Abstract. We present an architecture for a class of systems that perform distributed, collaborative, adaptive sensing (DCAS) of the atmosphere. Since the goal of these DCAS systems is to sense the atmosphere when and where the user needs are greatest, end-users naturally play the central role in determining how system resources (sensor targeting, computation, communication) are deployed. We describe the meteorological command and control components that lie at the heart of our testbed DCAS system, and provide timing measurements of component execution times. We then present a utility-based framework that determines how multiple end-user preferences are combined with policy considerations into utility functions that are used to allocate system resources in a manner that dynamically optimizes overall system performance.We also discuss open challenges in the networking and control of such enduser-driven systems.

Mobile devices dominate the Internet today, however the Internet rooted in its tethered origins continues to provide poor infrastructure support for mobility. Our position is that in order to address this problem, a key challenge that must be addressed is the design of a massively scalable global name service that rapidly resolves identities to network locations under high mobility. Our primary contribution is the design, implementation, and evaluation of Auspice, a nextgeneration global name service that addresses this challenge. A key insight underlying Auspice is a demand-aware replica placement engine that intelligently replicates name records to provide low lookup latency, low update cost, and high availability. We have implemented a prototype of Auspice and compared it against several commercial managed DNS providers as well as state-of-the-art research alternatives, and shown that Auspice significantly outperforms both. We demonstrate proof-of-concept that Auspice can serve as a complete end-to-end mobility solution as well as enable novel context-based communication primitives that generalize nameor address-based communication in today's Internet.

Distributed Collaborative Adaptive Sensing (DCAS) of the atmosphere is a new paradigm for detecting and predicting hazardous weather using a dense network of short-range, low-powered radars to sense the lowest few kilometres of the earth's atmosphere. DCAS systems are collaborative in that the beams from multiple radars are actively coordinated in a sense-andrespond manner to achieve greater sensitivity, precision and resolution than possible with a single radar. DCAS systems are adaptive in that the radars and their associated computing and communications infrastructure are dynamically reconfigured in response to changing weather conditions and end-user needs. This paper describes an end-to-end DCAS architecture and evaluates the performance of the system in an operational testbed with actual weather events and end-user considerations driving the system. Our results demonstrate how the architecture is capable of real-time data processing, optimisation of radar control and sensing of the atmosphere in a manner that maximises end-user utility. . (2010) 'Closed-loop architecture for distributive collaborative adaptive sensing of the atmosphere: meteorological command and control', Int.

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