Recent advances in animal tracking technology have ushered in a new era in biologging. However, the considerable size of many sophisticated biologging devices restricts their application to larger animals, whereas older techniques often still represent the state-of-theart for studying small vertebrates. In industrial applications, low-power wireless sensor networks (WSNs) fulfill requirements similar to those needed to monitor animal behavior at high resolution and at low tag mass. We developed a wireless biologging network (WBN), which enables simultaneous direct proximity sensing, high-resolution tracking, and long-range remote data download at tag masses of 1 to 2 g. Deployments to study wild bats created social networks and flight trajectories of unprecedented quality. Our developments highlight the vast capabilities of WBNs and their potential to close an important gap in biologging: fully automated tracking and proximity sensing of small animals, even in closed habitats, at high spatial and temporal resolution.

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In this paper, the BATS project is presented, which aims to track the behavior of bats via an ultra-low power wireless sensor network. An overview about the whole project and its parts like sensor node design, tracking grid and software infrastructure is given and the evaluation of the project is shown. The BATS project includes a lightweight sensor node that is attached to bats and combines multiple features. Communication among sensor nodes allows tracking of bat encounters. Flight trajectories of individual tagged bats can be recorded at high spatial and temporal resolution by a ground node grid. To increase the communication range, the BATS project implemented a long-range telemetry system to still receive sensor data outside the standard ground node network. The whole system is designed with the common goal of ultra-low energy consumption while still maintaining optimal measurement results. To this end, the system is designed in a flexible way and is able to adapt its functionality according to the current situation. In this way, it uses the energy available on the sensor node as efficient as possible.

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In this article, we propose an FPGA-based SQL query processing approach exploiting the capabilities of partial dynamic reconfiguration of modern FPGAs. After the analysis of an incoming query, a query-specific hardware processing unit is generated on the fly and loaded on the FPGA for immediate query execution. For each query, a specialized hardware accelerator pipeline is composed and configured on the FPGA from a set of presynthesized hardware modules. These partially reconfigurable hardware modules are gathered in a library covering all major SQL operations like restrictions and aggregations, as well as more complex operations such as joins and sorts. Moreover, this holistic query processing approach in hardware supports different data processing strategies including row- as column-wise data processing in order to optimize data communication and processing. This article gives an overview of the proposed query processing methodology and the corresponding library of modules. Additionally, a performance analysis is introduced that is able to estimate the processing time of a query for different processing strategies and different communication and processing architecture configurations. With the help of this performance analysis, architectural bottlenecks may be exposed and future optimized architectures, besides the two prototypes presented here, may be determined.

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