Large-scale wireless sensor networks (WSN) are increasingly deployed and an open question is how they can support multiple applications. Networks and sensing devices are typically heterogeneous and evolving: topologies change, nodes drop in and out of the network, and devices are reconfigured. The key question we address is how to verify that application requirements are met, individually and collectively, and can continue to be met, in the context of large-scale, evolving network and device configurations. We define a modelling and verification framework based on Bigraphical Reactive Systems (BRS) for modelling, with bigraph patterns and temporal logic properties for specifying application requirements. The bigraph diagrammatic notation provides an intuitive representation of concepts such as hierarchies, communication, events and spatial relationships, which are fundamental to WSNs. We demonstrate modelling and verification through a real-life urban environmental monitoring case-study. A novel contribution is automated online verification using BigraphER and replay of real-life sensed data streams and network events by the Cooja network simulator. Performance results for verification of two application properties running on a WSN with up to 200 nodes indicate our framework is capable of handling WSNs of that scale.

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Masses of sensors are being deployed at the scale of cities to manage parking spaces, transportation infrastructures to monitor traffic, and campuses of buildings to reduce energy consumption. These largescale infrastructures become a reality for citizens via applications that orchestrate sensors to deliver highvalue, innovative services. These applications critically rely on the processing of large amounts of data to analyze situations, inform users, and control devices. This paper proposes a design-driven approach to developing orchestrating applications for masses of sensors that integrates parallel processing of large amounts of data. Specifically, an application design exposes declarations that are used to generate a programming framework based on the MapReduce programming model. We have developed a prototype of our approach, using Apache Hadoop. We applied it to a case study and obtained significant speedups by parallelizing computations over twelve nodes. In doing so, we demonstrate that our design-driven approach allows to abstract over implementation details, while exposing architectural properties used to generate high-performance code for processing large datasets. Furthermore, we show that this high-performance support enables new, personalized services in a smart city. Finally, we discuss

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This paper proposes a design-driven development approach that is dedicated to the domain of orchestration of masses of sensors. The developer declares what an application does using a domainspecific language (DSL). Our compiler processes domain-specific declarations to generate a customized programming framework that guides and supports the programming phase.