Flexpop: A popularity-based caching strategy for multimedia applications in information-centric networking

Information-Centric Networking (ICN) is the dominant architecture for the future Internet. In ICN, the content items are stored temporarily in network nodes such as routers. When the memory of routers becomes full and there is no room for a new arriving content, the stored contents are evicted to cope with the limited cache size of the routers. Therefore, it is crucial to develop an effective caching strategy for keeping popular contents for a longer period of time. This study proposes a new caching strategy, named Flexible Popularity-based Caching (FlexPop) for storing popular contents. The FlexPop comprises two mechanisms, i.e., Content Placement Mechanism (CPM), which is responsible for content caching, and Content Eviction Mechanism (CEM) that deals with content eviction when the router cache is full and there is no space for the new incoming content. Both mechanisms are validated using Fuzzy Set Theory, following the Design Research Methodology (DRM) to manifest that the research is rigorous and repeatable under comparable conditions. The performance of FlexPop is evaluated through simulations and the results are compared with those of the Leave Copy Everywhere (LCE), ProbCache, and Most Popular Content (MPC) strategies. The results show that the FlexPop strategy outperforms LCE, ProbCache, and MPC with respect to cache hit rate, redundancy, content retrieval delay, memory utilization, and stretch ratio, which are regarded as extremely important metrics (in various studies) for the evaluation of ICN caching. The outcomes exhibited in this study are noteworthy in terms of making FlexPop acceptable to users as they can verify the performance of ICN before selecting the right caching strategy. Thus FlexPop has potential in the use of ICN for the future Internet such as in deployment of the IoT technology

Investigation of a hierarchical context-aware architecture for rule-based customisation of mobile computing service

The continuous technical progress in mobile device built-in modules and embedded sensing techniques creates opportunities for context-aware mobile applications. The context-aware computing paradigm exploits the relevant context as implicit input to characterise the user and physical environment and provide a computing service customised to the contextual situation. However, heterogeneity in techniques, complexity of contextual situation, and gap between raw sensor data and usable context keep the techniques from truly integration for extensive use. Studies in this area mainly focus on feasibility demonstration of the emerging techniques, and they lack general architecture support and appropriate service customisation strategy. This investigation aims to provide general system architecture and technical approaches to deal with the heterogeneity problem and efficiently utilise the dynamic context towards proactive computing service that is customised to the contextual situation. The main efforts of this investigation are the approaches to gathering, handling, and utilising the dynamic context information in an efficient way and the decision making and optimisation methods for computing service customisation. In brief, the highlights of this thesis cover the following aspects: (1) a hierarchical context-aware computing architecture supporting interoperable distribution and further use of context; (2) an in-depth analysis and classification of context and the corresponding context acquisition methods; (3) context modelling and context data representation for efficient and interoperable use of context; (4) a rule-based service customisation strategy with a rule generation mechanism to supervise the service customisation. In addition, feasibility demonstration of the proposed system and contribution justification of this investigation are conducted through case studies and prototype implementations. One case study uses mobile built-in sensing techniques to improve the usability and efficiency of mobile applications constrained by resource limitation, and the other employs the mobile terminal and embedded sensing techniques to predict users’ expectations for home facility automatic control. Results demonstrate the feasibility of the proposed context handling architecture and service customisation methods. It shows great potential for employing the context of the computing environment for context-aware adaptation in pervasive and mobile applications but also indicates some underlying problems for further study