An Energy-aware Ad-hoc Routing Strategy for Queriable Wireless Sensor Networks

The data volume handled by wireless sensor networks (WSN) is ever growing due to increasing node counts and node complexity – be it in traditional WSN applications or for Car2X or Internet-of-Things. Queriable WSN are a concept to handle the large data volumes in such networks by abstracting the network as a virtual database table to which users can pose queries. This declarative approach enables networks which can flexibly adapt to changing application requirements. In addition they possess a flat learning curve since users do not need to have a high technological understanding of the sensor node firmware. Upon executing a query it is first propagated through the network and once it has reached the desired nodes, results are collected and send back through the query-posing node (usually the sink). The routing which is used for the data aggregation step plays a major role in the energy efficiency in networks with increasing node and sensor value counts as represented by Car2X networks for instance. In this paper, an ad-hoc routing strategy for queriable WSN is proposed which is both energy-aware and application-specific. It will be shown that this routing can contribute greatly towards decreasing the energy consumption needed for data aggregation and thus helps increasing the network’s lifespan

Towards Cloud-supported Automotive Software Development and Test

The development of automotive software has been an evolving process for the last decades. As a result, the paradigm of software development which is independent of the target hardware platform has been adopted in almost all parts of the automotive industry. Deploying software to a hardware platform is now controlled by an enormous parameter set stored in a mapping configuration. This led to the creation of numerous vendor-specific tools for electronic control unit (ECU) development. While this approach simplifies and supports the re-usability of vehicle functions it also increases the complexity as well as the difficulty for integration tests and error localization. In this paper, we present a conceptual platform which allows to establish references between different development and test phase items in a developer-friendly way. It revolves around two self-developed tools supported by an extensive AUTOSAR knowledge base. The system creates inter-connectivity so that it becomes easier to locate the actual origin of a misbehavior or to find a test error manifestation in the actual end system for developers and testers alike

Introduction to the Proceedings of the ISCSET 2023: The 12th International Symposium on Computer Science, Computer Engineering and Educational Technologies

The 12th International Symposium on Computer Science, Computer Engineering and Educational Technologies (ISCSET 2023) is published in a special issue of the Embedded Self-Organizing Systems journal of the Chemnitz University of Technology for the second time. In a significant first, ISCSET 2023 utilized the EasyChair conference management platform for paper submissions. Each submission underwent thorough review by three esteemed professors and researchers from our partner universities, resulting in 27 submissions with an acceptance rate of 62%. But ISCSET 2023 was more than just papers; it was a dynamic symposium that featured engaging keynote presentations, thought-provoking talks by invited speakers as well as lively paper presentations. We had participants from 18 countries: Germany, Mongolia, China, France, Jordan, Algeria, Japan, Kazakhstan, Uzbekistan, Bangladesh, India, Iraq, Turkey, Afghanistan, Iran, Tunis, Pakistan and Syria. Thus, with ISCSET 2023 we celebrated a true global convergence of knowledge and ideas

An Event-based Local Action Paradigm to Improve Energy Efficiency in Queriable Wireless Sensor Actuator Networks

Wireless sensor networks (WSN) are deployed in a multitude of applications both in industrial and academic fields. In recent years, due to the emerge of Internet of Things (IoT) technologies and Vehicle2X communication scenarios, novel challenges for wireless sensor network platforms - regarding hardware and software - arose. Thus, challenges known from big data processing have reached the WSN scope and consequently approaches and methods have been devised to handle these. One such approach is queriable wireless sensor networks which enable their users the specification of sensing tasks in a declarative way without the need to re-program nodes in case the application requirements change. As many current WSN applications feature active parts with which nodes can directly influence their environment, the term wireless sensor actuator networks (WSAN) has been coined, setting such networks apart from solely passively measuring networks.In this article, we will present a short introduction to big data processing in wireless sensor networks which motivates the usage of queriable networks. We will show that in order to enable a WSAN to carry out actions energy-efficiently and in a timely manner, an event-based action model is favorable. Additionally, we will demonstrate how such an event system can be used to improve sub query performance in WSNs. We conclude with an evaluation regarding the benefit of combining this approach with wake-up receiver technologies based on a qualitative energy efficiency definition for WSN

Generische Datenerfassung und Aufbereitung im Kontext verteilter, heterogener Sensor-Aktor-Systeme

Die vorgestellte Arbeit präsentiert ein geschlossenes Konzept für die synchronisierte Erfassung, Verarbeitung und Aufbereitung beliebiger Sensor-Informationen. Es ist nun möglich, heterogene Sensornetze sowie dedizierte, autarke Messsysteme zeitlich zu koordinieren und entsprechend in Relation zu setzen. Auf Basis von XML erfolgt die ganzheitliche Beschreibung des Monitoring-Szenarios und die Einordnung der einzelnen Datensätze. Die Informationen können nun in beliebigen Ausgabeformaten anwendungsspezifisch definiert und visualisiert werden. Zusätzlich ermöglichen Mechanismen zur gezielten Messwert-Vorverarbeitung und -Filterung eine Senkung des benötigten Datenvolumens. Die Funktionalität des vorgestellten GREASE-Frameworks wird am Beispiel eines geschlossenen Test-Systems aus dem Automotive-Bereich evaluiert. Dabei wird die vorhandene Sensorik eines Kfz-Bordnetzes mit einem zusätzlichen Netzwerk aus Sensorknoten verfeinert. Die korrelierten Daten werden anschließend für die Visualisierung mittels Google Earth, jBEAM und anderen Lösungen aufbereitet

The Greifswald Post COVID Rehabilitation Study and Research (PoCoRe)–Study Design, Characteristics and Evaluation Tools

(1) Background: COVID-19 is often associated with significant long-term symptoms and disability, i.e., the long/post-COVID syndrome (PCS). Even after presumably mild COVID-19 infections, an increasing number of patients seek medical help for these long-term sequelae, which can affect various organ systems. The pathogenesis of PCS is not yet understood. Therapy has so far been limited to symptomatic treatment. The Greifswald Post COVID Rehabilitation Study (PoCoRe) aims to follow and deeply phenotype outpatients with PCS in the long term, taking a holistic and comprehensive approach to the analysis of their symptoms, signs and biomarkers. (2) Methods: Post-COVID outpatients are screened for symptoms in different organ systems with a standardized medical history, clinical examination, various questionnaires as well as physical and cardiopulmonary function tests. In addition, biomaterials are collected for the analysis of immunomodulators, cytokines, chemokines, proteome patterns as well as specific (auto)antibodies. Patients are treated according to their individual needs, adhering to the current standard of care. PoCoRe’s overall aim is to optimize diagnostics and therapy in PCS patients