Chia-Yen Shih

COLA: Complexity-Reduced Trilateration Approach for 3D Localization in Wireless Sensor Networks

Localization has been an important topic in data-centric wireless sensor networks (WSNs) due to the special association between location information and the relevance of sensory data. Although most proposed approaches have been modeled for 2D space, a gradual but marked shift in the focus of 3D localization has taken place. While the 3D technique brings WSNs closer to reality, its complexity in computation and accuracy can be relatively high. In this paper, we propose a COmplexity-reduced 3D trilateration Localization Approach (COLA) based on RSSI values. Our goal is to lower the complexity by reducing 3D trilateration to 2D trilateration through the use of super anchor nodes—ones with pairwise positions whose coordinates only differ in the z-axis. In this paper, we conduct several empirical experiments in an indoor office setting, and evaluate our approach by comparison with a typical 3D trilateration algorithm. The results show that our approach outperforms the typical algorithm and yields more accurate results with lower computational cost.

TrainSense: a novel infrastructure to support mobility in wireless sensor networks

In this paper, we present TrainSense, a novel infrastructure to support the development and testing of mobile sensing applications. TrainSense merges a mote and a model train into a single mobile unit, and enhances the basic model train infrastructure with several important features required for the evaluation of mobile scenarios. First, we develop a real-time controller to send control packets to model trains and motes to manage the network topology. Second, we design and implement a positioning system with centimeter precision. Third, we use the power available on the tracks to provide unlimited energy to the motes. Fourth, we provide a way for the motes to dock into a custom USB port, for reprogramming and data download. We evaluate TrainSense in two ways: (i) we establish the correctness of the implementation and measure the performance of its components, and (ii) we demonstrate its practical use with two sample wireless sensor network application scenarios: self-deployment and data muling.

On the Cooperation between Mobile Robots and Wireless Sensor Networks

Employing cooperative heterogeneous systems can enrich application scenarios and achieve higher application performance. The combination of mobile robots and Wireless Sensor Networks (WSNs) is a good example of such cooperation, and many recent research results have highlighted the benefits of the marriage of these two technologies. The main objectives of this chapter include: (1) providing a survey on a variety of applications with cooperating mobile robots and WSNs based on the roles they play for interaction, and (2) elaborating different cooperative interactions of robots and WSNs in our ongoing project, PLAtform for the deployment and operation of heterogeneous NETworked cooperating objects (PLANET), which is an integrated framework of heterogeneous cooperative objects for network deployment and operations.

Helicopter UAV systems for in situ measurements and sensor placement

The use of unmanned aerial systems (UAS) is growing in research and civil applications. Advancing technology offers huge potential which is just starting being used. We present a method to have a helicopter UAS interacting with the environment physically. This basic technology, which includes high precision control and a vision system can be adapted for different in situ measurement tasks. Applications cover a wide range from placement of sensors or direct measurements to sampling. While UAS systems get more complex, we describe a way of interacting with a them by means of an interactive control framework, which can also include other systems and sensors.

IRIS: Efficient Visualization, Data Analysis and Experiment Management for Wireless Sensor Networks

The design of ubiquitous computing environments is challenging, mainly due to the unforeseeable impact of real-world environments on the system performance. A crucial step to validate the behavior of these systems is to perform in-field experiments under various conditions. We introduce IRIS, an experiment management and data processing tool allowing the definition of arbitrary complex data analysis applications. While focusing on Wireless Sensor Networks, IRIS supports the seamless integration of heterogeneous data gathering technologies. The resulting flexibility and extensibility enable the definition of various services, from experiment management and performance evaluation to user-specific applications and visualization. IRIS demonstrated its effectiveness in three real-life use cases, offering a valuable support for in-field experimentation and development of customized applications for interfacing the end user with the system.

Experimental Study for Multi-layer Parameter Configuration of WSN Links

Many applications of wireless sensor networks (WSNs) need to balance multiple yet often conflicting performance requirements such as high energy efficiency, high throughput, low delay and low loss. Finding appropriate WSN parameter configuration to achieve the best trade-off requires in depth understanding of the joint effect of key parameters residing at different layers on the performance. In this paper, we present an extensive experimental study on the data delivery performance of aWSN link, where 4 major performance metrics, namely energy, throughput, delay and loss, were measured over 6 months under around 50 thousand parameter configurations of 7 key stack parameters. Different from existing work, rich observations are made out of the extensive measurement data, with the focus on the joint effect of these parameters on the performance. Specifically, for each of the four performance metrics, a set of guidelines is derived for parameter optimization. In addition, we propose empirical models for each performance metric to quantify the joint effects, which enable finding optimal settings for parameters such as payload size or retransmissions, in consideration of link quality and other parameter settings, to achieve better performance trade-offs. To demonstrate the potential of this work, the obtained joint parameter optimization results are applied to an example. The outcome is compared with those achieved by following representative single-parameter tuning guidelines from the literature. The comparison reveals that by considering the joint effect of multi-layer parameters together, a WSN application can obtain a much improved performance trade-off.

Kassandra: A framework for distributed simulation of heterogeneous cooperating objects

Abstract To address the heterogeneity and scalability issues of simulating Cooperating Objects (COs) systems, we propose Kassandra , a conceptual framework for enabling distributed COs simulation by integrating existing simulation tools. Moreover, Kassandra exploits the communication middleware used by real-world COs as underlying communication mechanism for integrating Kassandra -enabled simulation tools. In this way, real-world COs can be included with simulated objects in a seamless way to perform more accurate system performance evaluation. Moreover, such a hardware-in-the-loop approach is not limited to pre-deployment performance analysis, and can offer possibilities to analyse performance at different phases of CO applications. The concept of Kassandra has been carried out in the EU PLANET project. In this paper, we introduce the Kassandra framework components and show their interactions at different phases for node deployments in PLANET use cases. The result demonstrates the applicability of Kassandra to facilitate the development of CO applications.

Demonstration abstract: a lightweight, portable device with integrated USB-host support for reprogramming wireless sensor nodes

Node reprogramming serves as an important service to support post-deployment code management and maintenance for unattended wireless sensor networks or autonomous robotics applications. We present a prototype of a design framework called SHAMPU, a Single chip Host for Autonomous Mote Programming over USB. A SHAMPU device is portable and can be paired with a sensor node for post-deployment reprogramming that is OS independent. Moreover, it is small, lightweight and energy efficient. In the demo, we will present two scenarios, in which SHAMPU-paired Telosbs are integrated with a mobile flying robot and locomotives for local autonomous reprogramming by the flying robot and for network reprogramming with code dissemination via the data links on the tracks, respectively.

IRIS: A Flexible and Extensible Experiment Management and Data Analysis Tool for Wireless Sensor Networks

Performing field experiments is a key step to validate the design of a Wireless Sensor Network (WSN) application and to evaluate its performance under various conditions. We present an experiment management and data analysis tool called IRIS that offers effective management of various configuration settings forWSN experiments. One special feature of IRIS is its extensibility. That is, IRIS allows the developer to define customized functions for application-specific data analysis and performance evaluation. Other main features include: enabling the interaction with the deployedWSN at runtime for fine tuning the experiments and providing graphical presentation for visualizing the collected data as well as the processed results. We highlight the advantages of IRIS for the WSN application development in different experiment phases. Furthermore, we demonstrate the usefulness of IRIS with two real-life WSN applications to show that IRIS can be integrated to develop an application and can greatly help in performing experiments more efficiently.