Product line enabled intelligent mobile middleware

Current mobile middleware is designed according to a 'one-size-fits-all ' paradigm, which lacks the flexibility for customization and adaptation to different situations, and does not support user-centered application scenarios well. In this paper we describe an ongoing intelligent mobile middleware research project called PLIMM that focuses on user-centered application scenarios. PLIMM is designed based on software product line ideas which make it possible for specialized customization and optimization for different purposes and hardware/software platforms. To enable intelligence, the middleware needs access to a range of context models. We model these contexts with OWL, focusing on usercentered concepts. The basic building block of PLIMM is the enhanced BDI agent where OWL context ontology logic reasoning will add indirect beliefs to the belief sets. Our approach also addresses the handling of ontology evolutions resulting from the timely adaptation of ontology to changes and the consistent propagation of these changes to all related artifacts, using Frame based product line configuration techniques

Enhancing intelligence and dependability of a product line enabled pervasive middleware

To provide good support for user-centered application scenarios in pervasive computing environments, pervasive middleware must react to context changes and prepare services accordingly. At the same time, pervasive middleware should provide extended dependability via self-management capabilities, to conduct self-diagnosis of possible malfunctions using the current runtime context, and self-configuration and self-adaptation when there are service mismatches. In this article, we present an approach to combine the power of BDI practical reasoning and OWL/SWRL ontologies theoretical reasoning in order to improve the intelligence of pervasive middleware, supported by a set of Self-Management Pervasive Service (SeMaPS) ontologies featuring dynamic context, complex context, and self-management rules modeling. In this approach, belief sets are enriched with the results of OWL/SWRL theoretical reasoning to derive beliefs that cannot be obtained directly or explicitly. This is demonstrated with agents negotiating sports appointments. To cope with self-management, the corresponding monitoring, configuration, adaptation and diagnosis rules are developed based on OWL and SWRL utilizing SeMaPS ontologies. Evaluations show this combined reasoning approach can perform well, and that Semantic Web-based self-management is promising for pervasive computing environments

Mobile game development: Object-orientation or not

Mobile games are one of the primary entertainment applications at present. Limited by scarce resources, such as memory, CPU, input and output, etc, mobile game development is more difficult than desktop application development, with performance as one of the top critical requirements. As object-oriented technology is the prevalent programming paradigm, most of the current mobile games are developed with object-orientation (OO) technologies. Intuitively OO is not a perfect paradigm for embedded software. Questions remain such as how OO and to what degree OO will affect the performance, executable file size, and how optimization strategies can improve the qualities of mobile game software. These questions are investigated in this paper within the mobile Role-Playing-Game (RPG) domain using five industrial mobile games developed with OO. We analyzed them and found excessive usage of OO features used for the development of mobile device applications (but normal for usual desktop applications). We then apply some optimization strategies along the way of structural programming. The experiment shows that the total jar file size of these five optimized games decreases 71%, the lines of codes decreases 5