Reliability is one of the key challenges of pervasive systems. Numerous message-oriented architectures and service discovery protocols have been proposed to support service management in pervasive systems. Nevertheless, few researches have been done to improve the reliability of pervasive systems. This paper attempts to propose a reliable service management framework by formally defining a message-oriented service application model and protocols that facilitate autonomous composition, failure detection, and recovery of services. Proposed approaches are realized by constructing a developer's toolkit that enables rapid-prototyping of services. We evaluate the proposed approach by first proving the reliability property and then conducting experiments on recovery rate and performance. The results show that the recovery rate can be greatly improved by the proposed approach. Furthermore, the services developed by using the proposed approach are capable of integrating heterogeneous software/hardware, and can be deployed in dissimilar sites with little efforts.

Current trends suggest that the smart home systems should be adaptive and robust. Many service-oriented architectures and discovery protocols for the smart home environments have been proposed to support on-line re-composition of home services in reaction to changing environments. Nevertheless, few researches have been done to improve the robustness of smart home systems. This paper attempts to propose a service management protocol that supports fast self-healing and self-organizing of home services by enhancing SSDP/UPnP with two protocol extensions and a lightweight heartbeat mechanism. Experiment results show that for average scale of services (less than 10 service components), the proposed protocol is capable of activating a service and recovering a failed service within 1200 ms and 2000 ms, respectively.

Service Discovery is an interesting challenge in highly dynamic Pervasive Environments such as smart living spaces. In addition to adaptation to varied environments, autonomous failure recovery and activation of services are two fundamental issues of a Service Discovery protocol in order to achieve high service availability. In [1], we have introduced an enhanced version of UPnP's Simple Service Discovery Protocol (SSDP), which aims to fulfill these two fundamental issues. However, our experiences in the previous work show that the failure recovery performance is not desirable due to the multicast mechanism used by SSDP. In this paper, we propose a supporting data structure, Mapped Eviction SND Tree, composed of a set of specialized mapped-trees to speed up the failure recovery process. The system with this structure is aware of existing service nodes and need not to perform the discovery procedure again when failure is detected. Hence, the time for restoring the failed service is minimized. Experiment results show that the proposed approach helps reducing the failure recovery time up to 90 percent in average. Issues concerning maintenance and collaboration between the sets of internal data structures are also discussed in this paper.