Maciej J. Zawodniok

Predictive Congestion Control Protocol for Wireless Sensor Networks

Available congestion control schemes, for example transport control protocol (TCP), when applied to wireless networks results in a large number of packet drops, unfairness with a significant amount of wasted energy due to retransmissions. To fully utilize the hop by hop feedback information, a suite of novel, decentralized, predictive congestion control schemes are proposed for wireless sensor networks in concert with distributed power control (DPC). Besides providing energy efficient solution, embedded channel estimator in DPC predicts the channel quality. By using the channel quality and node queue utilizations, the onset of network congestion is predicted and congestion control is initiated. Stability of the hop by hop congestion control is demonstrated by using a Lyapunov-based approach. Simulation results show that the proposed schemes result in fewer dropped packets than a network without the hop-by-hop congestion control, better fairness index and network efficiency, higher aggregate throughput, and smaller end-to-end delays over the other available schemes like IEEE 802.11 protocol.

Reducing common-mode voltage in three-phase sine-triangle PWM with interleaved carriers

Interleaving pulse width modulation (PWM) waveforms is a proven method to reduce ripple in dc-dc converters. The present study explores interleaving for three-phase motor drives. Fourier analysis shows that interleaving the carriers in conventional uniform PWM significantly reduces the common-mode voltage. New digital signal processor (DSP) hardware supports interleaving directly with changes to just two registers at setup time, so no additional computation time is needed during operation. The common-mode voltage reduction ranges from 36% at full modulation to 67% when idling with zero modulation. Third-harmonic injection slightly reduces the advantage (to 25% at full modulation). However, the maximum RMS common-mode voltage is still less than 20% of the bus voltage under all conditions. The disadvantage of the proposed approach is an increase in current ripple at the switching frequency. Simulations verify the findings. Experiments on a motor drive that uses a commercially available motor-control DSP, connected to a 5 hp motor, agree well with calculations and simulations.

An Online Outlier Identification and Removal Scheme for Improving Fault Detection Performance

Measured data or states for a nonlinear dynamic system is usually contaminated by outliers. Identifying and removing outliers will make the data (or system states) more trustworthy and reliable since outliers in the measured data (or states) can cause missed or false alarms during fault diagnosis. In addition, faults can make the system states nonstationary needing a novel analytical model-based fault detection (FD) framework. In this paper, an online outlier identification and removal (OIR) scheme is proposed for a nonlinear dynamic system. Since the dynamics of the system can experience unknown changes due to faults, traditional observer-based techniques cannot be used to remove the outliers. The OIR scheme uses a neural network (NN) to estimate the actual system states from measured system states involving outliers. With this method, the outlier detection is performed online at each time instant by finding the difference between the estimated and the measured states and comparing its median with its standard deviation over a moving time window. The NN weight update law in OIR is designed such that the detected outliers will have no effect on the state estimation, which is subsequently used for model-based fault diagnosis. In addition, since the OIR estimator cannot distinguish between the faulty or healthy operating conditions, a separate model-based observer is designed for fault diagnosis, which uses the OIR scheme as a preprocessing unit to improve the FD performance. The stability analysis of both OIR and fault diagnosis schemes are introduced. Finally, a three-tank benchmarking system and a simple linear system are used to verify the proposed scheme in simulations, and then the scheme is applied on an axial piston pump testbed. The scheme can be applied to nonlinear systems whose dynamics and underlying distribution of states are subjected to change due to both unknown faults and operating conditions.

Energy-Efficient Hybrid Key Management Protocol for Wireless Sensor Networks

In this paper, we propose a subnetwork key management strategy in which the heterogeneous security requirements of a wireless sensor network are considered to provide differing levels of security with minimum communication overhead. Additionally, it allows the dynamic creation of high security subnetworks within the wireless sensor network and provides subnetworks with a mechanism for dynamically creating a secure key using a novel and dynamic group key management protocol. The proposed energy-efficient protocol utilizes a combination of pre-deployed group keys and initial trustworthiness of nodes to create a level of trust between neighbors in the network. This trust is later used to allow secure communication between neighbors when creating a dynamic, high security subnetwork within the sensor network. Results of simulations of the protocol in Ns2 are presented and the complexity of the protocol is analyzed. The proposed protocol reduces delay by 50% and energy consumption by 70% over the existing dynamic group key management (DGKM) scheme.

A testbed architecture for Auto‐ID technologies

Purpose – This paper presents an overview on the Auto‐ID (Automatic Identification) technologies testbed that has been established at the University of Missouri‐Rolla (UMR) with the objective of supporting research, development, and implementation of Auto‐ID technologies in network‐centric manufacturing environments.Design/methodology/approach – UMRs Auto‐ID testbed uses a unique hardware‐in‐the‐loop simulation methodology, which integrates decision‐making model development with the design of networking topology and data routing/scheduling schemes, in order to develop, test, and implement viable Auto‐ID solutions. The methodology is founded on a 3‐level integrated model: controller simulation, distributed controller simulation, and distributed controller simulation with hardware‐in‐the‐loop.Findings – This paper discusses two case studies that highlight the effective use of RFID technology, its potential advantages, challenges, and deficiencies stemming from particular applications. These applications in...

Detection and localization of multiple R/C electronic devices using array detectors

Accurate detection and localization of unintended emissions from multiple radio-controlled electronic devices have a wide range of security applications. First, this paper introduces a cost-effective mobile array detector. Subsequently, a novel scheme is presented for detection and localization of multiple devices emitting unintended passive emissions. Peak detection is employed in detecting the devices with superheterodyne receivers (SHRs). Experimental results demonstrate that the proposed scheme outperforms the traditional methodologies with a single antenna. A 2-D array is also proposed in this paper for localization of devices with SHRs using the angle of arrival. A new, synthetic aperture radar (SAR)-based scheme called edge synthetic aperture radar (ESAR) is also introduced in this paper for localization. Finally, the results for localization and error in localization are analyzed. The ESAR method reduces the error in localization up to 75% and increases accuracy in detection of multiple devices.

Embeddable Sensor Mote for Structural Monitoring

An embeddable sensor mote for structural monitoring is described. The Missouri University of Science and Technology (MST) F1 mote is designed to provide a general platform for sensing, networking, and data processing. The platform consists of an 8051 variant processor, two 802.15.4 variant radio platform options, micro Smart Digital (SDTM) flash storage, USB connectivity, RS-232 connectivity, and various sensor capabilities. Sensor capabilities include, but are not limited to, strain gauges, a three-axis multi-range accelerometer, thermocouples, and interface options for other digital and analog sensors via a screw terminal block. In its default configuration the strain conditioning channel is appropriate for structural monitoring, but through reconfiguration it can be used with other resistive bridge transducers for pressure, force, displacement, etc. The F1 mote provides capabilities for strain, temperature, and vibration sensing in a small package. The mote is used at MST for networked monitoring of structures and networked robotic vehicles. In this paper an overview of the F1 mote will be given that emphasizes its operating architecture and potential applications. Applications include infrastructure monitoring for structures such as bridges, levees, and buildings as well as robotics, machine monitoring, and sensor networks. The described platform provides novelty in that it has the ability to be a dedicated structural monitoring system, however can be also used in development of other systems. The F1 platform was designed to combine features of available dedicated platforms and available development kits. The F1 provides a novel combination of sensing, processing, and application possibilities for the targeted application areas.

Indoor positioning system using geo-magnetic field

In this paper we address the problem of non-adversarial co-operative localization using the Earths ambient magnetic field. We demonstrate the feasibility of using magnetic field to perform localization and tracking. A three-axis magnetic field sensor is employed to locate and track a target. The algorithm estimates the position using the magnitude of the current magnetic field readings. Our technique depends on the local distortions in the Earths magnetic field created by presence of various magnetic or metallic objects in the local workspace. These objects may be manmade or naturally occurring. The magnetic field data corresponding to known locations is stored in a database. A reverse lookup is used to estimate the position of the target. The localization techniques described in this paper have demonstrated successful target tracking with the average error radius of 2.5 feet.

Stability of a cyber-physical smart grid system using cooperating invariants

Cyber-Physical Systems (CPS) consist of computational components interconnected by computer networks that monitor and control switched physical entities interconnected by physical infrastructures. A fundamental challenge in the design and analysis of CPS is the lack of common semantics across the components. We address this challenge by employing a novel approach that composes the correctness of various components instead of their functionality using a conjunction of non-interfering logical invariants. We present a distributed algorithm that uses this approach to adaptively schedule power transfers between nodes in a smart power grid in such a way that the stability of both the computer network and the physical system are maintained. Simulation results demonstrate the necessity and usefulness of our approach in maintaining overall system stability in the presence of uncertainties in the computer network and with limited information about the global state of the system.

Detection of Super-Regenerative Receivers Using Hurst Parameter

The accurate and reliable detection of unintended emissions from radio receivers has a broad range of commercial and security applications. This paper presents and analyzes Hurst parameter-based detection method for super-regenerative receivers (SRRs). SRRs are low cost, easily manipulated, and widely used in common remote devices including doorbells, garage door openers, and remote controlled (R/C) toys. By design the SRR is a passive device that should only receive an RF signal. However, it also emits a low power, unintended electromagnetic signal. Such unintended emissions are enhanced by the presence of a known stimulating signal. Also, the emission is referred to as a device signature since it can uniquely identify the devices. The proposed detection method exploits a self-similarity property of such emissions to distinguish it from background noise. Hurst parameter quantifies the self-similarity. It is employed to detect and identify the SRR-based devices even if the signal fades into a noise.