Abstract-Many pervasive computing applications demand expressive situational awareness, which entails an entity learning detailed information about its immediate and surrounding context. Previous work has largely focused on individual entities' context, in this paper we present Grapevine, a framework for efficiently sharing context information in a localized region of a pervasive computing network, using that information to dynamically form groups defined by their shared situations, and assessing the aggregate context of that group. We provide an implementation of Grapevine and benchmark its performance in a live pervasive computing network deployment.

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Summary. Acquiring accurate context information is crucial to mobile and pervasive computing, and sharing context among nodes enables unique applications. As context information and the applications that consume it become increasingly diverse, they will need an efficient means to indicate tailored interest in this context information. This paper proposes a new probabilistic data structure, spatiotemporal Bloom filters (SpTBF) or "spitty bifs," which allow nodes to efficiently store and share their context interests. SpTBF provide both spatiotemporal locality and a fine-grained ability to control how context interests are disseminated. SpTBF are evaluated by modifying the Grapevine context sharing framework to inform its context dissemination capabilities, and the benefits are characterized in a variety of network scenarios.

Modern flight test systems are only now starting to deploy IP-based networks to carry instrumentation data. These newer systems are replacing their traditional fixed serial interconnects and multiplexers. With this evolution comes the need for network management solutions in flight test environments, which includes all aspects of configuring, controlling, and monitoring a multitude of network elements. These elements include the various system processes, including data acquisition, recording, real-time data processing, as well as the underlying networking devices themselves. Southwest Research Institute ® (SwRI ® ) has been involved in the development of a network management system that is part of a network based flight test system being developed for a customer transitioning to network based flight test systems for certifying their next generation commercial airplanes. This paper describes part of that network management approach, concentrating on the key issue of automatic network topology and device discovery.