Matthias Handy

Low energy adaptive clustering hierarchy with deterministic cluster-head selection

This paper focuses on reducing the power consumption of wireless microsensor networks. Therefore, a communication protocol named LEACH (low-energy adaptive clustering hierarchy) is modified. We extend LEACHs stochastic cluster-head selection algorithm by a deterministic component. Depending on the network configuration an increase of network lifetime by about 30% can be accomplished. Furthermore, we present a new approach to define lifetime of microsensor networks using three new metrics FND (First Node Dies), HNA (Half of the Nodes Alive), and LND (Last Node Dies).

Wireless sensor networks - new challenges in software engineering

Software development for wireless sensor networks requires novel programming paradigms and technologies. This article describes the concept of a new service oriented software architecture for mobile sensor networks. With this architecture, a flexible, scalable programming of applications based on an adaptive middleware is possible. The middleware supports mechanisms for cooperative data mining, self-organization, networking, and energy optimization to build higher-level service structures. The purpose of our research activities is the development of a framework, which radically simplifies the development of software for sensor network applications.

SeNeTs - test and validation environment for applications in large-scale wireless sensor networks

We present SeNeTs, a powerful software environment for test and validation of sensor network applications. SeNeTs is not tied to a specific hardware platform. It administrates large-scale sensor networks during execution without affecting communication among sensor nodes. Moreover, SeNeTs allows efficient debugging of sensor network applications with sophisticated update mechanisms

Energy-efficient data collection for Bluetooth-based sensor networks

A wide range of sensor network applications deals with an issue often referred to as data collection: sensor nodes periodically transmit data to a base station. The base station analyzes incoming data for interesting events. In this paper, we introduce a novel data collection protocol (DCP) for wireless sensor networks. DCP is tailored to Bluetooth-based sensor nodes and therefore enables sensor network applications based on inexpensive COTS-hardware. DCP is scalable, robust and not limited to piconet or scatternet structures. As a potential application of DCP, we describe a wireless sensor network deployed as flood prevention system.

DCP: a new data collection protocol for Bluetooth-based sensor networks

Two economic factors are essential for the success of wireless sensor networks as new key technology: low-cost hardware and strong prototype applications. Although not perfect, Bluetooth can be a driving technology in this domain. We present a new data collection protocol (DCP) for wireless sensor networks. DCP is tailored to Bluetooth-based sensor nodes and therefore enables sensor network applications based on inexpensive hardware. DCP is scalable, robust, and not limited to piconet or scatternet structures.

Budget-Based Clustering with Context-awareness for Sensor Networks

As the scale of modern sensor networks continues to grow, energy consumption, scalability and routing efficiency are becoming key design challenges. Network management plays an important role in achieving these goals. By decomposing a sensor network into smaller groups, clustering and its variants have been presented as efficient ways in network management. In this paper, we propose a dynamic, localized clustering approach derived from generic budget-based clustering techniques. The approach generates dynamic cluster sizes for a hierarchy of cluster heads, with respect to network context such as residual energy and activity rates of sensor nodes. We further refine the local estimated cluster sizes by using additional feedback during clustering process. Simulation results of stochastic deployment are used to demonstrate the performance of our algorithm, as well as the impact of context information as clustering parameters.

Prozessoren in Prozessen: Hardware und Dienste für allgegenwärtiges Rechnen

Aktuelle Entwicklungstendenzen im Hardwarebereich bilden das Fundament von Basistechnologien und neuartigen Anwendungen des Ubiquitous Computing. Moores Gesetz von der Verdopplung der Transistordichte auf Mikro-chips lasst sich — abgesehen von der Energiedichte von Energiequellen wie zum Beispiel Batterien — auf viele andere Leistungsparameter technischer Systeme ausweiten. Dieser Trend fuhrt — zusammen mit der Entwicklung neuer Werkstoffe und Fertigungsverfahren — zu immer kleineren und leistungsfahigeren Prozessoren, Sensoren, Aktoren und Kommunikationseinrichtungen und damit, als Verbund der Einzelkomponenten, zu miniaturisierten drahtlosen Sensorknoten. Neue selbstorganisierende Ansatze in der Softwaretechnik erlauben es, eine Vielzahl dieser Sensorknoten zu lokalisieren, zu vernetzen und kooperativ zur Bewaltigung von Uberwachungs- und Steuerungsaufgaben einzusetzen.