ViFi: virtual fingerprinting WiFi-based indoor positioning via multi-wall multi-floor propagation model

Widespread adoption of indoor positioning systems based on WiFi fingerprinting is at present hindered by the large efforts required for measurements collection during the offline phase. Two approaches were recently proposed to address such issue: crowdsourcing and RSS radiomap prediction, based on either interpolation or propagation channel model fitting from a small set of measurements. RSS prediction promises better positioning accuracy when compared to crowdsourcing, but no systematic analysis of the impact of system parameters on positioning accuracy is available. This paper fills this gap by introducing ViFi, an indoor positioning system that relies on RSS prediction based on Multi-Wall Multi-Floor (MWMF) propagation model to generate a discrete RSS radiomap (virtual fingerprints). Extensive experimental results, obtained in multiple independent testbeds, show that ViFi outperforms virtual fingerprinting systems adopting simpler propagation models in terms of accuracy, and allows a sevenfold reduction in the number of measurements to be collected, while achieving the same accuracy of a traditional fingerprinting system deployed in the same environment. Finally, a set of guidelines for the implementation of ViFi in a generic environment, that saves the effort of collecting additional measurements for system testing and fine tuning, is proposed

Dynamic Resource Management in a Static Network Operating System

We present novel approaches to managing three key resources in an event-driven sensornet OS: memory, energy, and peripherals. We describe the factors that necessitate using these new approaches rather than existing ones. A combination of static allocation and compile-time virtualization isolates resources from one another, while dynamic management provides the flexibility and sharing needed to minimize worst-case overheads. We evaluate the effectiveness and efficiency of these management policies in comparison to those of TinyOS 1.x, SOS, MOS, and Contiki. We show that by making memory, energy, and peripherals first-class abstractions, an OS can quickly, efficiently, and accurately adjust itself to the lowest possible power state, enable high performance applications when active, prevent memory corruption with little RAM overhead, and be flexible enough to support a broad range of devices and uses

Doppelverankerte Softwarearchitektur für drahtlose Sensornetze

Nach einem Jahrzehnt intensiver Forschung und Entwicklung sind drahtlose Sensornetze (WSNs) kurz davor, sich von einer unbekannten Technologie in ein tragfähiges Marktsegment zu verwandeln. Während dieses Zeitraums hat sich die WSN-Knoten-Hardware ständig verbessert, was zu erhöhter Funktionalität und einer Reduzierung von Formfaktor, Kosten und Energieverbrauch geführt hat. Leider konnte die Software-Entwicklung nicht mit demselben Tempo voranschreiten. Die Begrenztheit der Betriebsmittel und anwendungsspezifische Anforderungen sind dafür verantwortlich, dass Entwickler geschlossene und integrierte Lösungen anstreben, was die Wiederverwendung von Entwürfen und Programmiercode behindern. Dies führt dazu, dass der erforderliche Aufwand für die Entwicklung neuer Anwendungen und ihre Anpassung an die sich kontinuierlich entwickelnde Hardware ansteigt. Das Fehlen einer allgemeinen Softwarearchitektur für WSNs wird von vielen Mitgliedern der wissenschaftlichen Gemeinschaft als wesentlicher Faktor für die existierenden Defizite angesehen. Wir präsentieren eine doppelverankerte Softwarearchitektur für drahtlose Sensornetze, die eine effektive WSN Entwicklung ermöglicht, indem traditionelle Methoden des Entwurfes und der Wiederverwendung von Programmiercode angewendet werden, unter Einhaltung von bewährten Prinzipien wie funktioneller Entkoppelung und dem Verbergen von Komplexität. Gleichzeitig wird ein Mechanismus zur Steuerung des inhärenten Kompromisses zwischen Effizienz und Wiederverwendung zur Verfügung gestellt, so dass sich die genannten Vorteile im Vergleich mit einer maßgeschneiderten und vertikal integrierten Lösung ohne einen übermäßig hohen Nachteil an Leistungsfähighkeit realisieren lassen. Die vorgestellte Architektur ist als ein Komponenten-System ausgeführt, das um zwei “Anker” angeordnet ist, die Beständigkeit ermöglichen und als die Basis für den Entwurf und die Wiederverwendung von Programmiercode dienen. Der untere Portabilitäts-Anker abstrahiert die Hardware und ermöglicht explizite Kontrolle des Performance-Portabilität Trade-offs. Der obere Interoperabilität-Anker abstrahiert die Knoten-lokalen Dienste mithilfe einer expressiven Publish/Subscribe Schnittstelle und unterstützt anwendungsspezifische Anpassung. Diese Dissertation vertritt die These, dass eine breite Softwarearchitektur, die auf diesen beiden Ebenen des Software-Stacks verankert ist, wirksam Portabilität und Interoperabilität fördern kann und dass dies unter Beachtung der Kosten für die involvierten Abstraktionen geschieht. Wir werten diese Behauptungen in qualitativer und quantitativer Art und Weise aus, und zwar anhand eines Beispiels, das eine Reihe von Prototyp-Implementierungen realisiert, von denen einige breite Anwendung in der WSN-Forschungs-Gemeinschaft gefunden haben. Zur Unterstützung der Auswertung haben wir eine spezifische Test-Infrastruktur entwickelt, die eine effiziente Prüfung der funktionalen und nicht-funktionalen Eigenschaften von WSN-Protokollen und -Diensten ermöglicht.After a decade of intense research and development, Wireless Sensor Networks (WSNs) are on the verge of transforming from an obscure technology into a viable market segment. In this period, the WSN node hardware has constantly improved, resulting in better functionality while size, cost and energy consumption have been reduced. Unfortunately, the software development process has not been able to keep the same pace. The tight resource constraints and the application-specific requirements are driving developers into closed and integrated solutions which impede design and code reuse, increasing the required effort for developing new applications and adapting them to an ever evolving hardware. The lack of a common software architecture for WSNs is seen by many in the research community as significant contributing factor for the existing inefficiencies. We introduce a double-anchored software architecture that enables effective WSN development through traditional methodologies of design and code reuse, using time-tested principles like functional decoupling and complexity hiding. At the same time, it provides mechanisms for controlling the inherent trade-offs between efficiency and reuse so the above benefits can be achieved without paying a prohibitively high price in performance, compared to a customized and vertically integrated solution. The proposed architecture is specified in the form of a component framework organized around two “anchors” that provide rigidity and establish a base for design and code reuse. The lower portability anchor abstracts the hardware while enabling explicit control over the performance-portability trade-offs. The upper interoperability anchor abstracts the node-local services behind an expressive publish/subscribe interface and supports application-specific customization. This dissertation contends that a broad software architecture, anchored at these two levels of the software stack, can effectively promote portability and interoperability while maintaining high sensibility towards abstraction costs. We evaluate these claims in qualitative and quantitative way, on the example of several prototype implementations, some of which are in wide use in the WSN community. To support the evaluation we have also developed a custom distributed testing infrastructure that enables efficient testing of functional and non-functional properties of WSN protocols and services

Demo Abstract: TWIST Actu-A RESTful Testbed Platform for Remote Experimentation With Building Automation Sensors and Actuators

Abstract The TWIST Actu platform is aimed at extending the capabilities of the TWIST testbed at TU Berlin with support for remote experiments involving building automation sensors and actuators, as part of a wider effort to migrate the testbed from a pure sensor network testbed to one that can also effectively host more challenging cyber-physical system experimental scenarios. In this demo paper we summarize the main features of the hardware and software architecture of TWIST Actu, focusing on the design of the RESTful remote experimentation API that supports a "Testbed as a Service" model of use of the testbed resources. We also present a prototype implementation of the platform and scenario for demonstrating its capabilities

JOI: Joint placement of IoT analytics operators and pub/sub message brokers in fog-centric IoT platforms

Internet of Things (IoT) systems are expected to generate a massive amount of data that needs to be processed. Given the large scale and geo-distributed nature of such systems, fog computing along with publish/subscribe (pub/sub) messaging has been proposed as possible solutions for coping with processing at scale. However, it is still unclear how practitioners can leverage the benefits of fog computing, e.g., how to optimally place data processing operators and pub/sub brokers. Moreover, current IoT systems typically rely on pub/sub brokers at the cloud, which might diminish the benefits offered by edge or fog processing as the communication between IoT operators has to be mediated by the brokers located in the cloud. To address this shortcoming, we propose to place the IoT application operators and the pub/sub brokers jointly on a network of nodes spanning from edge to the cloud considering various factors such as network topology or the locations of the IoT sensors and the consumers of the IoT applications. Different than the prior works, we specifically consider pub/sub brokers and their unique characteristics in the placement decision. First, we formulate the placement of operators and brokers jointly across edge, fog, and the cloud as a cost minimization problem. Next, we design two low-complexity heuristics. Our simulation results corroborate the argument that a placement in the cloud is usually a good option for IoT use cases, but also reveal the gap to the optimal solution in scenarios with heavier clustering of producers and consumers of sensor data. Studying the optimality gap shows that in such a setting heuristic solutions usually stay under a stretch factor of 2, with a worst case factor of 2.5 for a tabu-based solution and 2.85 for a greedy and a fixed placement in the cloud