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Theses/Dissertations from 2023

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WATCH: A Distributed Clock Time Offset Estimation Tool on the Platform for Open Wireless Data-Driven Experimental Research, Cassie Jeng

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Targeted Adversarial Attacks against Neural Network Trajectory Predictors, Kaiyuan Tan

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Adversarial Patch Attacks on Deep Reinforcement Learning Algorithms, Peizhen Tong

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Real-time Analysis of Aerosol Size Distributions with the Fast Integrated Mobility Spectrometer (FIMS), Daisy Wang

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Mirror Position Detection in a Catoptric Surface, Run Zhang

Theses/Dissertations from 2022

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Applying HLS to FPGA Data Preprocessing in the Advanced Particle-astrophysics Telescope, Meagan Konst

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Model-based Deep Learning for Computational Imaging, Xiaojian Xu

Theses/Dissertations from 2021

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Machine Learning for Analog/Mixed-Signal Integrated Circuit Design Automation, Weidong Cao

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A Collaborative Knowledge-Based Security Risk Assessments Solution using Blockchains, Tara Thaer Salman

Adversarial Attack and Defense on Image Classification under Physical Constraints
Tong Wu
MS Project Report

Abstract:

Recent work has demonstrated how adversarial attacks on neural network can cause misclassifications of given objects in physical worlds. However, despite the large amount works, there have been limited researches focusing on the security of the whole computer vision pipeline. In addition, effective defending methods against such attacks remained unexplored, raising safety and reliability concerns for deployment of machine learning applications.

In this project, we argue the recent works of directly applying perturbations to the camera lens are obvious if any testing is done on the network to check its... Read More

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Effective Machine Learning Methods for Accurate Medical Image Segmentation, Zhuangzhuang Zhang

Theses/Dissertations from 2020

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Domain Specific Computing in Tightly-Coupled Heterogeneous Systems, Anthony Michael Cabrera

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Investigating Single Precision Floating General Matrix Multiply in Heterogeneous Hardware, Steven Harris

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Elicitation and aggregation of data in knowledge intensive crowdsourcing
Dohoon Kim
MS Project Report

Abstract:

With the significant advance of internet and connectivity, crowdsourcing gained more popularity and various crowdsourcing platforms emerged. This project focuses on knowledge-intensive crowdsourcing, in which agents are presented with the tasks that require certain knowledge in domain. Knowledge-intensive crowdsourcing requires agents to have experiences on the specific domain. With the constraint of resources and its trait as sourcing from crowd, platform is likely to draw agents with different levels of expertise and knowledge and asking same task can result in bad performance. Some agents can give better information when they... Read More

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A Virtual 4D CT Scanner
Xiwen Li
MS Project Report

Abstract:

4D CT scan is widely used in medical imaging. Images are acquired through phases. In this case, we can track the motion of organs such as heart. However, it also introduces motion artifacts. A lot of research focuses on remove these artifacts. It is difficult to acquire artifact data by a real CT scanner. In this project, we implement a virtual CT machine to simulate the real 4D CT scan. we also conduct experi- ments to check its clinical reality with respect to respiratory and heart motion parameters.

... Read More

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Centrality of Blockchain
Zixuan Li
MS Project Report

Abstract:

Decentralization is widely recognized as the property and one of most important advantage of blockchain over legacy systems. However, decentralization is often discussed on the consensus layer and recent research shows the trend of centralization on several subsystem of blockchain. In this project, we measured centralization of Bitcoin and Ethereum on source code, development eco-system, and network node levels. We found that the programming language of project is highly centralized, code clone is very common inside Bitcoin and Ethereum community, and developer contribution distribution is highly centralized. We further discuss... Read More

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The Effects of Mixed-Initiative Visualization Systems on Exploratory Data Analysis
Alvitta Ottley and Adam Kern
Technical Report

Abstract:

The primary purpose of information visualization is to act as a window between a user and the data. Historically, this has been accomplished via a single-agent framework: the only decision-maker in the relationship between visualization system and analyst is the analyst herself. Yet this framework arose not from first principles, but a necessity. Before this decade, computers were limited in their decision-making capabilities, especially in the face of large, complex datasets and visualization systems. This paper aims to present the design and evaluation of a mixed-initiative system that aids the... Read More

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Solving disappearance at GASTech with visual analytic techniques
Saulet Yskak
MS Project Report

Abstract:

We are living in a society, where images and charts speak louder than words. Therefore, information visualization plays a major role in solving complex problems since it provides a visual summary of data that makes it easier to identify trends and patterns.

In this master project, I propose a web – based visual analytics tool that enables to analyze complex email and time based / event series data. The visual analytics framework uses test data from IEEE VAST Challenge 2014: Mini challenge 1 that concentrated on the disappearance of employees... Read More

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Investigating Patterns in Convolution Neural Network Parameters Using Probabilistic Support Vector Machines, Yuqiu Zhang

Theses/Dissertations from 2019

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Decoupling Information and Connectivity via Information-Centric Transport, Hila Ben Abraham

A System for TA Checkouts
Benjamin Choi
MS Project Report

Abstract:

Currently, TA checkout procedures for courses like CSE 131 and 247 are handled in 1 of 2 ways: by filling out a form on the student’s browser or by filling out a Google Form. Both are bottlenecks in the checkout procedure, which the system aims to solve by allowing TAs to quickly checkout students with the help of mobile phones. For each assignment and student, a unique QR code will be used so TAs can quickly verify the identity of the student and correctly check them out for the desired... Read More

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Static Taint Analysis of Binary Executables Using Architecture-Neutral Intermediate Representation
Elaine Cole
MS Project Report

Abstract:

Ghidra, National Security Agency’s powerful reverse engineering framework, was recently released open-source in April 2019 and is capable of lifting instructions from a wide variety of processor architectures into its own register transfer language called p-code. In this project, we present a new tool which leverages Ghidra’s specific architecture-neutral intermediate representation to construct a control flow graph modeling all program executions of a given binary and apply static taint analysis. This technique is capable of identifying the information flow of malicious input from untrusted sources that may interact with key... Read More

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Management And Security Of Multi-Cloud Applications, Lav Gupta

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A Survey on the Role of Individual Differences on Visual Analytics Interactions: Masters Project Report
Jesse Huang and Alvitta Ottley
MS Project Report

Abstract:

There is ample evidence in the visualization commu- nity that individual differences matter. These prior works high- light various traits and cognitive abilities that can modulate the use of the visualization systems and demonstrate a measurable influence on speed, accuracy, process, and attention. Perhaps the most important implication of this body of work is that we can use individual differences as a mechanism for estimating people’s potential to effectively leverage visual interfaces or to identify those people who may struggle. As visual literacy and data fluency continue to become essential... Read More

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Toward Controllable and Robust Surface Reconstruction from Spatial Curves, Zhiyang Huang

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Polarization Division Multiplexing for Optical Data Communications, Darko Ivanovich

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Pipelined Parallelism in a Work-Stealing Scheduler
Thomas Kelly
MS Project Report

Abstract:

A pipeline is a particular type of parallel program structure, often used to represent loops with cross-iteration dependencies. Pipelines cannot be expressed with the typical parallel language constructs offered by most environments. Therefore, in order to run pipelines, it is necessary to write a parallel language and scheduler with specialized support for them. Some such schedulers are written exclusively for pipelines and unable to run any other type of program, which allows for certain optimizations that take advantage of the pipeline structure. Other schedulers implement support for pipelines on top... Read More

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Feature Extraction form CT Scan of Plant Root
Chunyuan Li
MS Project Report

Abstract:

Roots are vital for plant by absorbing water and nutrients and providing anchorage from beneath the soil. These roles are closely related to the roots’ architecture, which describes the geometry of individual roots and their branching structure. We proposed a pipeline to efficiently annotate root architecture. My contribution focus on building an interactive tool to visual and annotate root architecture. Besides, we come up with heuristics to automate the annotation process.

... Read More

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Point Cloud Processing with Neural Networks
Stephanie Miller and Jiahao Li
MS Project Report

Abstract:

In this project, we explore new techniques and architectures for applying deep neural networks when the input is point cloud data. We first consider applying convolutions on regular pixel and voxel grids, using polynomials of point coordinates and Fourier transforms to get a rich feature representation for all points mapped to the same pixel or voxel. We also apply these ideas to generalize the recently proposed "interpolated convolution", by learning continuous-space kernels as a combination of polynomial and Fourier basis kernels. Experiments on the ModelNet40 dataset demonstrate that our methods... Read More

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Challenges in Integrating IoT in Smart Home
Leiquan Pan and Chenyang Lu
MS Project Report

Abstract:

Wireless devices have become a major part in Smart Home industry. Almost every smart home company has its own wireless solutions and cloud services. Normally, customers can only monitor and control smart devices through applications or platforms companies provided. It causes inconveniences and problems when we have lots of smart devices. In my master project, I did two projects to implement smart home IoT applications. From a single functionality IoT application to a more complicated smart home system, there are lots of challenges and problems appeared. This article will mainly... Read More

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Real-Time Reliable Middleware for Industrial Internet-of-Things, Chao Wang

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Smart Home Audio Assistant
Xipeng Wang
MS Project Report

Abstract:

This report introduces an audio processing algorithm. It provides a way to access smart devices using audio. Although there are many audio assistants already on the market, most of them will not be able to control the smart devices. Therefore, this new system presented in this report will provide a way to analysis the customer’s questions. Then the algorithm will be able to query smart device information, modify the schedule or provide the reason for some arrangement.

... Read More

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Computational Geometry Teaching Tool
Yujie Zhou and Tao Ju
MS Project Report

Abstract:

When students are taking Computational Geometry course which covers many geometry algorithms, most of them are difficult to follow because these algorithms are very abstract even if authors draw pictures to illustrate. In order to help students to get a better understanding of these algorithms, we decide to design Computational Geometry Teaching Tool. This tool is a web application that covers 8 geometry algorithms : Graham Scan, Quick Hull, Line Segment Intersection, Dual, Line Arrangement, Voronoi Diagram, Incremental Delaunay Triangulation and Kd Tree. First, this tool is developed by using... Read More

Theses/Dissertations from 2018

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Nanopower Analog Frontends for Cyber-Physical Systems, Kenji Aono

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Development of Scalable Simulator for Spiking Neural Network, Jae Sang Ha

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Modeling and Analyzing Neural Dynamics and Information Processing over Multiple Time Scales, Sensen Liu

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Self-powered Time-Keeping and Time-of-Occurrence Sensing, Liang Zhou

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Security Services Using Blockchains: A State of the Art Survey
Maeda Zolanvari, Aiman Erbad, Raj Jain, and Mohammed Samaka
Journal Article

Abstract:

This article surveys blockchain-based approaches for several security services. These services include authentication, confidentiality, privacy and access control list (ACL), data and resource provenance, and integrity assurance. All these services are critical for the current distributed applications, especially due to the large amount of data being processed over the networks and the use of cloud computing. Authentication ensures that the user is who he/she claims to be. Confidentiality guarantees that data cannot be read by unauthorized users. Privacy provides the users the ability to control who can access their data.... Read More

Research from 2017

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Decoupling Information and Connectivity in Information-Centric Networking
Hila Ben Abraham, Jyoti Parwatikar, John Dehart, Adam Drescher, and Patrick Crowley
Technical Report

Abstract:

This paper introduces and demonstrates the concept of Information-Centric Transport as a mechanism for cleanly decoupling the information plane from the connectivity plane in Information-Centric Networking (ICN) architectures, such as NDN and CICN. These are coupled in today's incarnations of NDN and CICN through the use of forwarding strategy, which is the architectural component for deciding how to forward packets in the presence of either multiple next-hop options or dynamic feedback. As presently designed, forwarding strategy is not sustainable: application developers can only confidently specify strategy if they understand connectivity... Read More

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Efficiently and Transparently Maintaining High SIMD Occupancy in the Presence of Wavefront Irregularity, Stephen V. Cole

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Efficient Geometric Approaches for Mining Protein Structure from Cryo-EM Density Maps, Hang Dou

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Bio-Inspired Multi-Spectral and Polarization Imaging Sensors for Image-Guided Surgery, Nimrod Missael Garcia

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Parallel Real-Time Scheduling for Latency-Critical Applications, Jing Li

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Underwater Celestial Navigation Using the Polarization of Light Fields, Samuel Bear Powell

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Pricing and Bidding Strategies for Cloud Computing Spot Instances
Jiayi Song and Roch A. Guérin
Conference Paper

Abstract:

We consider a cloud service based on spot instances and explore bidding and pricing strategies aimed at optimizing users' utility and provider's revenue, respectively. Our focus is on jobs that are heterogeneous in both valuation and sensitivity to execution delay. Of particular interest is the impact of correlation in these two dimensions. We characterize optimal bidding and pricing strategies under some simplifying assumptions, and more importantly highlight the impact of correlation in determining the benefits of a spot service over an on-demand service. We also provide a preliminary assessment of... Read More

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Easier Parallel Programming with Provably-Efficient Runtime Schedulers, Robert Utterback

Research from 2016

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In-Network Retransmissions in Named Data Networking
Hila Ben Abraham and Patrick Crowley
Technical Report

Abstract:

The strategy layer is an important architectural component in both Content-Centric Networking (CCN) and Named Data Networking (NDN). This component introduces a new forwarding model that allows an application to configure its namespace with a forwarding strategy. A core mechanism in every forwarding strategy is the decision of whether to retransmit an unsatisfied Interest or to wait for an application retransmission. While some applications request control of all retransmissions, others rely on the assumption that the strategy will retransmit an Interest when it is not satisfied. Although an application can... Read More

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MERCATOR (Mapping EnumeRATOR for CUDA) User's Manual
Stephen V. Cole and Jeremy Buhler
Technical Report

Abstract:

Welcome to the MERCATOR user's manual! MERCATOR is a CUDA/C++ system designed to assist you in writing efficient CUDA applications by automatically generating significant portions of the GPU-side application code. We hope you find it helpful; please feel free to contact the authors with any questions or feedback.

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Learning in the Real World: Constraints on Cost, Space, and Privacy, Matt J. Kusner

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Multipath and Rate Stability
Junjie Liu and Roch A. Guérin
Conference Paper

Abstract:

Originally Published In Proc. IEEE Globecom Conference - CQRM: Communication QoS, Reliability & Modeling Symposium

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Locality-Aware Dynamic Task Graph Scheduling
Jordyn Maglalang, Sriram Krishnamoorthy, and Kunal Agrawal
Conference Paper

Abstract:

Dynamic task graph schedulers automatically balance work across processor cores by scheduling tasks among available threads while preserving dependences. In this paper, we design NabbitC, a provably efficient dynamic task graph scheduler that accounts for data locality on NUMA systems. NabbitC allows users to assign a color to each task representing the location (e.g., a processor core) that has the most efficient access to data needed during that node’s execution. NabbitC then automatically adjusts the scheduling so as to preferentially execute each node at the location that matches its color—leading... Read More

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Grafalgo - A Library of Graph Algorithms and Supporting Data Structures (revised)
Jonathan Turner
Technical Report

Abstract:

This report provides an (updated) overview of Grafalgo, an open-source library of graph algorithms and the data structures used to implement them. The programs in this library were originally written to support a graduate class in advanced data structures and algorithms at Washington University. Because the code's primary purpose was pedagogical, it was written to be as straightforward as possible, while still being highly efficient. Grafalgo is implemented in C++ and incorporates some features of C++11. The library is available on an open-source basis and may be downloaded from https://code.google.com/p/grafalgo/.... Read More

Research from 2015

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WOODSTOCC: Extracting Latent Parallelism from a DNA Sequence Aligner on a GPU
Stephen V. Cole, Jacob R. Gardner, and Jeremy D. Buhler
Technical Report

Abstract:

An exponential increase in the speed of DNA sequencing over the past decade has driven demand for fast, space-efficient algorithms to process the resultant data. The first step in processing is alignment of many short DNA sequences, or reads, against a large reference sequence. This work presents WOODSTOCC, an implementation of short-read alignment designed for Graphics Processing Unit (GPU) architectures. WOODSTOCC translates a novel CPU implementation of gapped short-read alignment, which has guaranteed optimal and complete results, to the GPU. Our implementation combines an irregular trie search with dynamic programming... Read More

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Faster Maximium Priority Matchings in Bipartite Graphs
Jonathan Turner
Technical Report

Abstract:

A maximum priority matching is a matching in an undirected graph that maximizes a priority score defined with respect to given vertex priorities. An earlier paper showed how to find maximum priority matchings in unweighted graphs. This paper describes an algorithm for bipartite graphs that is faster when the number of distinct priority classes is limited. For graphs with k distinct priority classes it runs in O(kmn1/2) time, where n is the number of vertices in the graph and m is the number of edges.

... Read More

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Grafalgo - A Library of Graph Algorithms and Supporting Data Structures
Jonathan Turner
Technical Report

Abstract:

This report provides an overview of Grafalgo, an open-source library of graph algorithms and the data structures used to implement them. The programs in this library were originally written to support a graduate class in advanced data structures and algorithms at Washington University. Because the code's primary purpose was pedagogical, it was written to be as straightforward as possible, while still being highly efficient. Grafalgo is implemented in C++ and incorporates some features of C++11. The library is available on an open-source basis and may be downloaded from https://code.google.com/p/grafalgo/. Source... Read More

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Maximum Priority Matchings
Jonathan Turner
Technical Report

Abstract:

Let G=(V,E) be an undirected graph with n vertices and m edges, in which each vertex u is assigned an integer priority in [1,n], with 1 being the ``highest'' priority. Let M be a matching of G. We define the priority score of M to be an n-ary integer in which the i-th most-significant digit is the number of vertices with priority i that are incident to an edge in M. We describe a variation of the augmenting path method (Edmonds' algorithm) that finds a matching with maximum priority score... Read More

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The Bounded Edge Coloring Problem and Offline Crossbar Scheduling
Jonathan Turner
Technical Report

Abstract:

This paper introduces a variant of the classical edge coloring problem in graphs that can be applied to an offline scheduling problem for crossbar switches. We show that the problem is NP-complete, develop three lower bounds bounds on the optimal solution value and evaluate the performance of several approximation algorithms, both analytically and experimentally. We show how to approximate an optimal solution with a worst-case performance ratio of 3/2 and our experimental results demonstrate that the best algorithms produce results that very closely track a lower bound.

... Read More

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The Edge Group Coloring Problem with Applications to Multicast Switching
Jonathan Turner
Technical Report

Abstract:

This paper introduces a natural generalization of the classical edge coloring problem in graphs that provides a useful abstraction for two well-known problems in multicast switching. We show that the problem is NP-hard and evaluate the performance of several approximation algorithms, both analytically and experimentally. We find that for random χ-colorable graphs, the number of colors used by the best algorithms falls within a small constant factor of χ, where the constant factor is mainly a function of the ratio of the number of outputs to inputs. When this ratio... Read More

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Maximizing Network Lifetime of Wireless Sensor-Actuator Networks under Graph Routing
Chengjie Wu, Dolvara Gunatilaka, Abusayeed Saifullah, Mo Sha, Paras Tiwari, Chenyang Lu, and Yixin Chen
Technical Report

Abstract:

Process industries are adopting wireless sensor-actuator networks (WSANs) as the communication infrastructure. The dynamics of industrial environments and stringent reliability requirements necessitate high degrees of fault tolerance in routing. WirelessHART is an open industrial standard for WSANs that have seen world-wide deployments. WirelessHART employs graph routing schemes to achieve network reliability through multiple paths. Since many industrial devices operate on batteries in harsh environments where changing batteries are prohibitively labor-intensive, WSANs need to achieve long network lifetime. To meet industrial demand for long-term reliable communication, this paper studies the problem... Read More

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Conflict-Aware Real-Time Routing for Industrial Wireless Sensor-Actuator Networks
Chengjie Wu, Dolvara Gunatilaka, Mo Sha, and Chenyang Lu
Technical Report

Abstract:

Process industries are adopting wireless sensor-actuator networks (WSANs) as the communication infrastructure. WirelessHART is an open industrial standard for WSANs that have seen world-wide deployments. Real-time scheduling and delay analysis have been studied for WSAN extensively. End-to-end delay in WSANs highly depends on routing, which is still open problem. This paper presents the first real-time routing design for WSAN. We first discuss end-to-end delays of WSANs, then present our real-time routing design. We have implemented and experimented our routing designs on a wireless testbed of 69 nodes. Both experimental results... Read More

Research from 2014

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Exploring User-Provided Connectivity
Mohammad H. Afrasiabi and Roch Guerin
Technical Report

Abstract:

Network services often exhibit positive and negative externalities that affect users' adoption decisions. One such service is "user-provided connectivity" or UPC. The service offers an alternative to traditional infrastructure-based communication services by allowing users to share their "home base" connectivity with other users, thereby increasing their access to connectivity. More users mean more connectivity alternatives, i.e., a positive externality, but also greater odds of having to share one's own connectivity, i.e., a negative externality. The tug of war between positive and negative externalities together with the fact that they often... Read More

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Data Transport System
Rahav Dor
MS Project Report

Abstract:

To facilitate the WU Smart Home research [21] we built a system that collects data from sensors and uploads the data to the cloud. The system supports data collection from multiple locations (typically apartments) that are independent from each other, endowing the system with two benefit: distributed data collection and alleviating privacy concerns. Each location is managed by a local micro-server (μServer) that is responsible for receiving data packets from sensors and managing their transient storage. Periodically the μServer triggers a data transport process that moves the data to a... Read More

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CloudPowerCap: Integrating Power Budget and Resource Management across a Virtualized Server Cluster
Yong Fu, Anne Holler, and Chenyang Lu
Technical Report

Abstract:

In many datacenters, server racks are highly underutilized. Rack slots are left empty to keep the sum of the server nameplate maximum power below the power provisioned to the rack. And the servers that are placed in the rack cannot make full use of available rack power. The root cause of this rack underutilization is that the server nameplate power is often much higher than can be reached in practice. To address rack underutilization, server vendors are shipping support for per-host power caps, which provide a server-enforced limit on the... Read More

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Performance Modeling of Virtualized Custom Logic Computations
Michael J. Hall and Roger D. Chamberlain
Technical Report

Abstract:

Virtualization of custom logic computations (i.e., by sharing a fixed function across distinct data streams) provides a means of reusing hardware resources, particularly when resources are limited. This is common practice in traditional processors where more than one user can share processor resources. In this paper, we virtualize a custom logic block using C-slow techniques to support fine-grain context-switching. We then develop and present an analytic model for several performance measures (throughput, latency, input queue occupancy) for both fine-grained and coarse-grained context switching (to a secondary memory). Next, we calibrate... Read More

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Global EDF Scheduling for Parallel Real-Time Tasks, Jing Li

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Federated Scheduling for Stochastic Parallel Real-time Tasks
Jing Li, Kunal Agrawal, Christopher Gill, and Chenyang Lu
Technical Report

Abstract:

Federated scheduling is a strategy to schedule parallel real-time tasks: It allocates a dedicated cluster of cores to high-utilization task (utilization >1); It uses a multiprocessor scheduling algorithm to schedule and execute all low-utilization tasks sequentially, on a shared cluster of the remaining cores. Prior work has shown that federated scheduling has the best known capacity augmentation bound of 2 for parallel tasks with implicit deadlines. In this paper, we explore the soft real-time performance of federated scheduling and address the average-case workloads instead of the worst-case values. In particular,... Read More

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Capacity Augmentation Bound of Federated Scheduling for Parallel DAG Tasks
Jing Li, Abusayeed Saifullah, Kunal Agrawal, and Christopher Gill
Technical Report

Abstract:

We present a novel federated scheduling approach for parallel real-time tasks under a general directed acyclic graph (DAG) model. We provide a capacity augmentation bound of 2 for hard real-time scheduling; here we use the worst-case execution time and critical-path length of tasks to determine schedulability. This is the best known capacity augmentation bound for parallel tasks. By constructing example task sets, we further show that the lower bound on capacity augmentation of federated scheduling is also 2 for any m > 2. Hence, the gap is closed and bound... Read More

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Streaming Computations with Precise Control
Peng Li, Kunal Agrawal, Jeremy Buhler, and Roger Chamberlain
Technical Report

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Migrating to IPv6 - The Role of Basic Coordination
Mehdi Nikkhah and Roch Guerin
Conference Paper

Abstract:

The need for a larger Internet address space was acknowledged early on, and a solution (IPv6) standardized years ago. Its adoption has, however, been anything but easy and still faces significant challenges. The situation begs the questions of "why has it been so difficult?" and "what could have been (or still be) done to facilitate this migration?" There has been significant recent interest in those questions, and the paper builds on a line of work based on technology adoption models to explore them. The results confirm the impact of several... Read More

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Software Defined Application Delivery Networking, Subharthi Paul

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Real-Time Wireless Sensor-Actuator Networks for Cyber-Physical Systems, Abusayeed Saifullah

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Inferring Memory Map Instructions
Paul T. Scheid, Ari J. Spilo, and Ron K. Cytron
MS Project Report

Abstract:

We describe the problem of inferring a set of memory map instructions from a reference trace, with the goal of minimizing the number of such instructions as well as the number of unreferenced but mapped storage locations. We prove the related decision problem NP-complete. We then present and compare the results of two heuristic approaches on some actual traces.

... Read More

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Wireless Sensor Networking in Challenging Environments, Mo Sha

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On the Analysis of DNA Methylation, Michael Stevens

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Real-Time Virtualization and Cloud Computing, Sisu Xi

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RT-OpenStack: a Real-Time Cloud Management System
Sisu Xi, Chong Li, Chenyang Lu, Christopher D. Gill, Meng Xu, Linh T.X. Phan, Insup Lee, and Oleg Sokolsky
Technical Report

Abstract:

Clouds have become appealing platforms for running not only general-purpose applications but also real-time applications. However, current clouds cannot provide real-time performance for virtual machines (VM) for two reasons: (1) the lack of a real-time virtual machine monitor (VMM) scheduler on a single host, and (2) the lack of a real-time aware VM placement scheme by the cloud manager. While real-time VM schedulers do exist, prior solutions employ either heuristics-based approaches that cannot always achieve predictable latency or apply real-time scheduling theory that may result in low CPU utilization. We... Read More

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Supervised Machine Learning Under Test-Time Resource Constraints: A Trade-off Between Accuracy and Cost, Zhixiang Xu

Research from 2013

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Simple Analytic Performance Models for Streaming Data Applications Deployed on Diverse Architectures
Jonathan C. Beard, Roger D. Chamberlain, and Mark A. Franklin
Technical Report

Abstract:

Modern hardware is inherently heterogeneous. With heterogeneity comes multiple abstraction layers that hide underlying complex systems. While hidden, this complexity makes quantitative performance modeling a difficult task. Designers of high-performance streaming applications for heterogeneous systems must contend with unpredictable and often non-generalizable models to predict performance of a particular application and hardware mapping. This paper outlines a computationally simple approach that can be used to model the overall throughput and buffering needs of a streaming application on heterogeneous hardware. The model presented is based upon a hybrid maximum flow and... Read More

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Learning with Single View Co-training and Marginalized Dropout, Minmin Chen

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Difficulties and Opportunities in Building Resilient Clinical Monitoring Systems with Wireless Sensor Networks, Rahav Dor

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Delivering Consistent Network Performance in Multi-tenant Data Centers, Mart Albert Haitjema

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Kernel Density Metric Learning
Yujie He, Wenlin Chen, and Yixin Chen
Technical Report

Abstract:

This paper introduces a supervised metric learning algorithm, called kernel density metric learning (KDML), which is easy to use and provides nonlinear, probability-based distance measures. KDML constructs a direct nonlinear mapping from the original input space into a feature space based on kernel density estimation. The nonlinear mapping in KDML embodies established distance measures between probability density functions, and leads to correct classification on datasets for which linear metric learning methods would fail. Existing metric learning algorithms, such as large margin nearest neighbors (LMNN), can then be applied to the... Read More

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Wireless Cyber-Physical Simulator and Case Studies on Structural Control, Bo Li

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Adding Data Parallelism to Streaming Pipelines for Throughput Optimization
Peng Li, Kunal Agrawal, Jeremy Buhler, and Roger D. Chamberlain
Technical Report

Abstract:

The streaming model is a popular model for writing high-throughput parallel applications. A streaming application is represented by a graph of computation stages that communicate with each other via FIFO channels. In this report, we consider the problem of mapping streaming pipelines — streaming applications where the graph is a linear chain — in order to maximize throughput. In a parallel setting, subsets of stages, called components can be mapped onto different computing resources. The through-put of an application is determined by the throughput of the slowest component. Therefore, if... Read More

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Efficient Parallel Real-Time Upsampling of Ultrasound Vectors
William D. Richard Ph.D.
Technical Report

Abstract:

Upsampling is required prior to the summation step in most receive digital beamforming implementations to produce an accurate summed RF line or vector. This is true in both annular and linear array systems where receive echos are digitized first and then time delayed in the digital domain to achieve proper signal alignment. The efficient, parallel, real-time upsampling circuit presented here produces M upsampled values per ADC clock, where M is the desired upsampling factor. A circuit implementation that upsamples by a factor of M=4 is presented as an example of... Read More

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Parallel Real-Time Scheduling of DAGs
Abusayeed Saifullah, David Ferry, Jing Li, Kunal Agrawal, Chenyang Lu, and Christopher Gill
Technical Report

Abstract:

Recently, multi-core processors have become mainstream in processor design. To take full advantage of multi-core processing, computation-intensive real-time systems must exploit intra-task parallelism. In this paper, we address the open problem of real-time scheduling for a general model of deterministic parallel tasks, where each task is represented as a directed acyclic graph (DAG) with nodes having arbitrary execution requirements. We prove processor-speed augmentation bounds for both preemptive and non-preemptive real-time scheduling for general DAG tasks on multi-core processors. We first decompose each DAG into sequential tasks with their own release... Read More

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Self-Adapting MAC Layer for Wireless Sensor Networks
Mo Sha, Meng Xu, Chenyang Lu, Linh T.X. Phan, Tae-Suk Kim, and Taerim Park
Technical Report

Abstract:

The integration of wireless sensors with mobile phones is gaining momentum as an enabling platform for numerous emerging applications. These mobile systems face dynamic environments where both application requirements and ambient wireless conditions change frequently. Despite the existence of many MAC protocols however, none can provide optimal performance along multiple dimensions, in particular when the conditions are frequently changing. Instead of pursuing a one-MAC-fit all approach we present a Self-Adapting MAC Layer (SAML) comprising (1) a Reconfigurable MAC Architecture (RMA) that can switch to different MAC protocols at run time... Read More

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Automated Color Calibration of Display Devices
Andrew Shulman
Technical Report

Abstract:

If you compare two identical images on two different monitors, they will likely appear different. Every display device is supposed to adhere to a particular set of standards regulating the color and intensity of the image it outputs. However, in practice, very few do. Color calibration is the practice of modifying the signal path such that the colors produced more closely match reference standards. This is essential for graphics professionals who are mastering original content. They must ensure that the source material appears correct when viewed on a reference monitor.... Read More

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End-to-End Delay Analysis for Wireless Control Networks under EDF Scheduling, Chengjie Wu

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EWA Model with Recency Effect and Limited Memory
Hang Xie
Technical Report

Abstract:

Game theory is an important field in economics; it studies how people make decisions amid conflict and cooperation. Various experiments have been carried to study the way people play those games, and economists study those data for various purposes. There has been a rise of need for using artificial agents to simulate the game, since we could save the cost of hiring human subjects for the experiments, and we could gain more control over the experiment settings.

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Real-Time Multi-Core Virtual Machine Scheduling in Xen
Sisu Xi, Meng Xu, Chenyang Lu, Linh T.X. Phan, Christopher Gill, Olga Sokolsky, and Insup Lee
Technical Report

Abstract:

Recent years have witnessed two major trends in the development of complex real-time systems. First, to reduce cost and enhance flexibility, multiple systems are sharing common computing platforms via virtualization technology, instead of being deployed separately on physically isolated hosts. Second, multicore processors are increasingly being used in real-time systems. The integration of real-time systems as virtual machines (VMs) atop common multicore platforms raises significant new research challenges in meeting the real-time performance requirements of multiple systems.

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Scanner: An Efficient and Accurate Trimming Tool for Illumina Next Generation Sequencing Reads
Xiang Zhou
Technical Report

Abstract:

Recent advances in High-Throughput Sequencing (HTS) technology have greatly facilitated the researches in bioinformatics field. With the ultra-high sequencing speed and improved base-calling accuracy, Illumina Genome Analyzer is currently the most widely used platform in the field. To use the raw reads generated from the sequencing machine, the 3’ adapter sequence attached to the real read in the process of ligation needs to be correctly trimmed. This is often done by some inhouse scripts or different packages with various parameters. They either use the Smith-Waterman algorithm or search for an... Read More

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An Algorithm for Triangulating 3D Polygons, Ming Zou

Research from 2012

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Common DMA Engine Interface
Roger Alessi
Technical Report

Abstract:

Circuit boards with Field Programmable Gate Arrays (FPGAs) have a historically diverse set of standards for communicating with other devices. This provides a challenge for developers creating FPGA applications and makes migration of applications from one board or FPGA to another difficult. Many board manufacturers, including Xilinx and GiDEL, create boards with Peripheral Component Interconnect Express (PCIe) buses. PCIe provides a low-level standard for transferring data between a Central Processing Unit (CPU) and an FPGA, and these manufacturers have designed Direct Memory Access (DMA) engines to implement the standard. However,... Read More

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Kinect Hand Recognition and Tracking
Alex Drake
Technical Report

Abstract:

he goal of this research project was to be able to identify and track a hand using the depth image from a Microsoft Kinect. The ability to do this would have uses in sign language recognition, rehabilitation, and gesture recognition amongst others. The Microsoft Kinect is currently capable of identifying and tracking whole bodies. Our approach was to follow the method that Microsoft used but apply it to detailed hand recognition instead of the body. The basic strategy they used was to take a large amount of labeled depth data... Read More

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Rapid Development Environments for Therapy Games: Looking Glass Therapy Games for Cerebral Palsy Treatment Utilizing the Kinect
Melynda Eden
Technical Report

Abstract:

Cerebral palsy is a group of neurological disorders that impair body movement, muscle coordination, hearing, vision, and cognitive function. Symptoms vary but can include muscle weakness, muscle and joint tightness, abnormal or unsteady gait, seizures, learning disabilities, speech problems, as well as hearing or vision problems [1]. Although cerebral palsy cannot be cured, treatments such as physical and occupational therapy can greatly help affected children develop motor skills needed to increase mobility and foster independence [2]. Computer based therapy games have shown promise in helping stroke survivors recover from stroke... Read More

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Implementation of Real-Time Calibration of Polarization Imaging Sensors
Collin Foster
Technical Report

Abstract:

Recent breakthroughs in nanofabrication techniques have led to development of sophisticated Division-of-Focal-Plane (DoFP) polarization imaging sensors. One such technique allows the fabrication of nanowire filters fabricated directly on the imaging sensor itself. This technique can be used to fabricate robust DoFP polarization imaging sensors. However, the polarization information captured by the imagers can be degraded due to imperfections in the fabrication of the nanowire filters on the imaging sensor. Polarization information can also be degraded from other sources including crosstalk between pixels. To compensate for these undesired effects, a calibration... Read More

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Reading Your Own Mind: Dynamic Visualization of Real-Time Neural Signals, Zachary V. Freudenburg

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Just Draw It! A 3D Sketching System
Cindy Grimm and Pushkar Joshi
Technical Report

Abstract:

We present a system for sketching in 2D to create 3D curves. The interface is light-weight, pen-based, and based on observations of how artists sketch on paper.

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Practical Approaches to Biological Network Discovery, Brian Haynes