Péter Völgyesi

Smart Dust: communicating with a cubic-millimeter computer

W hat do Rational Rose, Simulink, and LabVIEW have in common? At first, these tools seem very different. Rational Rose (http://www.rational.com) is a visual modeling tool, Simulink (http:// www.mathworks.com) is a hierarchical block-diagram design and simulation tool, and LabVIEW (http:// www.ni.com) is a graphical programming development environment. Despite the different terminology, these three tools share a common underlying theme: Each is an integrated set of modeling, model analysis, simulation, and code-generation tools that help design and implement computer-based systems (CBSs) in a specific, well-defined engineering field. These tools and other popular domain-specific integrated development environments can help capture specifications in the form of domain models. They also support the design process by automating analysis and simulating essential system behavior. In addition, they can automatically generate, configure, and integrate target application components. These environments translate the verified design—expressed in a domainspecific, primarily graphical modeling formalism—into a variety of artifacts that constitute a CBS implementation. These artifacts can include glue code, database schema, and configuration tables. These tools use domain-specific modeling languages that allow developers to represent essential design views and to both formally express and automatically enforce integrity constraints. These tools also support model composition that is synergistic with the design process in the particular engineering domain. Other benefits include having integrated models as opposed to relying merely on source code. In addition, the common input—that is, the shared design model—guarantees the consistency of different analysis results as long as all of the applied generators are correct. While the industry understands the welldocumented benefits of domain-specific, integrated modeling, analysis, and application-generation environments, their high cost represents a significant block to wide acceptance and application. Consequently, these tools are available only for domains with large markets in which high volume offsets the substantial initial investment cost. For CBSs in smaller, specialized domains, or even for single projects, the industry needs technology that can help rapidly and efficiently compose these environments from reusable components.Domain-specific integrated development environments can help capture specifications in the form of domain models. These tools support the design process by automating analysis and simulating essential system behavior. In addition, they can automatically generate, configure, and integrate target application components. The high cost of developing domain-specific, integrated modeling, analysis, and application-generation environments prevents their penetration into narrower engineering fields that have limited user bases. Model-integrated computing (MIC), an approach to model-based engineering that helps compose domain-specific design environments rapidly and cost effectively, is particularly relevant for specialized computer-based systems domains-perhaps even single projects. The authors describe how MIC provides a way to compose such environments cost effectively and rapidly by using a metalevel architecture to specify the domain-specific modeling language and integrity constraints. They also discuss the toolset that implements MIC and describe a practical application in which using the technology in a tool environment for the process industry led to significant reductions in development and maintenance costs.

Radio interferometric geolocation

We present a novel radio interference based sensor localization method for wireless sensor networks. The technique relies on a pair of nodes emitting radio waves simultaneously at slightly different frequencies. The carrier frequency of the composite signal is between the two frequencies, but has a very low frequency envelope. Neighboring nodes can measure the energy of the envelope signal as the signal strength. The relative phase offset of this signal measured at two receivers is a function of the distances between the four nodes involved and the carrier frequency. By making multiple measurements in an at least 8-node network, it is possible to reconstruct the relative location of the nodes in 3D. Our prototype implementation on the MICA2 platform yields an average localization error as small as 3 cm and a range of up to 160 meters. In addition to this high precision and long range, the other main advantage of the Radio Interferometric Positioning System (RIPS) is the fact that it does not require any sensors other than the radio used for wireless communication.

Simulation-based optimization of communication protocols for large-scale wireless sensor networks

6 15-322-3 162 Abstr-act-The design of reliable, dynamic, fault-tolerant services in wireless sensor networks is a big challenge and a hot research topic. In this paper an optimization method is proposed that can be used to tune parameters of the middleware services and applications to provide optimal performance. The optimization method is based on simulation, and is capable of handling noisy error surfaces. The proposed optimization algorithm is illustrated by a new spanning-tree formation algorithm, which can effectively operate even if links between nodes are asymmetrical. In the near future large-scale sensor networks will be the key elements of embedded systems used in space and aviationrelated challenges, e.g. monitoring and control of safety critical systems [l], Smart Surfaces, Smart Dust [2], or can be used to make everyday life more comfortable, e.g. Intelligent Spaces [3]. These sensor networks often use distributed operating system-like services (called middleware) over wireless communication protocols, which must be fault tolerant and adaptive because of the dynamic network topology and changing mission objectives. The design of such middleware services is not straightforward, since the sensors have limited resources, and thus the used protocols are usually very simple compared to ones used in wired communication schemes. The nondeterministic nature of the environment is another factor making the design more difficult. This paper presents a simulation-based optimization method that can be used to tune the algorithms used in the middleware layer. Also some results are presented that were gained by the proposed method. The hardware structure of the wireless sensors may vary greatly, but invariably each of the intelligent sensors is a compact device with its own power source, it contains a processing unit (a small microprocessor), a communication unit and the sensor itself. The widely used Berkeley fieldnodes (or motes) have similar structure containing an 8-bit microcontroller, a 916.5 MHz radio and several interchangeable sensors. These tiny units have a simple local operating system called TinyOS. Application-specific middleware services can be added to provide an interface between the application and the primitive services of the local operating system. The middleware can also be considered as a distributed operating system that establishes network-wide resources and functions that the applications can utilize, e.g. leader election, spanning tree formation, distributed consensus and mutual exclusion, distributed transactions, group communication services, clock synchronization, etc. Typical applications may include hundreds or thousands of motes with often unknown or random distribution (e.g. motes dropped from an airplane to a hostile environment). The communication services must be reliably established to achieve the overall goal of the distributed sensor system. During the operation of the sensor network different metrics for the quality of service (QoS) are required, a dynamic tradeoff is necessary between accuracy, response time, power consumption, and other qualities of interest. Thus, the middleware services must be prepared to adapt to the actual circumstances and the QoS metric. To design such middleware services, the highly random nature of the environment (wireless communication with possible disturbances, random layout, possibly damaged motes, etc.) must be taken into consideration. The proposed design method is a probabilistic simulationbased optimization that can help the designer choose the right algorithm with an optimal parameter set. The MATLAB-based simulator is capable of simulating the important aspects of the communication scheme: local OS services including the network protocol stack, and also the radio transmission phenomena (signal power vs. distance, fading, collision, disturbances). In the simulation

Countersniper system for urban warfare

An ad-hoc wireless sensor network-based system is presented that detects and accurately locates shooters even in urban environments. The localization accuracy of the system in open terrain is competitive with that of existing centralized countersniper systems. However, the presented sensor network-based solution surpasses the traditional approach because it can mitigate acoustic multipath effects prevalent in urban areas and it can also resolve multiple simultaneous shots. These unique characteristics of the system are made possible by employing novel sensor fusion techniques that utilize the spatial and temporal diversity of multiple detections. In this article, in addition to the overall system architecture, the middleware services and the unique sensor fusion algorithms are described. An analysis of the experimental data gathered during field trials at US military facilities is also presented.

Shooter localization and weapon classification with soldier-wearable networked sensors

The paper presents a wireless sensor network-based mobilecountersniper system. A sensor node consists of a helmetmountedmicrophone array, a COTS MICAz mote for internodecommunication and a custom sensorboard that implementsthe acoustic detection and Time of Arrival (ToA) estimationalgorithms on an FPGA. A 3-axis compass providesself orientation and Bluetooth is used for communicationwith the soldiers PDA running the data fusion and the userinterface. The heterogeneous sensor fusion algorithm canwork with data from a single sensor or it can fuse ToA orAngle of Arrival (AoA) observations of muzzle blasts andballistic shockwaves from multiple sensors. The system estimatesthe trajectory, the range, the caliber and the weapontype. The paper presents the system design and the resultsfrom an independent evaluation at the US Army AberdeenTest Center. The system performance is characterized by 1-degree trajectory precision and over 95% caliber estimationaccuracy for all shots, and close to 100% weapon estimationaccuracy for 4 out of 6 guns tested.

Sensor node localization using mobile acoustic beacons

We present a mobile acoustic beacon based sensor node localization method. Our technique is passive in that the sensor nodes themselves do not need to generate an acoustic signal for ranging. This saves cost, power and provides stealthy operation. Furthermore, the beacon can generate much more acoustic energy than a severely resource constrained sensor node, thereby significantly increasing the range. The acoustic ranging method uses a linear frequency modulated signal that can be accurately detected by matched filtering. This provides longer range and higher accuracy than the current state-of-the-art. The localization algorithm was especially designed to work in such acoustically reverberant environment, as urban terrain. The algorithm presented handles non-Gaussian ranging errors caused by echoes. Node locations are computed centrally by solving a global non-linear optimization problem in an iterative and incremental fashion

On metamodel composition

Computer-based systems (CBS) development integrates various disciplines, such as hardware design, software engineering, and performance modeling, as well as the base engineering discipline in which the CBS will operate. As such, use of a non-native modeling language is not acceptable when performing CBS design, and rapid specification and development of domain-specific modeling languages (DSMLs) is necessary. We advocate a UML-based metamodeling technique to DSML specification and generation. A key feature of our approach is the composition of new metamodels from existing metamodels through the use of three newly defined UML operators-equivalence, implementation inheritance, and interface inheritance. The paper describes the development of these new operators, details how they are used in metamodel composition, and presents examples of metamodel composition.

Air Quality Monitoring with SensorMap

The mobile air quality monitoring network (MAQUMON) is presented. The system consists of a number of car-mounted sensor nodes measuring different pollutants in the air. The data points are tagged with location and time utilizing an on-board GPS. Periodically, the measurements are uploaded to a server, processed and then published on the SensorMap portal. Given a sufficient number of nodes and diverse mobility patterns, a detailed picture of the air quality in a large area will be obtained at a low cost.

Wireless Acoustic Emission Sensor Network for Structural Monitoring

The paper presents a prototype wireless system for the detection of active fatigue cracks in aging railways bridges in real-time. The system is based on a small low-cost sensor node, called an AEPod, that has four acoustic emission (AE) channels and a strain channel for sensing, as well as the capability to communicate in a wireless fashion with other nodes and a base station. AEPods are placed at fracture-critical bridge locations. The strain sensor detects oncoming traffic and triggers the AEPod out of its hibernation mode. As the train stresses the fracture-critical member, acoustic emission and strain data are acquired. The data are compressed and filtered at the AEPod and transmitted off the bridge using cell-phone communication.

Multiple simultaneous acoustic source localization in urban terrain

Experiences developing a sensor network-based acoustic shooter localization system are presented. The system is able to localize the position of a shooter and the trajectory of the projectile using observed acoustic events, such as the muzzle blast and the ballistic shockwave. The network consists of a large number of cheap sensors communicating through an ad-hoc wireless network, which enables the system to resolve multiple simultaneous acoustic sources, eliminate multipath effects, tolerate multiple sensor failures while providing good coverage and high accuracy, even in such challenging environment as urban terrain. The paper describes the hardware and software platform developed for this application and summarizes the lessons learned during the development of the system.