boundaries. A basic ingredient of graph queries and algorithms are traversal operations and are a fundamental component of any database management system that aims at storing, manipulating, and querying graph data. Well-established graph traversal algorithms are standalone implementations relying on optimized data structures. The integration of graph traversals as an operator into a database management system requires a tight integration into the existing database environment and a development of new components, such as a graph topology-aware optimizer and accompanying graph statistics, graph-specific secondary index structures to speedup traversals, and an accompanying graph query language. In this thesis, we introduce and describe GRAPHITE, a hybrid graph-relational data management system. GRAPHITE is a performance-oriented graph data management system as part of an RDBMS allowing to seamlessly combine processing of graph data with relational data in the same system. We propose a columnar storage representation for graph data to leverage the already existing and mature data management and query processing infrastructure of relational database management systems. At the core of GRAPHITE we propose an execution engine solely based on set operations and graph traversals. Our design is driven by the observation that different graph topologies expose different algorithmic requirements to the design of a graph traversal operator. We derive two graph traversal implementations targeting the most common graph topologies and demonstrate how graph-specific statistics can be leveraged to select the optimal physical traversal operator. To accelerate graph traversals, we devise a set of graph-specific, updateable secondary index structures to improve the performance of vertex neighborhood expansion. Finally, we introduce a domain-specific language with an intuitive programming model to extend graph traversals with custom application logic at runtime. We use the LLVM compiler framework to generate efficient code that tightly integrates the user-specified application logic with our highly optimized built-in graph traversal operators. Our experimental evaluation shows that GRAPHITE can outperform native graph management systems by several orders of magnitude while providing all the features of an RDBMS, such as transaction support, backup and recovery, security and user management, effectively providing a promising alternative to specialized graph management systems that lack many of these features and require expensive data replication and maintenance processes

Keyword Search in Relational Databases: Architecture, Approaches and Considerations

Questo lavoro di tesi presenta le diverse soluzioni proposte in letteratura per applicare il paradigma keyword search alle basi di dati relazionali, e vuole delineare una architettura generale per definire e sviluppare questi sistemi. A tal proposito, le soluzioni presentate dalla comunità scientifica sono state analizzate focalizzandosi sui singoli componenti della pipeline di ricerca. Infine, si sono analizzati i processi di valutazione sperimentale di questi sistem

Mobile Tour Assistant for Malaysia

Malaysia's tourism industry has seen a rapid growth rate for the past years, and played a significant role in the development of the country's economy. 2007 is a special year for Malaysian tourism since it is called the "Visit Malaysia" year in celebration of 50 years of Independence. Information Technology has made remarkable contributions to the growth of tourism industry in Malaysia. Its efforts to promote tourism range from websites providing information to systems to service tourists. However, while countries with well-developed tourism industry like France and Hong Kong have developed comprehensive tour assistant packages for tourists, Malaysia is yet to do so. Thus, a comprehensive mobile tour package is needed for Malaysia. The objective of the project is to develop a well-designed tour assistant running on PDAs which makes use of current trends in mobile applications such as the adoption of AI technique in scheduling. Due to time and resource constraints, the project focuses on areas within and around Kuala Lumpur and targets on short-stay and transit tourists. Going through a thorough literature review and following the waterfall methodology, the project has successfully developed a full package of mobile tour assistant including the back end and front end. The project also makes contribution to creatively applying Genetic Algorithm, an AI technique in plan auto-scheduling. The author hopes that the package will be of high commercial value and contribute significantly to boosting Malaysia's tourism

Mobile Tour Assistant

Malaysia's tourism industry has seen a rapid growth rate for the past years, and played a significant role in the development of the country's economy. 2007 is a special year for Malaysian tourism since it is named the "Visit Malaysia" year in celebration of 50 years of Independence. Information Technology has made remarkable contributions to the growth of tourism industry in Malaysia. Its efforts to promote tourism range from websites providing information to systems to service tourists. However, while countries with well-developed tourism industry like France and Hong Kong have developed comprehensive tour assistant packages for tourists, Malaysia is yet to do so. Thus, a comprehensive mobile tour package is needed for Malaysia. The objective of the project is to make an enhancement to the development of a well-designed tour assistant running on PDAs which makes use ofcurrent trends in mobile applications such as the adoption ofAI technique in scheduling. This time around the enhancement will be based on the recommendation from the previous project into consideration and still due to time and resource constraints, the project focuses on areas within and around Kuala Lumpur and targets on short-stay and transit tourists butwill expand as much as possible. Going through a thorough literature review and following the waterfall methodology, the project has successfully developed a comprehensive mobile tour assistant package including the back end and front end module. The project makes creative application of Genetic Algorithm, an AI technique in auto-scheduling. The author hopes that the package will be of high commercial value and contribute significantly to boosting Malaysian tourism