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Work Performed in the First Year

In WP1, environmental and platform models and tools and methods for learning model parameters were designed. A number of environmental and platform aspects including temperature, interference, RSSI, and timing where identified. Each aspect was closely examined and a model was formulated which accurately represents their behaviour. The investigation of RSSI was published at ExtremeCom 2013 and won the best paper award. Tools where developed to learn model parameters during the setup phase of a deployment, to allow deployment-specific instantiations of the developed models.

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In WP2, first versions of environmentally-aware protocols have been designed and analyzed. At the network layer, we analyzed the operation of RPL under varying temperature levels and enhanced its performance, RPL is the standard routing protocol for IPv6 in low power and lossy wireless networks. At the data link layer, we analyzed the operation of n-way handshake agreements under interference and proposed methods to improve the resilience of the handshake.

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In WP3, a framework has been designed that allows the specification of dependability requirements. Different requirements can be specified for different phases of application execution. This framework has been mapped to two different language instances, one for applications where the application logic is specified in plain C as used in the Contiki toolchain, and one for applications where the application logic is specified using a macroprogramming languages. The project started to investigate constraint satisfaction and optimization problems for selecting protocol parameters to match these specifications before deployment and dynamically during runtime based on reinforcement learning.

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In WP4, we have identified a set of typical IoT applications that are exposed to challenging environmental conditions and that need to meet given dependability requirements. To this end, we have presented four candidate use cases that are of interest to our industrial partners, namely (i) outdoor parking management, (ii) civil infrastructure monitoring, (iii) condition based maintenance, and (iv) ventilation on demand. Based on a decision matrix encompassing business, technical, and logistics aspects, we have selected the first use case for our integrated experiments, and accordingly progressed with its design.



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