Defense Notices


All students and faculty are welcome to attend the final defense of EECS graduate students completing their M.S. or Ph.D. degrees. Defense notices for M.S./Ph.D. presentations for this year and several previous years are listed below in reverse chronological order.

Students who are nearing the completion of their M.S./Ph.D. research should schedule their final defenses through the EECS graduate office at least THREE WEEKS PRIOR to their presentation date so that there is time to complete the degree requirements check, and post the presentation announcement online.

Upcoming Defense Notices

Jennifer Quirk

Aspects of Doppler-Tolerant Radar Waveforms

When & Where:


Nichols Hall, Room 246 (Executive Conference Room)

Committee Members:

Shannon Blunt, Chair
Patrick McCormick
Charles Mohr
James Stiles
Zsolt Talata

Abstract

The Doppler tolerance of a waveform refers to its behavior when subjected to a fast-time Doppler shift imposed by scattering that involves nonnegligible radial velocity. While previous efforts have established decision-based criteria that lead to a binary judgment of Doppler tolerant or intolerant, it is also useful to establish a measure of the degree of Doppler tolerance. The purpose in doing so is to establish a consistent standard, thereby permitting assessment across different parameterizations, as well as introducing a Doppler “quasi-tolerant” trade-space that can ultimately inform automated/cognitive waveform design in increasingly complex and dynamic radio frequency (RF) environments. 

Separately, the application of slow-time coding (STC) to the Doppler-tolerant linear FM (LFM) waveform has been examined for disambiguation of multiple range ambiguities. However, using STC with non-adaptive Doppler processing often results in high Doppler “cross-ambiguity” side lobes that can hinder range disambiguation despite the degree of separability imparted by STC. To enhance this separability, a gradient-based optimization of STC sequences is developed, and a “multi-range” (MR) modification to the reiterative super-resolution (RISR) approach that accounts for the distinct range interval structures from STC is examined. The efficacy of these approaches is demonstrated using open-air measurements. 

The proposed work to appear in the final dissertation focuses on the connection between Doppler tolerance and STC. The first proposal includes the development of a gradient-based optimization procedure to generate Doppler quasi-tolerant random FM (RFM) waveforms. Other proposals consider limitations of STC, particularly when processed with MR-RISR. The final proposal introduces an “intrapulse” modification of the STC/LFM structure to achieve enhanced sup pression of range-folded scattering in certain delay/Doppler regions while retaining a degree of Doppler tolerance.


Mary Jeevana Pudota

Assessing Processor Allocation Strategies for Online List Scheduling of Moldable Task Graphs

When & Where:


Eaton Hall, Room 2001B

Committee Members:

Hongyang Sun, Chair
David Johnson
Prasad Kulkarni


Abstract

Scheduling a graph of moldable tasks, where each task can be executed by a varying number of

processors with execution time depending on the processor allocation, represents a fundamental

problem in high-performance computing (HPC). The online version of the scheduling problem

introduces an additional constraint: each task is only discovered when all its predecessors have

been completed. A key challenge for this online problem lies in making processor allocation

decisions without complete knowledge of the future tasks or dependencies. This uncertainty can

lead to inefficient resource utilization and increased overall completion time, or makespan. Recent

studies have provided theoretical analysis (i.e., derived competitive ratios) for certain processor

allocation algorithms. However, the algorithms’ practical performance remains under-explored,

and their reliance on fixed parameter settings may not consistently yield optimal performance

across varying workloads. In this thesis, we conduct a comprehensive evaluation of three processor

allocation strategies by empirically assessing their performance under widely used speedup models

and diverse graph structures. These algorithms are integrated into a List scheduling framework that

greedily schedules ready tasks based on the current processor availability. We perform systematic

tuning of the algorithms’ parameters and report the best observed makespan together with the

corresponding parameter settings. Our findings highlight the critical role of parameter tuning in

obtaining optimal makespan performance, regardless of the differences in allocation strategies.

The insights gained in this study can guide the deployment of these algorithms in practical runtime

systems.


Past Defense Notices

Dates

KEERTHI GANTA

TCP Illinois Protocol Implementation in ns-3

When & Where:


250 Nichols Hall

Committee Members:

James Sterbenz, Chair
Victor Frost
Bo Luo


Abstract

The choice of congestion control algorithm has an impact on the performance of a network. The congestion control algorithm should be selected and implemented based on the network scenario in order to achieve better results. Congestion control in high speed networks and networks with large BDP is proved to be more critical due to the high amount of data at risk. There are problems in achieving better throughput with conventional TCP in the above mentioned scenario. Over the years conventional TCP is modified to pave way for TCP variants that could address the issues in high speed networks. TCP Illinois is one such protocol for high speed networks. It is a hybrid version of a congestion control algorithm as it uses both packet loss and delay information to decide on the window size. The packet loss information is used to decide on whether to increase or decrease the congestion window and delay information is used to assess the amount of increase or decrease that has to be made.


ADITYA RAVIKANTI

sheets-db: Database powered by Google Spreadsheets

When & Where:


2001B Eaton Hall

Committee Members:

Andy Gill, Chair
Perry Alexander
Prasad Kulkarni


Abstract

The sheets-db library is a Haskell binding to Google Sheets API. sheets-db allows Haskell users to utilize google spread sheets as a light weight database. It provides various functions to create, read, update and delete rows in spreadsheets along with a way to construct simple structured queries. 


NIRANJAN PURA VEDAMURTHY

Testing the Accuracy of Erlang Delay Formula for Smaller Number of TCP Flows

When & Where:


246 Nichols Hall

Committee Members:

Victor Frost, Chair
Gary Minden
Glenn Prescott


Abstract

The Erlang delay formula for dimensioning different networks is used to calculate the probability of congestion. Testing the accuracy of a probability of congestion found using the Erlang formula against the simulation for probability of packet loss is demonstrated in this project. The simulations are done when TCP traffic is applied through one bottleneck node. Three different source traffic models having small number of flows is considered. Simulations results for three different source traffic models is shown in terms of probability of packet loss and load supplied to the topology. Various traffic parameters are varied in order to show the impact on the probability of packet loss and to compare with the Erlang prediction for probability of congestion.

 


MAHMOOD HAMEED

Nonlinear Mixing in Optical Multicarrier Systems

When & Where:


246 Nichols Hall

Committee Members:

Ron Hui, Chair
Shannon Blunt
Erik Perrins
Alessandro Salandrino
Carey Johnson

Abstract

Efficient use of the vast spectrum offered by fiber-optic links by an end user with relatively small bandwidth requirement is possible by partitioning a high speed signal in a wavelength channel into multiple low-rate subcarriers. Multicarrier systems not only ensure efficient use of optical and electrical components, but also tolerate transmission impairments. The purpose of this research is to experimentally understand and minimize the impact of mixing among subcarriers in Radio-Over-Fiber (RoF) and direct detection systems, involving a nonlinear component such as a semiconductor optical amplifier. We also analyze impact of clipping and quantization on multicarrier signals and compare electrical bandwidth utilization of two popular multiplexing techniques in orthogonal frequency division multiplexing (OFDM) and Nyquist modulation. 
For an OFDM-RoF system, we present a novel technique that minimizes the RF domain signal-signal beat interference (SSBI), relaxes the phase noise requirement on the RF carrier, realizes the full potential of the optical heterodyne technique, and increases the performance-to-cost ratio of RoF systems. We demonstrate a RoF network that shares the same RF carrier for both downlink and uplink, avoiding the need of an additional RF oscillator in the customer unit. 
For direct detection systems, we first experimentally compare performance degradations of coherent optical OFDM and single carrier Nyquist pulse modulated systems in a nonlinear environment. We then experimentally evaluate the performance of signal-signal beat interference (SSBI) compensation technique in the presence of semiconductor optical amplifier (SOA) induced nonlinearities for a multicarrier optical system with direct detection. We show that SSBI contamination can be removed from the data signal to a large extent when the optical system operates in the linear region, especially when the carrier-to-signal power ratio is low. 


SUSOBHAN DAS

Tunable Nano-photonic Devices

When & Where:


246 Nichols Hall

Committee Members:

Ron Hui, Chair
Alessandro Salandrino
Chris Allen
Jim Stiles
Judy Wu

Abstract

In nano-photonics, the control of optical signals is based on tuning of the material optical properties in which the electromagnetic field propagates, and thus the choice of materials and of the physical modulation mechanism plays a crucial role. Several materials such as graphene, Indium Tin Oxide (ITO), and vanadium di-oxide (VO2) investigated here have attracted a great deal of attention in the nanophotonic community because of their remarkable tunability. This dissertation will include both theoretical modeling and experimental characterization of functional electro-optic materials and their applications in guided-wave photonic structures. 
We have characterized the complex index of graphene in near infrared (NIR) wavelength through the reflectivity measurement on a SiO2/Si substrate. The measured complex indices as the function of the applied gate electric voltage agreed with the prediction of the Kubo formula. 
We have performed the mathematical modeling of permittivity of ITO based on the Drude Model. Results show that ITO can be used as a plasmonic material and performs better than noble metals for applications in NIR wavelength region. Additionally, the permittivity of ITO can be tuned by carrier density change through applied voltage. An electro-optic modulator (EOM) based on plasmonically enhanced graphene has been proposed and modeled. We show that the tuning of graphene chemical potential through electrical gating is able to switch on and off the ITO plasmonic resonance. This mechanism enables dramatically increased electro-absorption efficiency. 
Another novel photonic structure we are investigating is a multimode EOM based on the electrically tuned optical absorption of ITO in NIR wavelengths. The capability of mode-multiplexing increases the functionality per area in a nanophotonic chip. Proper design of ITO structure based on the profiles of y-polarized TE11 and TE21 modes allows the modulation of both modes simultaneously and differentially. 
We have experimentally demonstrated the ultrafast changes of optical properties associated with dielectric-to-metal phase transition of VO2. This measurement is based on a fiber-optic pump-probe setup in NIR wavelength. Instantaneous optical phase modulation of the probe was demonstrated during pump pulse leading edge, which could be converted into an intensity modulation of the probe through an optical frequency discriminator 


NIHARIKA DIVEKAR

Feature Extraction for Alias Resolution

When & Where:


2001B Eaton Hall

Committee Members:

Joseph Evans, Chair
Gary Minden
Benjamin Ewy


Abstract

Alias resolution or disambiguation is the process of determining which IP addresses belong to the same router. The focus of this project is the feature extraction aspect of the AliasCluster alias resolution technique. This technique uses five features extracted from traceroutes and uses a Naive Bayesian approach to resolve router aliases. The features extracted are the common subnet, percentage out-degree match for hop count ≤ 3, percentage out-degree match for hop count ≤ 4, percentage hop-count match for hop count ≤ 3, and percentage hop-count match for hop count ≤ 4. Using traceroutes from publicly available databases, the common subnet feature is determined by finding the number of bits common to two addresses, and the out-degree match is found by checking the number of interfaces in the downpath that appear in common to two addresses. The hop-count match is determined in a approach similar to the out-degree match, with an additional condition that the common interfaces must appear at the same hop count. In this project, algorithms to extract these features are implemented in Python and the feature distributions are compared to those described in the original AliasCluster work.


HAO CHEN

Mutual Information Accumulation over Wireless Networks: Fundamentals, Applications, and Implementation

When & Where:


246 Nichols Hall

Committee Members:

Lingjia Liu, Chair
Shannon Blunt
Victor Frost
Erik Perrins
Zsolt Talata

Abstract

Future wireless networks will face a compound challenge of supporting large traffic volumes, providing ultra-reliable and low latency connections to ultra-dense mobile devices. To meet this challenge, various new technologies have been introduced among which mutual-information accumulation (MIA), an advanced physical (PHY) layer coding technique, has been shown to significantly improve the network performance. Since the PHY layer is the fundamental layer, MIA could potentially impact various network layers of a wireless network. Accordingly, the understanding of improving network design based on MIA is far from being fully developed. In the proposed research, we target to 1) apply MIA techniques to various wireless networks such as cognitive radio networks, device-to-device networks, etc; 2) mathematically characterize the performance of such networks employing MIA; 3) use hardware to demonstrate the performance of MIA for a simple wireless network using the Universal Software Radio Peripherals (USRPs).


BHARATH ELLURU

Measuring Firmware of An Embedded Device

When & Where:


2001B Eaton Hall

Committee Members:

Perry Alexander, Chair
Jerzy Grzymala-Busse
Prasad Kulkarni


Abstract

System Security has been one of the primary focus areas for embedded devices in recent times. The pervasion of embedded devices over a wide range of applications ranging from routers to RFID badge controls emphasizes the need for System Security. Any security compromise may result in manipulation, damage or loss of crucial data leading to unwarranted results. A conventional approach towards system security is the use of static analysis tools on source code. However, very few of these tools operate at the system level. This project envisions measuring (Looking at a given device and analyzing what is present)firmware of Gumstix, an embedded device running poky version of Linux and build a model that serves as an input to Action Notation Modelling Language (ANML) planner. An ANML planner can be later on used to generate a check list of vulnerabilities, which is out of scope for this project. 


PENG SENG TAN

Addressing Spectrum Congestion by Spectrally-Cognizant Radar Design

When & Where:


250 Nichols Hall

Committee Members:

Jim Stiles, Chair
Shannon Blunt
Chris Allen
Lingjia Liu
Tyrone Duncan

Abstract

Due to the need for greater Radio Frequency (RF) spectrum by wireless communication industries such as mobile telephony, cable/satellite and wireless internet as a result of growing consumer base and demands, it has led to the issue of spectrum congestion as radar systems have traditionally maintain the largest share of the RF spectrum. To resolve the spectrum congestion problem, it has become even necessary for users from both types of systems to coexist within a finite spectrum allocation. However, this then leads to other problems such as the increased likelihood of mutual interference experienced by all users that are coexisting within the finite spectrum. 
In this dissertation, we propose to address the problem of spectrum congestion via two independent approaches. The first approach involves designing an intelligent scheme to perform spectrum reallocation to radar systems such that the range resolution performance can be maintained with a smaller resulting bandwidth but at a cost of degraded sidelobe performance. The second approach involves designing a radar waveform that possesses good spectral containment property by utilizing the framework of Poly-phased coded Frequency Modulated (PCFM) waveforms such that the waveform will mitigate the issue of interference experienced by other users coexisting within the same band. 


LEI YANG

Design and Analysis of Low-Latency Anonymous Communications for Big Data Applications

When & Where:


246 Nichols Hall

Committee Members:

Fengjun Li, Chair
Luke Huan
Prasad Kulkarni
James Sterbenz
Yong Zeng

Abstract

Although the Internet tremendously facilitates online interaction and information exchange beyond geographic boundaries, it also enlarges attack surface for adversaries to sniff users’ privacy such as who you are, who you are talking to, and what you are saying from their communication activities over the open networks. The goal of anonymous communication networks is to protect the identity and location of a communication participant from being learned by the other participant or any third party. Tor is a most popular low-latency anonymity network. While Tor provides good privacy protection to millions of users on a daily basis, its performance and security issues are widely recognized. We anticipate that big data applications, such as anonymous video conferencing, will pose a large amount of extra traffic to Tor. The performance problem becomes a biggest obstacle impeding Tor’s further expansion, which will be aggravated in the big data era. On the other hand, it is well known that Tor is vulnerable to traffic analysis attacks, especially the end-to-end traffic confirmation attack. 
In this proposal, we target the problems discussed above and propose a solution suite to address them correspondingly. We first explore the utilization of resources and find that a large portion of low-bandwidth relays are under-utilized. Therefore, we propose a multipath routing scheme to use idle resources to support bandwidth-intensive applications, which are the efforts that we make to solve the performance problems in general Tor services. To further improve the performance, we propose to enable differentiated services in Tor. The current Tor system treats clients’ requests equally and provides the same level of protection, neglecting the heterogeneity in individuals’ anonymity needs. To address this problem, we propose a learning-based solution that can automatically recognize users’ different anonymity needs for different applications and integrates it into the currently multipath Tor design to support dynamic, self-configurable anonymous communication. Then, we propose a multipath-routing based architecture for Tor hidden services to enhance the resistance of Tor hidden services against traffic analysis attacks.