Service-oriented architectures (SOAs) promise to provide transparency to resource access by exposing the resources available as services. SOAs have been employed within pervasive computing systems to provide essential support to user tasks by creating services representing the available resources. The mechanism of combining two or more basic services into a possibly complex service is known as service composition. Existing solutions to service composition employ a template-matching approach, where the user needs are expressed as a request template, and through composition, a system would identify services to populate the entities within the request template. However, with the dynamism involved in pervasive environments, the user needs have to be met by exploiting available resources, even when an exact match does not exist. In this paper, we present a novel service composition mechanism for pervasive computing. We employ the service-oriented middleware platform called Pervasive Information Communities Organization (PICO) to model and represent resources as services. The proposed service composition mechanism models services as directed attributed graphs, maintains a repository of service graphs, and dynamically combines multiple basic services into complex services. Further, we present a hierarchical overlay structure created among the devices to exploit the resource unevenness, resulting in the capability of providing essential service-related support to resource-poor devices. Results of extensive simulation studies are presented to illustrate the suitability of the proposed mechanism in meeting the challenges of pervasive computing-user mobility, heterogeneity, and the uncertain nature of involved resources.
This paper presents the design and deployment experience of an air-dropped wireless sensor network for volcano hazard monitoring. The deployment of five stations into the rugged crater of Mount St. Helens only took one hour with a helicopter. The stations communicate with each other through an amplified 802.15.4 radio and establish a self-forming and self-healing multi-hop wireless network. The distance between stations is up to 2 km. Each sensor station collects and delivers real-time continuous seismic, infrasonic, lightning, GPS raw data to a gateway. The main contribution of this paper is the design and evaluation of a robust sensor network to replace data loggers and provide real-time long-term volcano monitoring. The system supports UTCtime synchronized data acquisition with 1ms accuracy, and is online configurable. It has been tested in the lab environment, the outdoor campus and the volcano crater. Despite the heavy rain, snow, and ice as well as gusts exceeding 120 miles per hour, the sensor network has achieved a remarkable packet delivery ratio above 99% with an overall system uptime of about 93.8% over the 1.5 months evaluation period after deployment. Our initial deployment experiences with the system have alleviated the doubts of domain scientists and prove to them that a low-cost sensor network system can support real-time monitoring in extremely harsh environments.
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