Jan Blumenthal

Weighted Centroid Localization in Zigbee-based Sensor Networks

Localization in wireless sensor networks gets more and more important, because many applications need to locate the source of incoming measurements as precise as possible. Weighted centroid localization (WCL) provides a fast and easy algorithm to locate devices in wireless sensor networks. The algorithm is derived from a centroid determination which calculates the position of devices by averaging the coordinates of known reference points. To improve the calculated position in real implementations, WCL uses weights to attract the estimated position to close reference points provided that coarse distances are available. Due to the fact that Zigbee provides the link quality indication (LQI) as a quality indicator of a received packet, it can also be used to estimate a distance from a node to reference points.

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.

Improved Weighted Centroid Localization in Smart Ubiquitous Environments

Location-awareness is highly relevant subject in ubiquitous computing, as many applications exploit location information to provide adequate services or adapt to a changing physical environment. While GPS provides reliable outdoor localization, indoor positioning systems present a bigger challenge. Many indoor localization systems have been proposed. However, most of them rely on customized hardware or presume some dedicated infrastructure. In this paper, we focus on WLAN-based localization in smart ubiquitous environments. We propose an improved scheme of the Weighted Centroid Localization(WCL) algorithm that is robust and provides higher location accuracy than the original WCL algorithm. The improvements are based on the use of dynamic weighting factors that are solely dependent on the correlation of the Received Signal Strength Indicators of the received beacon signals. Compared to the original WCL scheme, our approach does not increase requirements to the environment. Real-world experiments in a typical environment that we report on in this paper confirm that the increased location accuracy determined in previous calculations is reproducible in a realistic noisy environment. This provides a simple, cost-efficient, and battery-conserving, but yet adequate technique for getting the accurate location information of mobile devices.

Precise Positioning with a Low Complexity Algorithm in Ad hoc Wireless Sensor Networks

ABSTRACT Nodes in a sensor network are often randomly distributed. To assign measurements to locations, each node has to determine its own position. Due to limited resources of the nodes, resource-aware positioning algorithms are required. In this paper, we present the novel “Weighted Centroid Localization” algorithm (WCL). Compared to other approximative algorithms, WCL achieves a remarkable average positioning error below 6%. Moreover, the algorithm features simple implementation and scales well in large sensor networks. In contrast to exact algorithms using analytical equations and complex matrix operations, WCL requires only a very small memory footprint.

Minimal transmission power as distance estimation for precise localization in sensor networks

Positioning sensor nodes requires distance information to reference points. Due to resource limitations in sensor networks, distance determination in low-cost sensor nodes without additional hardware is difficult. Known techniques such as distance estimation based on received signal strength (RSSI) are mostly inaccurate or have limitations. We propose a new method to measure the distance between a transmitting node and a receiving node using the minimal transmission power. The determined distance is more precise than RSSI, has a low variance and is therefore particularly suitable for positioning. Finally, we implemented a demonstrator application using weighted centroid localization to show the practical implementation.

Improved Precision of Coarse Grained Localization in Wireless Sensor Networks

In wireless sensor networks, the coarse grained localization is a method to compute the position of randomly distributed sensor nodes. Without optimizations, it provides low precision which heavily depends on the transmission range of base stations. In this paper, we propose novel optimizations of coarse grained localization with centroid determination (CGLCD) to determine the position of nodes more precisely. Our focus is to compute an optimal transmission range of all base stations and to reduce the total energy consumption. We present an analytic proof of a simple equation to determine the optimal transmission range in grid-aligned finite wireless sensor networks. Using this optimal transmission range, we reduced the positioning error about 80%. Thereby, nodes as well as base stations require lowest energy

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.

Framework for validation, test and analysis of real-time scheduling algorithms and scheduler implementations

This paper describes our work towards a rapid prototyping system for hard real-time systems focusing on scheduling algorithms and scheduler implementations. The framework aims at speeding up the decision making process during selection of a suitable scheduling algorithm for a real-time application. The framework supports various kinds of real-time scheduling algorithms, which can be simulated for evaluation purposes. Furthermore, implementations of these algorithms can be tested in a real-time operating system (RTOS) with real or synthetic workloads. The algorithms are implemented as software routines, which are part of the operating system (OS), or realized within a coprocessor to free the operating system kernel from time consuming scheduling operations. Both kinds of implementations have to provide an application programming interface that hides the algorithm from implementation issues. The target operating system of our framework is mainly RT-Linux, even though development for those systems is possible under Linux as well as Windows-NT. The framework proposed in this paper is new in that it supports the selection of the right algorithm and the right implementation for the target platform based on real-time scheduling analysis.

Controlling wireless sensor networks using SeNeTs and EnviSense

We present SeNeTs and EnviSense. SeNeTs is a powerful software environment for test and validation of sensor network applications. 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. EnviSense is a graphical frontend to easily configure and administrate sensor networks using SeNeTs. Both software systems are independent on the hardware platform and also able to run stand-alone.