Optimal Sleep-Wake Scheduling for Quickest Intrusion Detection using wireless sensor Networks

We consider the problem of quickest detection of an intrusion using a sensor network, keeping only a minimal number of sensors active. By using a minimal number of sensor devices,we ensure that the energy expenditure for sensing, computation and communication is minimized (and the lifetime of the network is maximized). We model the intrusion detection (or change detection) problem as a Markov decision process (MDP). Based on the theory of MDP, we develop the following closed loop sleep/wake scheduling algorithms: 1) optimal control of Mk+1, the number of sensors in the wake state in time slot k + 1, 2) optimal control of qk+1, the probability of a sensor in the wake state in time slot k + 1, and an open loop sleep/wake scheduling algorithm which 3) computes q, the optimal probability of a sensor in the wake state (which does not vary with time),based on the sensor observations obtained until time slot k.Our results show that an optimum closed loop control onMk+1 significantly decreases the cost compared to keeping any number of sensors active all the time. Also, among the three algorithms described, we observe that the total cost is minimum for the optimum control on Mk+1 and is maximum for the optimum open loop control on q.

Reliable Routing in Sensor Networks

In sensor networks, routing algorithms should be designed such that packet losses due to wireless links are reduced.In this paper, we present a ”potential”-based routing scheme to find routes with high packet delivery ratios. The basic idea is to define a scalar potential value at each node in the network and forward data to the neighbour with the highest potential.For a simple 2-relay network, we propose a potential function that takes into account wireless channel state. Markov-chain based analysis provides analytical expressions for packet delivery ratio. Considerable improvement can be observed compared to a channel-state-oblivious policy. This motivates us to define a channel-state-dependent potential function in a general network context. Simulations show that for a relatively slowly changing wireless network, our approach can provide up to 20% better performance than the commonly- used shortest-hop-count-based routing.

Lamb wave based identification and parameter estimation of corrosion in metallic plate structure using a circular PWAS array

A circular array of Piezoelectric Wafer Active Sensor (PWAS) has been employed to detect surface damages like corrosion using lamb waves. The array consists of a number of small PWASs of 10 mm diameter and 1 mm thickness. The advantage of a circular array is its compact arrangement and large area of coverage for monitoring with small area of physical access. Growth of corrosion is monitored in a laboratory-scale set-up using the PWAS array and the nature of reflected and transmitted Lamb wave patterns due to corrosion is investigated. The wavelet time-frequency maps of the sensor signals are employed and a damage index is plotted against the damage parameters and varying frequency of the actuation signal (a windowed sine signal). The variation of wavelet coefficient for different growth of corrosion is studied. Wavelet coefficient as function of time gives an insight into the effect of corrosion in time-frequency scale. We present here a method to eliminate the time scale effect which helps in identifying easily the signature of damage in the measured signals. The proposed method becomes useful in determining the approximate location of the corrosion with respect to the location of three neighboring sensors in the circular array. A cumulative damage index is computed for varying damage sizes and the results appear promising.

Viscoelastic phenomenology based structure assignment for closed-loop vibration control of a beam with sensors and actuators

In this paper we incorporate a novel approach to synthesize a class of closed-loop feedback control, based on the variational structure assignment. Properties of a viscoelastic system are used to design an active feedback controller for an undamped structural system with distributed sensor, actuator and controller. Wave dispersion properties of onedimensional beam system have been studied. Efficiency of the chosen viscoelastic model in enhancing damping and stability properties of one-dimensional viscoelastic bar have been analyzed. The variational structure is projected on a solution space of a closed-loop system involving a weakly damped structure with distributed sensor and actuator with controller. These assign the phenomenology based internal strain rate damping parameter of a viscoelastic system to the usual elastic structure but with active control. In the formulation a model of cantilever beam with non-collocated actuator and sensor has been considered. The formulation leads to the matrix identification problem of two dynamic stiffness matrices. The method has been simplified to obtain control system gains for the free vibration control of a cantilever beam system with collocated actuator-sensor, using quadratic optimal control and pole-placement methods.

Distributed Source Coding for Sensor Data Model and Estimation of Cluster Head Errors Using Bayesian and K-Near Neighborhood Classifiers in Deployment of Dense Wireless Sensor Networks

The lifetime calculation of large dense sensor networks with fixed energy resources and the remaining residual energy have shown that for a constant energy resource in a sensor network the fault rate at the cluster head is network size invariant when using the network layer with no MAC losses.Even after increasing the battery capacities in the nodes the total lifetime does not increase after a max limit of 8 times. As this is a serious limitation lots of research has been done at the MAC layer which allows to adapt to the specific connectivity, traffic and channel polling needs for sensor networks. There have been lots of MAC protocols which allow to control the channel polling of new radios which are available to sensor nodes to communicate. This further reduces the communication overhead by idling and sleep scheduling thus extending the lifetime of the monitoring application. We address the two issues which effects the distributed characteristics and performance of connected MAC nodes. (1) To determine the theoretical minimum rate based on joint coding for a correlated data source at the singlehop, (2a) to estimate cluster head errors using Bayesian rule for routing using persistence clustering when node densities are the same and stored using prior probability at the network layer, (2b) to estimate the upper bound of routing errors when using passive clustering were the node densities at the multi-hop MACS are unknown and not stored at the multi-hop nodes a priori. In this paper we evaluate many MAC based sensor network protocols and study the effects on sensor network lifetime. A renewable energy MAC routing protocol is designed when the probabilities of active nodes are not known a priori. From theoretical derivations we show that for a Bayesian rule with known class densities of omega1, omega2 with expected error P* is bounded by max error rate of P=2P* for single-hop. We study the effects of energy losses using cross-layer simulation of - large sensor network MACS setup, the error rate which effect finding sufficient node densities to have reliable multi-hop communications due to unknown node densities. The simulation results show that even though the lifetime is comparable the expected Bayesian posterior probability error bound is close or higher than Pges2P*.

Connectivity-aware Routing in Sensor Networks

Sensor network applications such as environmental monitoring demand that the data collection process be carried out for the longest possible time. Our paper addresses this problem by presenting a routing scheme that ensures that the monitoring network remains connected and hence the live sensor nodes deliver data for a longer duration. We analyze the role of relay nodes (neighbours of the base-station) in maintaining network connectivity and present a routing strategy that, for a particular class of networks, approaches the optimal as the set of relay nodes becomes larger. We then use these findings to develop an appropriate distributed routing protocol using potential-based routing. The basic idea of potential-based routing is to define a (scalar) potential value at each node in the network and forward data to the neighbor with the highest potential. We propose a potential function and evaluate its performance through simulations. The results show that our approach performs better than the well known lifetime maximization policy proposed by Chang and Tassiulas (2004), as well as AODV [Adhoc on demand distance vector routing] proposed by Perkins (1997).

An Efficient Scheme for Establishing Pairwise Keys for Wireless Sensor Networks

This paper addresses the problem of secure path key establishment in wireless sensor networks that uses the random key pre-distribution technique. Inspired by the recent proxy-based scheme in the work of Ling and Znati (2005) and Li et al. (2005), we introduce a friend-based scheme for establishing pairwise keys securely. We show that the chances of finding friends in a neighbourhood are considerably more than that of finding proxies, leading to lower communication overhead. Further, we prove that the friend-based scheme performs better than the proxy-based scheme both in terms of resilience against node capture as well as in energy consumption for pairwise key establishment, making our scheme more feasible.

Ultrasonic Lamb wave based monitoring of corrosion type of damage in plate using a circular array of piezoelectric transducers

In this paper we propose a concept and report experimental results based on a circular array of Piezoelectric Wafer Active Sensors (PWASs) for rapid localization and parametric identification of corrosion type damage in metallic plates. Implementation of this circular array of PWASs combines the use of ultrasonic Lamb wave propagation technique and an algorithm based on symmetry breaking in the signal pattern to locate and monitor the growth of a corrosion pit on a metallic plate. Wavelet time-frequency maps of the sensor signals are employed to obtain an insight regarding the effect of corrosion growth on the Lamb wave transmission in time-frequency scale. We present here a method to eliminate the time scale, which helps in identifying easily the signature of damage in the measured signals. The proposed method becomes useful in determining the approximate location of the damage with respect to the location of three neighboring sensors in the circular array. A cumulative damage index is computed from the wavelet coefficients for varying damage sizes and the results appear promising. Damage index is plotted against the damage parameters for frequency sweep of the excitation signal (a windowed sine signal). Results of corrosion damage are compared with circular holes of various sizes to demonstrate the applicability of present method to different types of damage. (C) 2011 Elsevier Ltd. All rights reserved.

Wireless Sensor Networks for Organizational Network Analysis

Since their emergence, wireless sensor networks (WSNs) have become increasingly popular in the pervasive computing industry. This is particularly true within the past five years, which has seen sensor networks being adapted for wide variety of applications. Most of these applications are restricted to ambience monitoring and military use, however, very few commercial sensor applications have been explored till date. For WSNs to be truly ubiquitous, many more commercial sensor applications are yet to be investigated. As an effort to probe for such an application, we explore the potential of using WSNs in the field of Organizational Network Analysis (ONA). In this short paper, we propose a WSN based framework for analyzing organizational networks. We describe the role of WSNs in learning relationships among the people of an organization and investigate the research challenges involved in realizing the proposed framework.

Health Monitoring Of Composite Structures Based On Acoustic Wave Sensing Using Fiber Optic Sensors

Structural Health Monitoring has gained wide acceptance in the recent past as a means to monitor a structure and provide an early warning of an unsafe condition using real-time data. Utilization of structurally integrated, distributed sensors to monitor the health of a structure through accurate interpretation of sensor signals and real-time data processing can greatly reduce the inspection burden. The rapid improvement of the Fiber Optic Sensor technology for strain, vibration, ultrasonic and acoustic emission measurements in recent times makes it feasible alternative to the traditional strain gauges, PVDF and conventional Piezoelectric sensors used for Non Destructive Evaluation (NDE) and Structural Health Monitoring (SHM). Optical fiber-based sensors offer advantages over conventional strain gauges, and PZT devices in terms of size, ease of embedment, immunity from electromagnetic interference (EMI) and potential for multiplexing a number of sensors. The objective of this paper is to demonstrate the acoustic wave sensing using Extrinsic Fabry-Perot Interferometric (EFPI) sensor on a GFRP composite laminates. For this purpose experiments have been carried out initially for strain measurement with Fiber Optic Sensors on GFRP laminates with intentionally introduced holes of different sizes as defects. The results obtained from these experiments are presented in this paper. Numerical modeling has been carried out to obtain the relationship between the defect size and strain.

Self Assessment-Based Decision Making for Multiagent Cooperative Search

This paper addresses a search problem with multiple limited capability search agents in a partially connected dynamical networked environment under different information structures. A self assessment-based decision-making scheme for multiple agents is proposed that uses a modified negotiation scheme with low communication overheads. The scheme has attractive features of fast decision-making and scalability to large number of agents without increasing the complexity of the algorithm. Two models of the self assessment schemes are developed to study the effect of increase in information exchange during decision-making. Some analytical results on the maximum number of self assessment cycles, effect of increasing communication range, completeness of the algorithm, lower bound and upper bound on the search time are also obtained. The performance of the various self assessment schemes in terms of total uncertainty reduction in the search region, using different information structures is studied. It is shown that the communication requirement for self assessment scheme is almost half of the negotiation schemes and its performance is close to the optimal solution. Comparisons with different sequential search schemes are also carried out. Note to Practitioners-In the futuristic military and civilian applications such as search and rescue, surveillance, patrol, oil spill, etc., a swarm of UAVs can be deployed to carry out the mission for information collection. These UAVs have limited sensor and communication ranges. In order to enhance the performance of the mission and to complete the mission quickly, cooperation between UAVs is important. Designing cooperative search strategies for multiple UAVs with these constraints is a difficult task. Apart from this, another requirement in the hostile territory is to minimize communication while making decisions. This adds further complexity to the decision-making algorithms. In this paper, a self-assessment-based decision-making scheme, for multiple UAVs performing a search mission, is proposed. The agents make their decisions based on the information acquired through their sensors and by cooperation with neighbors. The complexity of the decision-making scheme is very low. It can arrive at decisions fast with low communication overheads, while accommodating various information structures used for increasing the fidelity of the uncertainty maps. Theoretical results proving completeness of the algorithm and the lower and upper bounds on the search time are also provided.

Discrimination of Nuclear Grade Steel Samples Subjected to Different Heat Treatment Procedures Based on Acoustic Emission (AE) Data Profiling at Crack Initiation

The present work is an attempt to study crack initiation in nuclear grade, 9Cr-1Mo ferritic steel using AE as an online NDE tool. Laboratory experiments were conducted on 5 heat treated Compact Tension (CT) specimens made out of nuclear grade 9Cr-1Mo ferritic steel by subjecting them to cyclic tensile load. The CT Specimens were of 12.5 mm thickness. The Acoustic emission test system was setup to acquire the data continuously during the test by mounting AE sensor on one of the surfaces of the specimen. This was done to characterize AE data pertaining to crack initiation and then discriminate the samples in terms of their heat treatment processes based on AE data. The AE signatures at crack initiation could conclusively bring to fore the heat treatment distinction on a sample to sample basis in a qualitative sense.Thus, the results obtained through these investigations establish a step forward in utilizing AE technique as an on-line measurement tool for accurate detection and understanding of crack initiation and its profile in 9Cr-1Mo nuclear grade steel subjected to different processes of heat treatment.

Swarm intelligence algorithms for integrated optimization of piezoelectric actuator and sensor placement and feedback gains

Swarm intelligence algorithms are applied for optimal control of flexible smart structures bonded with piezoelectric actuators and sensors. The optimal locations of actuators/sensors and feedback gain are obtained by maximizing the energy dissipated by the feedback control system. We provide a mathematical proof that this system is uncontrollable if the actuators and sensors are placed at the nodal points of the mode shapes. The optimal locations of actuators/sensors and feedback gain represent a constrained non-linear optimization problem. This problem is converted to an unconstrained optimization problem by using penalty functions. Two swarm intelligence algorithms, namely, Artificial bee colony (ABC) and glowworm swarm optimization (GSO) algorithms, are considered to obtain the optimal solution. In earlier published research, a cantilever beam with one and two collocated actuator(s)/sensor(s) was considered and the numerical results were obtained by using genetic algorithm and gradient based optimization methods. We consider the same problem and present the results obtained by using the swarm intelligence algorithms ABC and GSO. An extension of this cantilever beam problem with five collocated actuators/sensors is considered and the numerical results obtained by using the ABC and GSO algorithms are presented. The effect of increasing the number of design variables (locations of actuators and sensors and gain) on the optimization process is investigated. It is shown that the ABC and GSO algorithms are robust and are good choices for the optimization of smart structures.

Subspace-based DOA estimation using Fractional Lower Order statistics

Direction Of Arrival (DOA) estimation, using a sensor array, in the presence of non-Gaussian noise using Fractional Lower-Order Moments (FLOM)matrices is studied. In this paper, a new FLOM based technique using the Fractional Lower Order Infinity Norm based Covariance (FLIC) Matrix is proposed. The bounded property and the low-rank subspace structure of the FLIC matrix is derived. Performance of FLIC based DOA estimation using MUSIC, ESPRIT, is shown to be better than other FLOM based methods.