Doe Nnsa Proposal

8/7/2019 Doe Nnsa Proposal

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Research and Education Program Proposal

Detection and Sensing of Environmental and Chemical Substancesusing

Ad-hoc Wireless Sensor Networks

Sponsored by:

U.S. Department of EnergyNational Nuclear Security Agency

Submitted by:

Southern University Department of Energy Massie Chair of ExcellenceProgram

Technical Contacts:

Dr. Ernest L. Walker, Principal Investigator Dr. PatrickCarriere, Massie Chair

Tel: 225-771-4023 Tel: 225-771-5292Fax: 225-775-9828 Fax: [email protected] [email protected]

Administrative Contact: AuthorizingOfficer:

Dr. Habib Mohamadian Dr. MildredSmalleyDean, College of Engineering Vice Chancellor,Research Tel: 225-771-5290 Tel: 225-73890Fax. 225-772-5721 Fax. 225-771-3361


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The Massie Chair of Excellence Program at Southern University proposes a multidisciplinary

research and education program focused in the detection and sensing of environmental and

chemical substances using Ad-hoc Wireless Sensor Networks (AWSN). The program will be housed in a 112,000 Sq. Ft. building, with state-of-the-art classroom and laboratory

facilities, within the College of Engineering. The program has two primary goals: 1) to

conduct research in areas that are pivotal to the development of technologies that willcontribute to the realization of AWSN which will significantly enhance our nations defense

capability as well as the quality of life for its citizens; and 2) to train students in the

development and use of these technologies to assure the sustainability of these efforts intothe future. The objectives for the first five years of the operation of the program are were to:

1) to conduct research in areas that will contribute to the removal of current barriers to

realizing broad application of AWSN; to include, sensing, data fusion, and communications

and networking; 2) to develop sensing system prototypes to demonstrate proof of conceptfor future implementation of autonomous nano-scale ad-hoc wireless sensing systems for

both military and civilian applications; to include, new or improved, multisensor technology,

data fusion algorithms, wire wireless network protcols and architectures; 3) to train graduate

students in the theory and practice of realizing AWSN through the conduct of research insupport of theses and dissertations and for the development of new undergraduate and

graduate courses; and 4) to train undergraduate students in the practice of realizing AWSNsystems through undergraduate research assistantships and senior (capstone) design

experiences. Since the development of nano-scale wireless sensor systems will require the

integration of: an array of sensors, each with a unique sensing task (multisensors); a

distillation of the information gathered by the sensor array (data fusion), and securecommunication facilities used to exchange information between sensor nodes1 (ad-hoc

wireless network) must be unified into a single autonomous power controlled package that

will, depending upon the application, range in volume from hundreds to thousands of cubicnanometers. Accordingly, due to varying materials and fabrication techniques necessary for

success in such an endeavor, these subsystems will be investigated and developed as a single

system. The objectives for the second five years is focused on improving performance ofremote sensing systems through development of: 1) sophisticated devices for fast and accurate

sensing; 2) optimal control of unmanned airborne vehicle (UAV) trajectories for data acquisition; 3)

and develop high performance novel communication networking. Motivated by the fact that the

overall performance of sensor systems depends critically on the accuracy and sensitivity of

individual sensors, we propose to design, fabricate and characterize several sensors and incorporate

them into communication systems. Given that modern remote sensing systems heavily employ

mobile sensor carriers, such as UAVs , it is crucial to control the trajectories of them in order to

achieve the best performance of acquiring accurate data. For this purpose, we propose a new

approach for designing optimal trajectories of UAVs. Once data is available from the sensors, the

next challenging task is to efficiently and reliably transmit the data to remote locations. To address

the issue of increasing amounts of data (such as image, video), multipath and fading effects, noiseand the limited spectrum in wireless communications of remote sensing, we propose a novel space-

time coding and multiple input multiple output (MIMO) communication techniques which areespecially suitable for current remote sensing systems.

1 A sensing system with the ability to exchange information with a like or similarconfiguration

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1.0 GOALS AND OBJECTIVES

The Southern University Massie Chair of Excellence Program proposes toconduct a research and education program in the area of Ad hoc WirelessNetworking and Sensing (AWNS), as applied to the detection and sensing ofenvironmental and chemical substances. The goals for the program are: 1) tocontribute to the innovation of ad-hoc wireless sensor network technologiesto enhance our nations security and defense capability, as well as thequality of life for its citizens; and 2) to train students in the development anduse of these technologies to assure the sustainability of these efforts into thefuture. The objectives for the first five years are: 1) to conduct research inareas that will contribute to the removal of current barriers to realizing broadapplication of AWSN; to include, data fusion, communications and

networking, and sensors; 2) to develop AWSN system prototypes todemonstrate proof of concept; to include, new or improved, fusionalgorithms, sensor fabrication techniques, and secure and efficient wirelesscommunications facilities on a common 3) to train graduate students in thetheory and practice of realizing AWSN through the conduct of research insupport of theses and dissertations and for the development of newundergraduate and graduate courses; and 4) to train undergraduatestudents in the practice of realizing AWSN systems through the sponsorshipof undergraduate research assistantships and senior (capstone) designexperiences. It should be noted that the above stated goals and objectivesare supportive of the goals for the National Nuclear Security Administration

(NNSA), an agency within the U. S. Department of Energy. In particular, thisproposal addresses goals on Safe Guards and Securityand Nonproliferation& Verification R&D, as set forth in the NNSA Strategic Plan1. Accordingly, incarrying out the goals and objectives of the proposed research andeducation program, collaborations with NNSA organizations which havemissions consistent with our program efforts, will be sought. Theseorganizations include: Lawrence Livermore National Laboratory, which is1 The NNSA Strategic can be found at http://www.nnsa.doe.gov

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tasked with Proliferation Detection System development as well as Counter-proliferation Analysis; and Sandia National Laboratory, which is task withBiological Weapons Non-proliferation. It is envisioned that, to the extentpossible, both faculty and students associated with this program willexperience periodic fellowships and internships with these organizations.

2.0 MOTIVATION

Since 9/11, security technologies are receiving heightened attention byresearchers, government agencies, military and manufacturers to helpprevent or mitigate another terrorist attack within our country. Technologiesin various stages of development range from more sensitive and versatiledetectors for biological, chemical, and radiological agents to newdiagnostics, vaccines, and therapeutics against anthrax, smallpox, and otherpotential bio-terror agents. Many of these technologies, particularly thosedesigned to guard against an attack on the nation's infrastructure, have

either already been, or are being, developed within the private sector. Thethree key end-user groups are identified as users, or potential users, ofchemical and biological detection technologies. The prime end-user is themilitary. The second group is civil defense and law enforcement agencies, orfirst responders. These end-users are present at state and local levels andare tasked with protecting civilians in the event of a wider exposure.Demand in this sector is expected to rise; due to the terrorist actions againstthe United States and in other countries. The third group of end-users is thecivilian sector. These are primarily large companies desiring to protectemployees; companies involved in chemical demilitarization work andgovernment agencies without first responder duties. Although demand is

expected to increase within the civilian sector, as well, some companies maystill consider the high cost of the devices, translating into the cost-to-benefitratio, as too high. One of the main challenges for the private and publicsectors is that most bio-detection programs are still in the research anddevelopment phase. Accordingly, the DoE Massie Chair of ExcellenceProgram at Southern University proposes to conduct a research anddevelopment and education program over the next five years that willcontribute to the nations effectiveness in realizing highly responsive andpervasive systems of protection for its citizens.

3.0 STATEMENT OF WORK

The Southern University Massie Chair of Excellence Program (SUMCEP)proposes to conduct research and development and education and outreachprograms in the Detection and Sensing of Environmental and ChemicalSubstances using Ad-hoc Wireless Sensor Networks. The research will beconducted within the facilities of the College of Engineering at SouthernUniversity, Baton Rouge, Louisiana. The College is largely housed within theP.B.S. Pinchback Building, a new 112,000 Sq. Ft. building with state-of-the-art

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classroom and laboratory facilities, including the Massie Chair of ExcellenceLaboratory within the Department of Civil Environmental Engineering; as wellas the Wireless Networks & Sensors and Electronic Materials Processinglaboratories, within the Department of Electrical Engineering.

3.1 Research and Development3.1.1 Data Fusion

Sensor based data fusion is an emerging technology applied to areas such asautomated target recognition, battlefield surveillance, guidance and controlof autonomous vehicles, monitoring of chemical and biological agents,complex machinery, medical diagnosis, smart buildings and countless othersuch applications. The following are specific techniques that will beemployed in our data fusion investigation:

Association metrics (AM) - a general term for assigning a numberrepresenting a degree of likeness between data sets. AM proceduresinclude: Principal Component Analysis (PCA), a multivariate procedurewhich rotates data such that maximum variabilities are projected ontoaxes;

Neural Networks (NN) - a network of many simple units ("processors "),each possibly having a small amount of local memory; and Fuzzy Logic(FL), a multi-valued logic that allows intermediate values to be definedbetween conventional evaluations; such as, yes/no, true/false,black/white, etc;

Distributive Processing raw sensor signals are sampled and processed

and individual relevant summary statistics are extracted from the rawsignal, stored locally in individual nodes and may be transmitted to othernodes upon request;

Goal-oriented, On-demand, Processing To conserve energy, each sensornode only performs signal processing tasks that are relevant to thecurrent query, or in the absence of a query, retreats into a standby mode;i.e. a sensor does not automatically publish extracted information --- itforwards such information only when needed;

Information Fusion used to infer global information over a certain space-time region from local observations, Collaborative Signal Processing (CSP)must facilitate efficient, hierarchical information fusion --- progressivelylower bandwidth information must be shared between nodes overprogressively large regions;

Multi-resolution Processing depending on the nature of the query, someCSP tasks may require higher spatial resolution involving a finer samplingof sensor nodes, or higher temporal resolution involving higher samplingrates. Space-time processing using wavelets may also be fruitfullyexploited in our investigation.

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3.1.2 Wireless Communications and Networking

Research activities in the areas of networking and communication will focuson the development of new, and or, improved approaches to accomplish

more effective techniques to enable network discovery, network control androuting, network security, and tasking and querying in ad hoc wirelessnetworks. In addition, since the effectiveness of some of the abovetechniques will be strongly dependent upon the implementation of thephysical transmission facility employed; accordingly, a bottoms upapproach will be employed in the investigation of the following processesdefined below.

Physical Channel Processes - We will investigate, using both computationa theoretical techniques, the viability of Variable Spreading Factor ZeroCorrelation Zone Code Division Multiple Access (VSF-ZCZ CDMA)

sequences, as a method of establishing a secure and agile multiuserwireless channel. Network Discovery Processes We will investigate, by both computation a

theoretical techniques, network discovery processes, one of which will bea multiuser variant of the collision avoidance carrier sense multipleaccess (CA-CSMA) access method.

Medium Access Processes We will investigate, by both computation atheoretical methods, medium access methods for gaining access to thetransmission medium for the exchange of data, one of which will be amultiuser variant of the token-passing access method.

Higher Level Processes Novel processes at the higher levels; i.e., linkand network (packet), will also be investigated using both computation atheoretical methods. The primary focus for these processes will be toprovide an effective transition between the dynamic character of thephysical and medium access processes to a more stable, but responsive,interface to the end-user, via appropriate transport and applicationprocesses.

3.1.3 Sensors

Our investigations for sensors in an AWSN environment will be directedtoward two types of sensing technologies: 1) a three-dimensional millimetersized multisensor chip, mainly made up of micro-sensors, a nanobattery, andsmart interface(s); such as, microprocessors and A/D converters; 2) waterand airborne biological and chemical sensors. For the proposed designs, wewill be developing the following sensing structures:3.1.3.1 Multisensor Chip

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The design and fabrication of a PZT (plumbum (lead) zirconatetitanate) film pressure sensor consisting of a PZT (0.5 m) and LSMO(0.1 m) film heterostructure.

The design and fabrication of a PZT film pressure sensor, designed tobe used as an acoustic sensor by measuring acoustic emission (AE)

wave propagation through PZT films. The design and fabrication of an infrared-based optical micro-sensor. These devices will be fabricated using MEMS-based processingmethods.

The design and fabrication of a temperature sensor will beaccomplished by using platinum thin films prepared on (5000) SiO2/Sisubstrates by DC magnetron sputtering.

The design and fabrication of a vibration sensor will consist of an arrayof mechanical oscillators. This piezoresistive vibration sensor employssilicon cantilevers with their natural frequencies placed adjacently andhaving lengths of about 600-m.

The design and fabrication of a chemical sensor will be accomplishedvia nanoparticle seeds of iron, cobalt, nickel, copper and silver and areprocessed by vapor deposition on prefabricated micro hotplatesfollowed by annealing at 500C prior to self-aligned SnO2 deposition.

The design and fabrication of the interfaces for this multi-sensor will beaddressable, programmable, self-testing, and compatible with abidirectional digital bus. The important interfaces that we will use are:sensor bus; mps; communication interface; microprocessor interface;ADC; MUX; frequency to digital converter; digital register; and addressdetector.

The design and fabrication of a built-in multisensor lithium-ion

nanobattery. The anode is a multi-walled carbon nanotube arrayelectrode. The cathode is Sulfur-Carbon nanocomposite with elementalsulfur incorporated in porous carbon.

The design and fabrication of the packaging consisting of: the sensorsusing eutectic bonding; electrostatic bonding; and low temperatureglass bonding. For holes and micro-chamber fabrication we will beusing methods like laser drilling, and ion beam milling.

3.1.3.2 Water and Airborne Biological and Chemical Sensors

The development and characterization of sensors that will detect toxic

chemical gases/vapors The development and chracterization of an immunosensor, employing

the principles of amperometry, volatametry, fluorometry, andpiezoelectricity, for detection of toxins (simulates of toxins such asBotulinum toxin and Ricin) and bacteria (heat sterilized bacteria suchas E.coli, Salmonella, Pathogenic Vibrios, and Lysteria).

3.2 Education and Outreach

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Currently, the College of Engineering at Southern University has a Master ofEngineering with Option in environmental engineering and a civil engineeringprogram with concentration in environmental engineering. In addition, theCollege has three state-of-the-art environmental laboratories: 1) water

chemistry; 2) analytical; 3) environmental testing labs that are available toconduct research and training. These labs are used to provide services andtraining to Southern University and community based environmentalprograms. The goals of the environmental labs are as follows:

To provide a focal point for all environmental research for theuniversity; To support various environmental curricula; To become a licensed environmental lab recognized on the state,local and national level; To provide services for community based environmentalprograms.

The Massie Program at Southern will engage in curriculum developmentactivities that further the aims of increasing the number of minorities trainedin environmental restoration technology and waste management. Near-termcurriculum development activities will include the definition, planning andspecification of educational goals and objectives that are consistent withDOE NNSAs environmental restoration and waste management plans.

3.2.1 K-12 Students The Massie Program will assist and provide resources to elementary,

middle, and high schools to infuse environmental issues in sciencecourses. In collaboration with middle/high school educators, Massie Program

researchers will annually formulate & contribute environmental highschool projects and will provide support for materials and supplies.

The Massie Program will regularly supervise student teams in themonths leading into the local, regional and ultimately the Statecompetition and participate as judges for the competition asneeded.

3.2.2 Undergraduate Students Massie Scholars: The Massie Program will support undergraduate

students, namely Massie Scholars, who will conduct research and othermentoring activities for K-12 students under the supervision of facultymembers and graduate students. Massie researchers are also committedto involving undergraduates in ongoing environmental research.

Capstone Design: Massie researchers will partner with private and publicaffiliates to identify, propose, financially support and advise designprojects of a scale and scope appropriate for the Capstone Design on

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environmental restoration technology and waste management. TheMassie Program will support a selection of student teams enteringNational Design Competitions with projects emphasizing on environmentalrestoration technology and waste management.

3.2.3 Graduate Students

Massie researchers will recruit and support qualified graduate studentcandidates, to carry out the core research in support of theses anddissertations

Course materials in environmental restoration technology and wastemanagement will be developed and will part of the elective offerings inour graduate programs, a selected number of which will be developed fordistance learning offerings.

3.2.3 General Public The Massie Program will make the public aware of existing and emerging

environmental restoration technology and waste management. In

facilitating dissemination and public outreach, activities, calls forparticipation and achievements will be regularly announced throughnewsletters, targeted mailings, and the Massie Program web site.

The Massie Program will periodically conduct workshops and seminars onemerging environmental restoration technology and waste management,via local and distant learning facilities. All educational materials, lessonplans, videos, and modules developed will be made available toattendees.

The Massie Program at Southern will provide continuing education coursesfor hazardous materials and waste workers and technologists; communityand professional policy makers and opinion-makers; the news media;public action groups; non-profit organizations and foundation personnel;legislators; members of the judiciary; law enforcement personnel; medicalpersonnel; pre-college teachers; faculty and staff members of highereducation institutions

4.0 APPROACH

4.1 Research and Development

4.1.1 Data Fusion

Data fusion is the process of combining data and knowledge from differentsources with the aim of maximizing the useful information content. Itimproves reliability or discriminate capability while offering the opportunityto minimize the data retained. In the not too distant future, advances inprocessor, memory and radio technologies will enable small andinexspensive sensor nodes capable of wireless communication andsignificant computation. The addition of sensing capability to such devices

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will make distributed microsensing, an activity in which a collection of nodescoordinated to achieve a large sensing task, possible. This is so-calledmultisensor data fusion (also referenced as collaborative signal andinformation processing). Such technology can revolutionize informationgathering and processing in many situations. Multisensor data fusion is an

emerging technology applied to the areas such as automated targetrecognition, battlefield surveillance, guidance and control of autonomousvehicles, monitoring of complex machinery, medical diagnosis, and smartbuildings. Techniques for multisensor data fusion are drawn from a widerange of areas including artificial intelligence, pattern recognition, statisticalestimation, and control theory. Technology aspects of data fusion includedetection (or decision) theory, estimation theory, digital signal processing,and parametric and non-parametric data fusion techniques (including fuzzylogic, neural networks, artificial intelligence, pattern recognition, statisticalestimation, and control theory, and voting logic).Technology aspects of data fusion include: (1) detection (or decision) theory:

probabilistic data fusion (probabilistic method, information measures, andalternatives to probability); (2) estimation theory: the Kalman filter, themulti-sensor Kalman filter and track -to-track fusion, nonlinear data fusionmethods and multi-sensor multi-target data association; (3) special datafusion architectures for distributed and decentralized data fusion system andothers; such as, digital signal processing, parametric and non-parametricdata fusion techniques (including fuzzy logic, neural networks, artificialintelligence, pattern recognition, statistical estimation, and control theory,and voting logic). The following are specific techniques that will be used inour data fusion investigation. Association metrics is a general term forassigning a number representing a degree of likeness in data. The

association metric can measure either the amount to which two pieces ofdata are alike or the amount two components of the data are alike across alldata sets. Association metrics are used to gauge the overall structure of datasets and to provide information on individual data points within a data set.There are many different ways of defining association metrics, depending onthe structure of the data and the nature of the supposed likeness betweendata or its components; for details, see [12]. Principal Component Analysis(PCA) is a multivariate procedure that rotates data such that maximumvariabilities are projected onto axes. Essentially, a set of correlated variablesare transformed into a set of uncorrelated variables which are ordered byreducing variability. The uncorrelated variables are linear combinations of

the original variables, and the last of these variables can be removed withminimum loss of real data. The main use of PCA is to reduce thedimensionality of a data set while retaining as much information as ispossible. It computes a compact and optimal description of the data set. Thefirst principal component is the combination of variables that explains thegreatest amount of variation. The second principal component defines thenext largest amount of variation and is independent to the first principalcomponent. There can be as many possible principal components as there

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are variables. Neural Network (NN) is a network of many simple processors("units"), each possibly having a small amount of local memory. The unitsare connected by communication channels ("connections") that usually carrynumeric (as opposed to symbolic) data, encoded by any of various means.The units operate only on their local data and on the inputs they receive via

the connections. The restriction to local operations is often relaxed duringtraining. Some NNs are models of biological neural networks and some arenot; but historically, much of the inspiration for the field of NNs came fromthe desire to produce artificial systems capable of sophisticated, perhaps"intelligent", computations similar to those the human brain routinelyperforms, and thereby possibly to enhance our understanding of the humanbrain. Most NNs have some sort of "training" rule whereby the weights ofconnections are adjusted on the basis of data. In other words, NNs "learn"from examples (as children learn to recognize dogs from examples of dogs)and exhibit some capability for generalization beyond the training data. NNsnormally have great potential for parallelism, since the computations of the

components are largely independent of each other. Some people regardmassive parallelism and high connectivity to be defining characteristics ofNNs, but such requirements rule out various simple models, such as simplelinear regression (a minimal feed forward net with only two units plus bias),which are usefully regarded as special cases of NNs. In principle, NNs cancompute any computable function, i.e., they can do everything a normaldigital computer can do, or perhaps even more, under some assumptions ofdoubtful practicality. In practice, NNs are especially useful for classificationand function approximation/mapping problems which are tolerant of someimprecision, which have lots of training data available, but to which hard andfast rules (such as those that might be used in an expert system) cannot

easily be applied. Almost any finite-dimensional vector function on acompact set can be approximated to arbitrary precision by feed forward NNs(which are the type most often used in practical applications) if you haveenough data and enough computing resources. Clustering is the process ofgrouping together similar data items. Numerically, this is traditionally done inone of two ways. Hierarchical clustering proceeds from a provisional initialclustering, and iteratively merges and/or splits clusters until a requireddegree of similarity holds for the elements of the clusters. There are avariety of rules for deciding which clusters are merged/split and how.Partitional clustering attempts to cluster the set directly, in a manner thatdepends on a set of parameters. These parameters are then adjusted to

optimally satisfy a chosen criterion of separation and compactness ofclusters. There are, in each of the two approaches, a great number ofpossible implementations. This reflects the lack of a definitive meaning of acluster. Just as there are many lines we could fit two a two-dimensional set ofpoints (and we will typically choose one, say the least-squares fit, using ourjudgment) so there will be many possible clusterings of data. Fuzzy Logic isbasically a multivalued logic that allows intermediate values to be definedbetween conventional evaluations like yes/no, true/false, black/white, etc.

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Fuzzy logic is a superset of conventional (Boolean) logic that has beenextended to handle the concept of partial truth - truth values between"completely true" and "completely false". Fuzzy logic is a way of interfacinginherently analog processes that move through a continuous range of values,to a digital computer, that likes to see things as well-defined discrete

numeric values. Furthermore, fuzzy logic is well suited to low-costimplementations based on cheap sensors, low-resolution analog-to-digitalconverters, and 4-bit or 8-bit one-chip microcontroller chips. Such systemscan be easily upgraded by adding new rules to improve performance or addnew features. In many cases, fuzzy control can be used to improve existingtraditional controller systems by adding an extra layer of intelligence to thecurrent control method.

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The technical approaches for data fusion are depended on the ac hoc(sensing) networks adopted for (wireless) communication, but powerconsumption is a critical consideration in a wireless sensor network. Thelimited amount of energy stored at each node must support multiplefunctions, including sensor operations, on-board signal processing, and

communication with neighboring nodes. Thus, one must consider power-efficient sensing modalities, low sampling rates, low-power signalprocessing algorithms, and efficient communication protocols toexchange information among nodes. To facilitate monitoring of a sensorfield, including detection, classification, identification, and tracking oftargets, global information in both space and time must be collected andanalyzed over a specified space-time region. However, individual nodesonly provide spatially local information. Furthermore, due to powerlimitation, temporal processing is feasible only over limited time periods.This necessitates collaborative signal processing (CSP) between nodestoprocess the space-time signal. Center activities relating to data fusion will

focus on the development of new and or improved approaches toaccomplish more effective algorithms for (decentralized) data fusion withfollowing desirable features: Distributive processing Raw signals aresampled and processed at individual nodes but are not directlycommunicated over the wireless channel. Instead, each node extractsrelevant summary statistics from the raw signal, which are typically ofsmaller size. The summary statistics are stored locally in individual nodesand may be transmitted to other nodes upon request. Goal-oriented, on-demand processing To conserve energy, each node only performssignal processing tasks that are relevant to the current query. In theabsence of a query, each node retreats into a standby mode to minimize

energy consumption. Similarly, a sensor node does not automaticallypublish extracted information --- it forwards such information only whenneeded. Information fusion To infer global information over a certainspace-time region from local observations, CSP must facilitate efficient,hierarchical information fusion --- progressively lower bandwidthinformation must be shared between nodes over progressively largeregions. For example, (high bandwidth) time series data may beexchanged between neighboring nodes for classification purposes.However, lower bandwidth CPA (closest point of approach) data may beexchanged between more distant nodes for tracking purposes. Multi-resolution processing Depending on the nature of the query, some CSP

tasks may require higher spatial resolution involving a finer sampling ofsensor nodes, or higher temporal resolution involving higher samplingrates. For example, reliable detection may be achievable with a relativelycoarse space-time resolution, whereas classification typically requiresprocessing at a higher resolution. Multi-resolution space-time processingusing wavelets may be fruitfully exploited in this research effort.

4.1.2 Wireless Communications and Networking

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4.1.2.1 Physical Processes2 - In order to mitigate some of the currentdifficulties associated with communications in an AWSN environmentinvolving physical processes, we propose to begin our investigations in thecommunication and networking area on a recently discovered spread

spectrum coding method which will be here called variable spreading factorzero correlation zone code division multiple access (VSF-ZCZ-CDMA) [17, 19].The motivation for this approach lies in the fact that a) these sequenceshave near ideal correlation characteristics within a symmetrical regionaround zero lags, called the zero correlation zone (ZCZ), which to asignificant extent, removes all multiple access interference (MAI) and far-near effects from the detection process, assuming the detection isaccomplished under quasi-synchronous conditions (within the ZCZ); b) thesize of the ZCZ can be easily adapted in response to time-varying channelcharacteristics; c) the lengths (spreading factors) of the coding sequencescan be easily adapted, in response to time-varying channel characteristics.

Prior work indicates significant performance improvement, over conventional(Walsh-Hadamard) sequences, in a mobile communications environment. Weare further motivated to investigate this approach because, due to thesignificantly smaller cell sizes for AWSN (tens of square meters), ascompared to cell sizes for mobile communications (tens of squarekilometers), resulting in smaller dynamic ranges for multipath and fadingeffects, significantly better performance is expected when ZCZ sequencesare employed in an AWSN environment. Additionally, this performanceimprovement is expected to be realized with relatively low complexityreceiving structures. In the following we provide background for our interestin VSF-ZCZ-CDMA coding for physical process realization.

Generally, in multiuser CDMA systems it is desirable to have a codingscheme that will provide pure orthogonality with respect to correlationcharacteristics of the coding sequences; i.e., the autocorrelation responsesshould have an impulsive response at zero lags, and zero responseelsewhere; and the cross-correlation responses would have zero response forall lags. These correlation characteristics would provide for very effectivemultiuser communications using either synchronous or asynchronousdetection. This level of performance is due to the fact that the main sourcesof impairment; i.e., multi-access interference (MAI) and the near-far problem(NFP), would be non-existent. Recently, researches have reported thediscovery of a class of zero correlation zone (ZCZ) sequences which can

achieve quasi-orthogonality and is part of a class of codes referred to asGeneralized Orthogonal Sequences (GOS) Fan [9] [19] [20]. These sequencesshow significant performance improvement over Walsh-Hardamardsequences in a mobile wireless environment [17]. In general, ZCZ codesequences have a continuous zero periodic cross-correlation function (CCF)

2 In this work, we have avoided using the traditional architectural terminology which refer tolayers, we use processes to emphasize a more contemporary approach to architecture,as it relates to ad-hoc wireless sensor networks.

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zone in its central portion, including the zero lags response. These sequencesalso have a continuous zero periodic auto-correlation function (ACF) zone inthe same lags region, except that at zero lags which has a normalizedresponse of 1. This feature will allow a CDMA system to be operated in quasi-synchronous mode, due to the fact that MAI and NFP will be significantly

reduced, if time delay variations within the system are limited to less thanthe ZCZ.

4.1.2.2 Medium Access Control Processes - Network discovery and mediumaccess processes for AWSN have be studied by many researchers [14, 15,16], employing both contention and non-contention techniques. However, forAWSN, which can have large numbers (tens hundreds) of sensor nodeswithin a cell, can make contention techniques very inefficient. For thisreason, the proposed research seeks to separate the discovery and mediumaccess processes. However, for AWSN, which can have a large number (tens hundreds) of sensor nodes within a given cell, can render contention

techniques very inefficient. The proposed research seeks to separate thediscovery and data exchange functions of the medium access controlprocess3. This approach is motivated by the assumption that for AWSN toachieve the highest data utilization and power efficiency possible under alltraffic mixes (discovery and data), medium access control methods must becapable of allocating the required mix of transmission resources,appropriately. Accordingly, the proposed network discovery process is amulti-user variant of collision avoidance carrier sense multiple access (CA-CSMA) method while the medium access process is a multi-user variant ofthe token-passing protocol. Accordingly, we propose that the discoveryprocess be allotted up to n, (where n is M>n1, n=1, is default) asynchronous

multi-user ZCZ-VSF-CDMA channels (sequences) and is adapted to theintensity of discovery arrivals. The medium access process, for datatransmission, consists of an M-n multi-user ZCZ-VSF-CDMA channels, whereM is the total number of ZCZ sequences in the code. The basis architectureconsists of the following: a) a Sensor Node, is a network node that collectsdata from sensors, processes (fuses) the collected data, and interchanges itwith neighboring sensor nodes inside, or outside its Cell; b) a Cell is acollection of sensor nodes, under the control of a super sensor node call theMonitor; c) a Monitor is a sensor node with added function for managingaccess and connection control within a given cell, or within nearest neighborcell (All sensor nodes are capable of being a Monitor, but only one Monitor is

active within a cell at any given time). The establishment of a monitor is partof the network discovery process.A summary of the network discovery process to be investigated is initiated:when a sensor node becomes active due to power-up, or wake-up (arisesfrom hibernation); when there is a loss or interruption of Monitor function3 Here we have used the word process to avoided the more conventional term layer to amore contemporaryview of describing this function in an AWSN environment.

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within a given cell, or within a nearest neighbor cell; or when a sensor nodemigrates into the domain of one other, or more, cells. A monitor isestablished via a claim monitor process (CMP); initiated under the followingconditions: when a monitor node is not identified during the networkdiscovery process (NDP); when a monitor node migrates into one other, or

more cells; or when a monitor become inactive (via power-down, hibernation,or degraded link performance). A summary of the medium access process tobe investigated is initiated when: a sensor node requests a channel (codesequence) assignment or permission to transmit data over an assignedchannel; a monitor wishes to respond to a channel assignment request, totransmit over an assigned channel, discover cell connectivity, or to exchangenetwork statistics with monitors from neighboring cells. The higher levelprocesses; i.e., link and network (packet) processes, will also beinvestigated. The primary focus for these processes will be to provide aneffective transition between the dynamic character of the physical andmedium access processes to the more stable, but responsive, interface to

the end-user, via appropriate transport and application processes.4.1.3 Sensors

Our investigations for sensor in an AWSN environment will be directedtoward a three-dimensional millimetersized multisensor chip. The chipincludes a pressure/acoustic micro sensor, an optical micro sensor, atemperature micro sensor, a vibration micro sensor, a chemical nano sensorand a nano-battery. Development of such micro sensors is to design andcarry out miniaturization and integration of several complex structures on asingle chip powered by a Li-ion battery. The present design approach will,

thus, be a three dimensional sub-millimeter sized multi sensor chip which willrespond to several different physical and chemical variables simultaneouslyand would be coupled with smart interfaces like microprocessors and A/DConverters to help simulate webs of sensors and networks for informationprocessing. These aspects are very important for stability and supportoperations as well as for development of anti-terrorism strategies. Thearchitecture of a Multi Sensor Chip (MSC) comprises of four subsystems: a) apower supply subsystem which consists of the battery and the dc-dcconverter which powers the rest of the system; b) a sensing subsystem thatlinks the node to the physical phenomena and consists of a group of micro ornano sensors; c) an analog to digital converter (ADC) which converts the

analog outputs of the sensors to digital data; and d) a computing subsystemconsisting of a microcontroller unit for processing the digital data.Sensor nodes are battery driven and hence they must have a lifetime on theorder of months to years without battery replacement or charging. Therehave been many recent efforts in the area of energy-aware communicationslike TRAMA (Traffic-Adaptive Media Access) protocol, FPS (Flexible PowerScheduling), Duranet, TinyOS, T-MAC, and S-MAC. Extensive literature reviewhas been done which will enable us to perform aggressive energy

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optimization [34-37], and optimization of architectural and algorithmicapproaches of the MSC [33, 38, 39]. There has also been extensive study ofareas like integrated multisensors for humidity, contaminationmeasurement, and habitat monitoring [40-44] which has helped us toproceed better with a well-structured design methodology. There have been

efforts in exploring the limits of power saving, but no significant work hasbeen done to secure the protocol against malicious attackers. We will try toaddress this security issue.A built-in lithium-ion battery will be provided for the multisensors. The anodeis a multi-walled carbon nanotube array electrode, since these electrodesexhibit high current density due to their high surface area and orderedelectrode configuration. The cathode is Sulfur-Carbon nanocomposite withelemental sulfur incorporated in porous carbon. Nanoporous dielectricmembranes made from anodically oxidized aluminum foil can be used forstoring the gel electrolyte (PDVF-HFP copolymer and nano-SiO2 powdermatrix containing a 70 wt% liquid electrolyte of PC-EC-DEC (1:4:5, v/v)

containing 1 M LiPF6) of the battery. The battery design is expected to yieldhigh current density (~500 mA/cm2) and high reversible capacity (~440mAh/g), despite being very small in size. The dc-dc converter will beresponsible for providing a constant supply voltage to the rest of the sensornode while utilizing the complete capacity of the battery. The efficiencyfactor associated with the converter plays a big role in determining batterylifetime [30]. A low efficiency factor leads to significant energy loss in theconverter, reducing the amount of energy available to other sensor nodecomponents. Hence we shall focus on achieving a high efficiency factor.Sensor transducers translate physical phenomena to electrical signals. Wewill develop a variety of sensors that respond to temperature, light intensity,

sound, pressure, vibration, and corrosion. For pressure/acoustic sensing wepropose a thin PZT (plumbum (lead) zirconate titanate) film pressure sensorconsisting of a PZT (0.5 m) and LSMO (0.1 m) film heterostructure. ThePZT is deposited by Sol-gel process or pulsed laser ablation of stoichiometricceramic targets PbZr0.52Ti0.48O3 and, Pt and Au electrode on the top andbottom of the PZT film, respectively. The Pt/PZT/Au thin-film capacitorexhibits a good piezoelectric constant, which is as high as 67 pC/N [24]. Theresolution of the thin PZT film pressure microsensor is about 1 mbar. PZT filmpressure sensor is also designed to be used as an acoustic sensor bymeasuring acoustic emission (AE) wave (SAW) propagation through PZT films[25]. An Infra red-based sensor is proposed as the optical microsensor. These

devices are fabricated using MEMS-based processing methods. An IR sensorhaving a 55-m square refraction mirror is built onto the silicon wafer.Infrared radiation emitted by the object reaches the wafer, and is convertedinto heat by the IR sensor. On application of heat, the sensor bimorphdeforms and expands, so that the refraction angle of the mirror changes isbased on heat intensity [26]. The sensing of temperature will beaccomplished by platinum thin films prepared on (5000) SiO2/Si substratesby DC magnetron sputtering. The Platinum Resistance Thermometer as a

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thermo-resistive device has excellent characteristics such as high accuracy,long-term stability, wide temperature range, good linearity and rapidresponse time [27]. A vibration sensor is proposed consisting of an array ofmechanical oscillators. This piezoresistive vibration sensor employs siliconcantilevers with their natural frequencies placed adjacently and having

lengths of about 50 600m [28]. Finally, the proposed chemical sensingapproach will consist ofnanoparticle seeds of iron, cobalt, nickel, copper andsilver will be processed by vapor deposition on prefabricated micro hotplatesfollowed by annealing at 500C prior to self-aligned SnO2 deposition.Significant control of SnO2 grain sizes, ranging between 20 and 121 nm, isachieved based on the seed-layer type. Smaller grain diameters result inhigh sensitivity in 90-ppm ethanol illustrating the benefits of nanoparticleseeding for chemical sensing [29]. A 10-bit data-acquisition system thatcombines a 5-channel multiplexer, high-bandwidth track/hold, and serialinterface with high conversion speed and ultra-low power consumption ADCwill be designed. This will convert the analog electrical signals to digital

signals coming from the output of five sensors (pressure/acoustic microsensor, optical micro sensor, temperature micro sensor, vibration microsensor, chemical sensor).MCU is responsible for providing intelligence to the sensor node, forcontrolling the sensors and for the execution of communication protocols andsignal processing algorithms on the gathered sensor data. The proposedMCU will be addressable, programmable, self-testing, and compatible with abidirectional digital sensor bus. The choice of MCU should be dictated by theapplication scenario in order to achieve a close match between theperformance level offered by the MCU and that demanded by theapplication. Further, MCUs usually support various operating modes,

including Active, Idle, and Sleep modes, for power management purposes.Each mode is characterized by a different amount of power consumption.Thus, the power consumption levels of the various modes, the transitioncosts, and the amount of time spent by the MCU in each mode all have asignificant bearing on the total energy consumption (battery lifetime) of thesensor node. Since we have studied the power-performance characteristicsof MCUs extensively by analyzing the several techniques that are availableto estimate the power consumption of these embedded processors [31],[32], we will make a good choice of the MCU appropriate for our proposedsystem.

4.2 Education and Outreach

The Massie Program at Southern will establish working partnerships amongits constituents including K-12 teachers, college students (undergraduateand graduate), researchers, and scientists. It will support a collection ofactivities that foster an environment where every participant becomes botha teacher/mentor and a student, and where teamwork is emphasized so thateveryone contributes and everyone learns about sensor based technologies.

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A website will be developed and built for the purpose of showcasing theresearch and education activities of the Southern University program. Thewebsite will be built and maintained by both undergraduate and graduateMassie Fellows, under the direction and oversight of Masse Researchers and

College of Engineering Information Technology Staff.

5.0 REFERENCES

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28. W. Benecke, L. Csepregi, A. Heuberger, K. Kuhl, H. Seidel, Afrequency-selective, piezoresistive silicon vibration sensor., Rec. of the 3rdInt. Conf. on Solid-State Sensors and Actuators, 1985, pp. 105-108.

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2001 ACMSIGCOMM Workshop on Data Communications in Latin Americaand the Caribbean, San Jose, Costa Rica, Apr. 2001.

42. A. El-Hoiydi. Aloha with preamble sampling for sporadic traffic in adhoc wireless sensor networks. In Proceedings of IEEE InternationalConference on Communications, New York, NY, USA, Apr. 2002.

43. Y. Xu, J. Heidemann, D. Estrin, Geography-informed energyconservation for ad hoc routing, MobiCom, 2001, Rome, Italy, pp. 70-84,July 2001.

44. Integrated Multisensors for Industrial Humidity, Measurement,Integrated Multisensors for Industrial Humidity Measurement, G.Brokmann, B. March, D. Rmhild and A. Steinke, CiS Institut frMikrosensorik gGmbH, D-99097 Erfurt, Germany, 2001.

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