7. GI/ITG KuVS Fachgespräch Drahtlose Sensornetze

In dem vorliegenden Tagungsband sind die Beiträge des Fachgesprächs Drahtlose Sensornetze 2008 zusammengefasst. Ziel dieses Fachgesprächs ist es, Wissenschaftlerinnen und Wissenschaftler aus diesem Gebiet die Möglichkeit zu einem informellen Austausch zu geben – wobei immer auch Teilnehmer aus der Industrieforschung willkommen sind, die auch in diesem Jahr wieder teilnehmen.Das Fachgespräch ist eine betont informelle Veranstaltung der GI/ITG-Fachgruppe „Kommunikation und Verteilte Systeme“ (www.kuvs.de). Es ist ausdrücklich keine weitere Konferenz mit ihrem großen Overhead und der Anforderung, fertige und möglichst „wasserdichte“ Ergebnisse zu präsentieren, sondern es dient auch ganz explizit dazu, mit Neueinsteigern auf der Suche nach ihrem Thema zu diskutieren und herauszufinden, wo die Herausforderungen an die zukünftige Forschung überhaupt liegen.Das Fachgespräch Drahtlose Sensornetze 2008 findet in Berlin statt, in den Räumen der Freien Universität Berlin, aber in Kooperation mit der ScatterWeb GmbH. Auch dies ein Novum, es zeigt, dass das Fachgespräch doch deutlich mehr als nur ein nettes Beisammensein unter einem Motto ist.Für die Organisation des Rahmens und der Abendveranstaltung gebührt Dank den beiden Mitgliedern im Organisationskomitee, Kirsten Terfloth und Georg Wittenburg, aber auch Stefanie Bahe, welche die redaktionelle Betreuung des Tagungsbands übernommen hat, vielen anderen Mitgliedern der AG Technische Informatik der FU Berlin und natürlich auch ihrem Leiter, Prof. Jochen Schiller

On the Cost of Shifting Event Processing within Wireless Environments

With the emergence of wireless sensor networks, the challenges of event recognition and processing have been partially shifted into the embedded domain. While new processing capabilities on small devices allow for physically close event monitoring and fast filtering, new challenges due to sparse resources or medium contention when relying on wireless communication arise. Within this talk, a short introduction into an experimental setup featuring event-detection on a construction fence is given. The goal has been to distinguish a person climbing over the fence from other events, which it may be exposed to, with the help of a wireless sensor network. The results obtained will be presented thoroughly. Regarding those, we discuss in which situations distributed event recognition and processing is to be preferred over a conventional server-centered deployment. Therefore, the costs such as communication, hardware and deployment related costs implying an architectural decision are examined

Ein regelbasiertes Programmiermodell für drahtlose Sensornetze

Increased efforts towards device miniaturization have led to the emergence of a new class of ad-hoc networks, the so called wireless sensor networks. Individual devices or nodes are commonly battery-powered, small in size, equipped with a variety of sensors, frugal processing capabilities and a wireless transceiver. Spatially distributed within a deployment area, these nodes are able to autonomously form a network and cooperatively serve a specified task, for instance to acquire environmental data, to detect predefined events and/or to enable direct, physical interaction. Applications that rely on wireless sensor network technology are therefore typically concerned with the investigation of phenomena that either spread over a large area, that demand for autonomous scheduling over a great period of time, that require unobtrusive mechanisms for data collection or immediate reactivity to observed states. A wireless sensor network can hence be understood as an application enabler, a tool which can be utilized to build a specific application rather than having a purpose of its own. Application development for these kinds of networks is however complex, errorprone and tedious: Resource scarcity, timing constraints and a typically asynchronous operational model inherent to embedded devices are directly exposed to a programmer while at the same time, the need to map application semantics to run on a distributed, unreliable network has to be objected. Instead of being able to implement the envisioned application in a problem-oriented manner, the developer is forced to take a system-oriented viewpoint. This circumstance is especially disadvantageous when considering application domain experts and not professional software developers to be prospective users. This thesis proposes a holistic programming model called FACTS that combines two well-known mechanisms for abstracting from low-level challenges into a dedicated framework for wireless sensor network programming: Abstraction through provision of a better conceptual model via a higher-level language at design time, and abstraction due to deliberate support, especially at runtime. First of all, FACTS increases the expressiveness of sensor networking concerns with the help of a domain-specific language. Event-centric, problem-oriented task specification is enabled relying on a rule-based programming paradigm, while at the same time accessible hardware-related functionality is limited to only relevant features. Reactivity is captured at the language level by means of utilizing a natural, declarative yet concise representation. Moreover, application knowledge can be denoted equally well with the help of rules, as has already been proven e.g. in the context of business rule specification, making rules a good choice for non-professional developers. Furthermore, substantial support in terms of runtime support, development toolchain and encapsulation of typical sensor networking routines is provided within the FACTS middleware framework. The developer is empowered with a set of tools that accompany him throughout the development process and allow for simplified programming, debugging and testing. A core element here is the runtime environment that can be utilized on typical, small-scale wireless sensor nodes. It ensures the stable execution of rule-oriented programs by shielding a programmer from concerns such as manual stack management, correct event ordering and timing prerequisites of the underlying hardware. A number of protocols and applications ported to and developed for FACTS validate approach usability and shed a light on its advantages as well as on its bounds.Die fortschreitende Miniaturisierung technischer Bauteile erlaubt mittlerweile den flächendeckenden Einsatz kleinster Rechner, die sich durch drahtlose Kommunikation miteinander verbinden. Ausgestattet mit einer Vielzahl von Sensoren finden sich diese sogenannten drahtlosen Sensorknoten in ad-hoc Netzen zusammen, und ermöglichen so eine Vielzahl neuartiger Anwendungen. Die Programmierung dieser Sensornetze ist allerdings komplex und sehr fehleranfällig, da viele Faktoren wie die räumliche Verteilung, die unzuverlässige drahtlose Kommunikation und die Programmierung eingebetteter Systeme berücksichtigt werden müssen. Diese Dissertation stellt eine regelbasierte, domänen-spezifische Sprache und ein dazugehöriges Rahmenwerk vor, welches dem Programmierer eine abstrakte, problem-orientierte Sichtweise auf das Sensornetz zur Verfügung stellt. Neu ist, dass der Programmierer mit präzisen, mächtigen Sprachelementen die Reaktionen eines Sensorknotens auf komplexe Ereignisse definieren kann, ohne sich systembedingter Abläufe bewusst sein zu müssen. Verschiedene Optimierungsverfahren wurden vorgestellt, die sowohl die Laufzeit des Systems beschleunigen, als auch den Speicherverbrauch minimieren. Die Evaluation hat nicht nur die Qualität des Ansatzes in unterschiedlichsten Szenarien unter Beweis gestellt, sondern auch quantitativ nachgewiesen, dass die durch die Abstraktion bedingten, durchschnittlichen Verluste in Reaktivität keinen signifikanten Einfluss auf seine Nutzbarkeit haben

FACTS - A Rule-Based Middleware Architecture for Wireless Sensor Networks

Introducing a middleware abstraction layer into wireless sensor networks is a widely accepted solution to facilitate application programming and allow network organization. In this paper, we argue that although an event-based approach is the most obvious solution, it also provides the most natural way to address software development in wireless sensor networks. As a proof of concept, we introduce FACTS, a very flexible middleware framework able to provide support for a wide range of different applications. The objective is to combine advantages of event-centric processing and rule-based execution while preserving low resource usage

ABSTRACT On the Cost of Shifting Event Processing within Wireless Environments

With the emergence of wireless sensor networks, the issues of event recognition and processing have been partially shifted into the embedded domain. New processing capabilities on small devices allow for physically close event monitoring and fast filtering without having to set up a wired infrastructure beforehand. This opportunity for flexible deployments, local data storage and demand-driven event forwarding opens up new application areas for event-centric architectures. However, the convenience of localized event processing comes at a cost, such as sparse resources or medium contention when relying on wireless communication. Several parameters have to be evaluated to decide whether pushing the application logic into a sensor network is worthwhile, or whether a conventional server-centered deployment is to be preferred. In this paper, we discuss parameters influencing an architectural decision and their interdependencies, illustrate our contribution with the help of an example and provide a generic cost model for estimating this decision. 1

Using Network Density as a New Parameter to Estimate Distance

Abstract—A wireless sensor network consists of a large quan-tity of small, low-cost sensor nodes that are limited in terms of memory, available energy and processing capacity. Generally, these sensor nodes are distributed in space to obtain physical parameters such as temperature, humidity, vibration or light conditions, and transmit the measured values to a central entity. The measurements are tagged with the corresponding location of the nodes in the network and the time of sampling, to enable a view on the value distribution in space and time later on. Positioning of wireless sensor nodes without dedicated hardware is an open research question. Especially in the domain of embedded networked sensors, many applications rely on spatial information to relate collected data to the location of its origin. As a first step towards localization, an estimation of the distance between two nodes is often carried out to determine their positions. So far, the majority of approaches therefore explore physical properties of radio signals such as the strength of a received signal or its trip time. However, this is problematic since either the complexity on the software or on the hardware side is not adequate for embedded systems, or the approaches lack the required accuracy. In this paper we present the WDNI algorithm (Weighted Density of Node Intersection) to determine the distance between two nodes, relying solely on the investigation of local node densities. To evaluate the accuracy of this algorithm, we ran extensive simulations and experimented with different testbed setups using real sensor nodes, and finally compared WDNI to a range-free distance estimation algorithm based the analysis of RSSI values. I

An Efficient Implementation of Reinforcement Learning Based Routing on Real WSN Hardware

Abstract — Efficient multi-hop data dissemination is a crucial building block to enable mature wireless sensor network (WSN) applications. Exploiting machine learning for these routing problems has received increasing attention in recent years due to its flexibility and localized mechanisms. However, with such an approach the resulting protocols often have additional memory and processing time requirements. Nevertheless, these requirements are within the reach of today’s WSN hardware, however few substantial tests have been performed to clearly demonstrate this. This paper evaluates and discusses the results and experiences gained from implementing our reinforcement learning based multicast routing protocol (FROMS) in a testbed of ScatterWeb nodes. A comparison of our results is made to a well-known WSN routing scheme, namely a multicast variation of Directed Diffusion. Our evaluation includes several minor, but practical modifications to both protocols such as transmission backoffs and the use of acknowledgments. This paper offers three main contributions. First, we demonstrate that machine learning algorithms can be efficiently implemented on resource restricted devices and that they perform very well in multiple network scenarios. Second, we confirm the validity of simulation results obtained in a previous evaluation of FROMS, and at the same time gather delivery rates under realistic settings. Finally, we offer some general observations on properties and pitfalls of WSN implementations along with potential solutions. I

Mobile Agents: A Construction Kit for

Mobile Agents are a well-known programming paradigm nowadays. There is a multitude of research concerning Mobile Agent Systems with emphasize on agent coordination, agent languages and agent migration technology. On the one hand, it is often argued, that Mobile Agents are well-suited for the use in the Internet and especially with Mobile Devices and roaming users. On the other hand, there are only few publications describing the actual implementation of a Mobile Agent System for Mobile Devices