Context-awareness is becoming an important foundation of adaptive mobile systems; however, techniques for discovering contextually relevant Web content and Smart Devices (i.e., Smart Resources) remain consigned to small-scale deployments. To address this limitation, this paper introduces Ambient Ocean, a Web search engine for context-aware Smart Resource discovery. Ocean provides scalable mechanisms for supplementing Resources with expressive contextual metadata as a means of facilitating in-situ discovery and composition. Ocean supports queries based on arbitrary contextual data, such as location, biometric details, telemetry data, situational cues, sensor information, etc. Ocean utilizes a combination of crowd-sourcing, context-enhanced query expansion and personalization techniques to continually optimize query results over time. This paper presents Ocean’s conceptual foundations, its reference implementation, and a preliminary evaluation that demonstrates significantly improved Smart Resource discovery results in real-world environments.
Ocean Paper Accepted at the 2014 IEEE International Conference on Internet of Things