M.S. Thesis Defense
Computer Science and Electrical Engineering
University of Maryland, Baltimore County

Fabrication and Characterization of a

Pd Nanowire-based Glucose Biofuel Cell

Kweku Amoah

10:30-12:30 Monday, 25 November 2013, ITE 346

The use of glucose as a biofuel has received a lot of attention in part due to the potential applications of such systems. In addition to the being a clean energy alternative, it provides a pathway for implantable microelectronic devices such as pacemakers to be powered by interstitial fluid and eliminate the need for batteries. Furthermore, using interstitial fluid as power sources will drastically reduce necessary invasive surgeries to replace batteries. Additionally, cost to such patients will be reduced while quality of life enhanced. The research presents a unique platform for harvesting energy from glucose. Using semiconductor cleanroom techniques, electrically conductive palladium nanowires are grown on anodized aluminum oxide (AAO) templates using silicon and glass as supporting substrates. Photolithography is used to create two non-continuous gold windows and contact pads on the substrates. AAO templates are attached to the two gold windows and palladium nanowires are electrochemically grown on the AAO templates. Glucose oxidase and catalase are immobilized on the anode and laccase on the cathode. In the presence of glucose, electrons are released that generate voltage and current. The current-voltage behavior of the fuel cell, as well as electrochemical properties, is characterized using standard performance metrics. In 0.5 moles per liter of glucose solution with a neutral pH of 7.3, the open circuit voltage obtained was 335 mV and the short circuit current of 6 µA to yield a maximum power output of 2.01µW.

Committee: Drs. Gymama Slaughter (Chair), Fow-Sen Choa and Joel Morris

Computer Science and Electrical Engineering
University of Maryland, Baltimore County

Ph.D. Dissertation Defense

Private Packet Filtering Searching for Sensitive Indicators
without Revealing the Indicators in Collaborative Environments

Michael John Oehler

10:30-12:30 Thursday, 21 November 2013, ITE 325

Private Packet Filtering (PPF) is a new capability that preserves the confidentiality of sensitive attack indicators, and retrieves network packets that match those indicators without revealing the matching packets. The capability is achieved through the definition of a high-level language, the definition of a conjunction operator that expands the breadth of the language, a simulation of the document detection and recovery rates of the output buffer, and through a description of applicable system facets. Fundamentally, PPF uses a private search mechanism that in turn relies on the (partial) homomorphic property of the Paillier cryptosystem. PPF is intended for use in a collaborative environment involving a cyber defender and a partner: The defender has access to a set of sensitive indicators, and is willing to share some of those indicators with the partner. The partner has access to network data, and is willing to share that access. Neither is willing to provide full access. Using the language, the defender creates an encrypted form of the sensitive indicators, and passes the encrypted indicators to the partner. The partner then uses the encrypted indicators to filter packets, and returns an encrypted packet capture file. The partner does not decrypt the indicators and cannot identify which packets matched. The defender decrypts, reassembles the matching packets, gains situational awareness, and notifies the partner of any malicious activity. In this sense, the defender reveals only the observed indicator and retains control of all other indicators. PPF allows both parties to gain situational awareness of malicious activity, and to retain control without exposing every indicator or all network data.

Committee: Dhananjay Phatak (chair), Michael Collins, Josiah Dykstra, Russell Fink, John Pinkston and Alan Sherman

Dissertation Defense

Design and Analysis of Underwater Acoustic
Networks with Reflected Links

Lloyd Emokpae

11:00am Tuesday, 12 November 2013, ITE 346, UMBC

Underwater acoustic networks have applications in environmental state monitoring, oceanic profile measurements, leak detection in oil fields, distributed surveillance, and navigation. For these applications, sets of nodes are employed to collaboratively monitor an area of interest and track certain events or phenomena. In addition, it is common to find autonomous underwater vehicles (AUVs) acting as mobile sensor nodes that perform search-and-rescue missions, reconnaissance in combat zones, and coastal patrol. These AUVs are to work cooperatively to achieve a desired goal and thus need to be able to, in an ad-hoc manner, establish and sustain communication links in order to ensure some desired level of quality of service. Therefore, each node is required to adapt to environmental changes and be able to overcome broken communication links caused by external noise affecting the communication channel due to node mobility. In addition, since radio waves are quickly absorbed in the water medium, it is common for most underwater applications to rely on acoustic (or sound) rather than radio channels for mid-to-long range communications. However, acoustic channels pose multiple challenging issues, most notably the high transmission delay due to slow signal propagation and the limited channel bandwidth due to high frequency attenuation. Moreover, the inhomogeneous property of the water medium affects the sound speed profile while the signal surface and bottom reflections leads to multipath effects.

In this dissertation, we address these networking challenges by developing protocols that take into consideration the underwater physical layer dynamics. We begin by introducing a novel surface-based reflection scheme (SBR), which takes advantage of the multipath effects of the acoustic channel. SBR works by using reflections from the water surface, and bottom, to establish non-line-of-sight (NLOS) communication links. SBR makes it possible to incorporate both line-of-sight (LOS) and NLOS links by utilizing directional antennas, which will boost the signal-to-noise ratio (SNR) at the receiver while promoting NLOS usage. In our model, we employ a directional underwater acoustic antenna composed of an array of hydrophones that can be summed up at various phases and amplitudes resulting in a beam-former. We have also adopted a practical multimodal directional transducer concept which generates both directional and omni-directional beam patterns by combining the fundamental vibration modes of a cylindrical acoustic radiator. This allows the transducer to be electrically controlled and steered by simply adjusting the electrical voltage weights. A prototype acoustic modem is then developed to utilize the multimodal directional transducer for both LOS and NLOS communication. The acoustic modem has also been used as a platform for empirically validating our SBR communication model in a tank and with empirical data.

Networking protocols have been developed to exploit the SBR communication model. These protocols include node discovery and localization, directional medium access control (D-MAC) and geographical routing. In node discovery and localization, each node will utilize SBR-based range measurements to its neighbors to determine their relative position. The D-MAC protocol utilizes directional antennas to increase the network throughput due to the spatial efficiency of the antenna model. In the proposed reflection-enabled directional MAC protocol (RED-MAC), each source node will be able to determine if an obstacle is blocking the LOS link to the destination and switch to the best NLOS link by utilizing surface/bottom reflections. Finally, we have developed a geographical routing algorithm which aims to establish the best stable route from a source node to a destination node. The optimized route is selected to achieve maximum network throughput. Extensive analysis of the network throughput when utilizing directional antennas is also presented to show the benefits of directional communication on the overall network throughput.

Committee: Mohamed Younis (Chair), Tulay Adali, Charles Laberge, Anupam Joshi, Lisa Marvel, Edward Hua

IEEE – Job Search Workshop

12:00-1:00 Monday, 11 November 2013, ITE LH 7

Join IEEE for a job search workshop. A Career Services’ expert will give a presentation tailored for STEM grad students. Learn about job search techniques that work best for those in a STEM major and start your search now.

It could take up to 9 months to find a job after graduation… Don’t wait until your last year to start looking for a job.

Kick start your job search with us, November 11th, at noon, in Lecture Hall 7. No matter where you are in your studies, it’s never too early to start job searching. Lunch will be served!

RSVP online.

M.S. Thesis Defense
Computer Science and Electrical Engineering
University of Maryland, Baltimore County

Fast Modular Exponentiation Using Residue Domain Representation:
A Hardware Reference Implementation and Analysis

Christopher D. Nguyen

12:00–2:00pm, Tuesday, 5 November 2013, ITE 228, UMBC

Using field-programmable gate arrays (FPGAs) we engineered and analyzed the first hardware implementation of Phatak’s reduced-precision residue number system (RP-RNS) to perform modular exponentiation.

Residue number systems (RNSs) provide an alternative representation to the binary system for performing integer arithmetic used in applications such as public-key cryptography and digital signal processing. They offer full parallel computation for addition, subtraction, and multiplication increasing performance from O(K) to O(lg K) for a K-bit number. However, base extension, division, and sign detection become harder operations.

RP-RNS is a new set of algorithms that uses approximation and a time-memory trade-off to address the hard operations. The partial reconstruction (PR) algorithm addresses base extension and the quotient-first scaling (QFS) algorithm addresses scaling. RP-RNS modular exponentiation uses the PR and QFS algorithms. RP-RNS improves performance of modular multiplication in an RNS with range [0, M-1] from the O((lg n)^2) delay of current systems (e.g. Cox-Rower) to a theoretical O(lg n) delay where n is the word-length of M.

Our implementation is based on Phatak’s description and recommended architecture diagrams. We found even low-end FPGAs can store over 30 channels of logic. Following the recommendation of parallel look-up table (LUT) access, we distributed the LUTs to be local to each channel. We found this recommendation applied to QFS exceeds the capacity of today’s high-capacity FPGAs (e.g. Xilinx Virtex-7) for modest 2,000-bit divisors. We propose several improvements to increase feasibility; one is to store the LUTs external to the FPGA, which would introduce a performance penalty per look-up.

Committee: Alan Sherman (chair), Dhananjay Phatak, Chintan Patel and
Ryan Robucci

PhD Defense

Visualizing Sequential Patterns in Large

Datasets Using Levels of Abstraction

Dana Wortman

11am – 2pm, Friday, 1 November 2013, ITE 325b

Student retention and success are important topics in all academic fields and institutions. Faculty seek to understand which topics, theories, or skills defeat students or require strengthening to promote success. Programs seek to understand how to better sequence courses to ensure students are prepared for requisite future courses. Institutions seek to understand how to intervene to promote retention and improve graduation rates. Unfortunately, most statistics gathered by Institutional Research efforts are limited to failure rates, enrollment rates, and graduation rates and do not often explore individual student performance. While these are often further analyzed by various student demographic attributes such as race and gender, these statistical methods alone are insufficient to understand student performance over time and sequential patterns of enrollment or success and failure. This research presents a method using multiple levels of abstraction to visualize performance patterns over time.

To visualize student enrollment and performance patterns, several issues must be addressed including sequential versus concurrent enrollment, spatial layout of course events, and performance over time. Another challenge addressed by this work is that of presenting sequences within the context of the entire program. To address these issues, multiple abstractions are combined in a multi-layered visualization that presents a high-level overview of students enrollment and performance patterns while retaining detailed information regarding individual student progress and performance as they advance through their courses.

The aggregated view represents the lowest level of abstraction, student enrollment and performance are aggregated into a graph structure, presenting patterns of movement throughout the program at the individual course level. The clustered view represents mined sequential patterns of enrollment and performance, illustrating common sequences. The directed view represents the highest level of abstraction and uses two visual elements, heat maps and a vector field, to illustrate overall performance in individual events and movement through the program. Results from multiple cohorts can then be superimposed on the same visualization to enable easy comparisons between patterns. Together, these abstractions provide a focus+context view of student performance, retaining outliers and emphasizing common patterns to illuminate dominant and unique patterns between cohorts of students.

This approach can help educators better understand student progress through the program, performance in individual courses, or student-selected course sequencing and this information can be used to address deficiencies in preparation, skills, or prerequisites. To demonstrate the appropriateness of this approach, performance and enrollment patterns are explored in the Computer Science program at the University of Maryland, Baltimore County. Specifically, this work examines the Gateway policy that requires students to earn a B or higher in the first two required programming courses before progressing with the hopes of validating the existing Gateway but also exploring other possible Gateway courses. Other issues explored within the Computer Science program include race, gender, math placement, and high school scores with the goal of attracting and retaining a more diverse group of students.

Committee: Penny Rheingans (chair), Marie desJardins, Marc Olano, Tim Finin and Diane Lee

Computer Science and Electrical Engineering
University of Maryland, Baltimore County

Ph.D. Dissertation Defense

Multiple Objective Task Scheduling
for Scalable High Performance Computing

Tyler A. Simon

12:30-2:30 Friday, 8 November 2013, ITE 325b

Individual processor frequencies have reached an upper physical and practical limit. Processor designs now involve adding multiple processing elements to a single chip to enable increased performance. It is expected that all future processor designs will have multiple cores with a focus on reducing frequencies and adding more individual processing elements (cores) while having to balance power consumption, reliability and maintain high performance.

Due to the increased complexity as well as increased heterogeneity of parallel architectures, petascale and future exascale systems, with the number of processors on the order of 10^8-10^9, must incorporate more intelligent software tools that help manage parallel execution for the user. I demonstrate that by managing the parallel execution environment at runtime, we can satisfy performance tradeoffs for a particular application or application domain for a set of common HPC architectures. It is expected that future exascale computing systems will have to execute programs on many individual and potentially low powered processing elements. These processors need to be fed data efficiently and reliably through the duration of a parallel computation.

In this thesis I provide a performance analysis of two common graph algorithms for finding a minimum spanning tree and evaluate the multicore performance of a common high performance computing (HPC) benchmark on multicore processors. I also develop a novel autonomic execution model and adaptive runtime system (ARRIA) Adaptive Runtime Resource for Intensive Applications. ARRIA is designed with the intent of improving application programmability, scalability and performance while freeing the programmer from explicit message passing and thread management. Experiments are conducted that evaluate ARRIA’s capabilities on data intensive applications, those where the majority of execution time is spent reading and writing either to local or remote memory locations. In my approach, I focus on developing task schedules that satisfy multiple objectives for clusters of compute nodes during runtime. This approach is novel in that it can control application performance and satisfy constraints that are solved using multi objective optimization techniques as the program runs. The development and implementation of the ARRIA runtime system and subsequent optimization criteria likely provide reasonable models for the exascale computing era.

The results of this dissertation demonstrate, experimentally, that for high performance computing systems, a dynamic, task based, parallel programming environment and scheduler can provide lower total workload runtimes and high utilization compared with commonly used static scheduling policies.

Computer Science and Electrical Engineering
Quantum Computing Seminar

Thermal Light N-qubit

Tao Peng (PhD Advisor: Yanhua Shih)
UMBC Physics Department

2:30-3:00 Tuesday, 22 October 2013, ITE 325b

This talk will discuss the equipment and optical elements that required for building the incoherent thermal source, the qubit, and the detection scheme of the intensity fluctuation-fluctuation correlation.

All optical XOR, CNOT gates with initial insight
for quantum computation using linear optics

Omar Shehab (PhD Advisor: Samuel Lomonaco)
UMBC CSEE Department

3:00-3:30 pm, Tuesday, 22 October 2013, ITE 325b

The design for an all-optical XOR gate is proposed. The basic idea is to split the input beams, and let them cancel or strengthen each other selectively, or flip the encoded information based on their polarization properties. The information is encoded in terms of polarization of the beam. Polarization of a light beam is well understood, hence, the design should be feasible to implement. The truth table of the optical circuit is worked out and compared with the expected truth table. Then it is demonstrated that the design complies with the linear behavior of the XOR function.

Next, based on a similar idea, the design of an all-optical CNOT gate is proposed. The truth table for the gate is verified. Then, it is discussed how this approach can be used for Linear Optics Quantum Computation (LOQC). It is shown that a Hadamard gate, a rotation gate, and a CNOT gate make up a universal set of quantum gates based on linear optics. This novel approach requires no additional power supply, extra input beam or ancilla photon to operate. It also does not require an expensive and complex single photon source and detector. Only narrowband laser sources are required to operate these gates.

Organizer: Prof. Samuel Lomonaco,

UMBC Center for Information Security and Assurance

Quantum Computing and Cybersecurity

John Seymour

Noon-1:00 Friday, 4 October 2013
Cyber Defense Lab, room 228 ITE, UMBC

This talk will be a brief introduction to the topic of quantum computing for the computer scientist interested in cybersecurity. It will begin with a light summary of the fundamental quantum algorithms and move to discuss the recent advances in quantum computing, including the D-Wave quantum optimizer, University of Bristol’s new quantum chip, quantum programming languages, and more. Finally, it will introduce some current research questions and projects residing in the intersection of quantum computing and cybersecurity.

John Seymour is a Ph.D. student in the UMBC computer science graduate program. As a UMBC undergraduate, he was a triple major — Computer Science, — Mathematics and Philosophy. He is currently working on three research projects: evaluation of a detection protocol for Man-in-the-Middle attacks, a web-based game for teaching students basic concepts of internet security, and integration of social media with internet voting to facilitate collaborative decision making.

Host: Dr. Alan T. Sherman,

UMBC students interested in learning more about pursuing a graduate program in a STEM area should consider taking advantage of a free GEM GRAD Lab event to be held at the University of Virginia on Saturday, September 28th. UMBC is a co-sponsor, along with UVA and VA Tech and will provide free bus transportation. See here for more information and details about how to reserve a seat on the bus. The event will cover topics that include why go to graduate school, how to apply to graduate school, how to fund graduate school and voices from the field.