Context-Aware Pervasive Service Management in Smart Home Environments
The concept of Smart Home envisions a technology-enriched living space that is capable of anticipating intensions of occupants and providing appropriate services accordingly. Most of the services in such space are context-aware and are realized by an assemblage of heterogeneous components. The objective of this thesis is to design a suite of service management mechanisms that makes such context-aware services flexible, robust, efficient, and consistent.
The flexibility heavily depends on the underlying architecture style. After a thorough review on existing representative pervasive systems, it is concluded that the Message-Oriented Middleware (MOM) is one of the most flexible architecture styles for the Smart Home. Meanwhile, robustness is one of the key challenges for the Smart Home, but few researches have been done to improve the robustness of Message-Oriented Smart Home systems. Hence, this research work attempts to propose a flexible and robust service management framework by formally defining an MOM-based service application model and protocols that facilitate autonomous composition, failure detection and recovery of services. The proposed approach is evaluated by first proving the reliability property and then conducting experiments on recovery rate as well as performance.
Decentralized service management protocols such as UPnP are believed to be more suitable for Smart Homes. These protocols are usually realized by using IP multicast, which, if not carefully designed, often suffer from network flooding problems. This research proposes several efficiency boosting techniques that reduce the replications of unnecessary messages. The analytical predictions agree well with the simulated and experimental results, which show that the traffic can be greatly reduced by the proposed approaches.
Pervasive service composition also attracts increasing interests. When composing services, the criteria for scoring and electing services are usually specified by users, which tend to be vague and subjective. Moreover, the deployment of services in smart homes is usually not as well-planned as that in traditional enterprise environments. Hence, the criteria can be contradictory and the activated components can interfere with one another. This thesis addresses these issues by first proposing the Preference Expression that is capable of specifying both enumerative/numeric as well as mandatory/negotiable preferences. Then, a set of unification rules for unifying conflicting preferences is presented. Finally, this thesis proposes a Fuzzy-based approach to estimate the degree of interference based on available context information. By incorporating the above-mentioned mechanisms, an integrated service composition framework is presented. Experiments that evaluate the effectiveness of the proposed framework are also conducted and reported.
Keywords: Pervasive Computing, UPnP, SSDP, Smart Home, Services Models, Services Discovery Architecture, IP Multicast, Service Systems, Service Composition, Feature Interaction, User Preferences.