Computer Engineering Commons^™

Protecting Return Address Integrity For Risc-V Via Pointer Authentication, Yuhe Zhao

Masters Theses

Embedded systems based on lightweight microprocessors are becoming more prevalent in various applications. However, the security of them remains a significant challenge due to the limited resources and exposure to external threats. Especially, some of these devices store sensitive data and control critical devices, making them high-value targets for attackers. Software security is particularly important because attackers can easily access these devices on the internet and obtain control of them by injecting malware.

Return address (RA) hijacking is a common software attack technique used to compromise control flow integrity (CFI) by manipulating memory, such as return-to-libc attacks. Several methods have …

Extracting Dnn Architectures Via Runtime Profiling On Mobile Gpus, Dong Hyub Kim

Masters Theses

Due to significant investment, research, and development efforts over the past decade, deep neural networks (DNNs) have achieved notable advancements in classification and regression domains. As a result, DNNs are considered valuable intellectual property for artificial intelligence providers. Prior work has demonstrated highly effective model extraction attacks which steal a DNN, dismantling the provider’s business model and paving the way for unethical or malicious activities, such as misuse of personal data, safety risks in critical systems, or spreading misinformation. This thesis explores the feasibility of model extraction attacks on mobile devices using aggregated runtime profiles as a side-channel to leak …

An Efficient Privacy-Preserving Framework For Video Analytics, Tian Zhou

Doctoral Dissertations

With the proliferation of video content from surveillance cameras, social media, and live streaming services, the need for efficient video analytics has grown immensely. In recent years, machine learning based computer vision algorithms have shown great success in various video analytic tasks. Specifically, neural network models have dominated in visual tasks such as image and video classification, object recognition, object detection, and object tracking. However, compared with classic computer vision algorithms, machine learning based methods are usually much more compute-intensive. Powerful servers are required by many state-of-the-art machine learning models. With the development of cloud computing infrastructures, people are able …

Improving The Programmability Of Networked Energy Systems, Noman Bashir

Doctoral Dissertations

Global warming and climate change have underscored the need for designing sustainable energy systems. Sustainable energy systems, e.g., smart grids, green data centers, differ from the traditional systems in significant ways and present unique challenges to system designers and operators. First, intermittent renewable energy resources power these systems, which break the notion of infinite, reliable, and controllable power supply. Second, these systems come in varying sizes, spanning over large geographical regions. The control of these dispersed and diverse systems raises scalability challenges. Third, the performance modeling and fault detection in sustainable energy systems is still an active research area. Finally, …

Action : Adaptive Cache Block Migration In Distributed Cache Architectures, Chandra Sekhar Mummidi

Masters Theses

Increasing number of cores in chip multiprocessors (CMP) result in increasing traffic to last-level cache (LLC). Without commensurate increase in LLC bandwidth, such traffic cannot be sustained resulting in loss of performance. Further, as the number of cores increases, it is necessary to scale up the LLC size; otherwise, the LLC miss rate will rise, resulting in a loss of performance. Unfortunately, for a unified LLC with uniform cache access time, access latency increases with cache size, resulting in performance loss. Previously, researchers have proposed partitioning the cache into multiple smaller caches interconnected by a communication network which increases aggregate …

Internet Infrastructures For Large Scale Emulation With Efficient Hw/Sw Co-Design, Aiden K. Gula

Masters Theses

Connected systems are becoming more ingrained in our daily lives with the advent of cloud computing, the Internet of Things (IoT), and artificial intelligence. As technology progresses, we expect the number of networked systems to rise along with their complexity. As these systems become abstruse, it becomes paramount to understand their interactions and nuances. In particular, Mobile Ad hoc Networks (MANET) and swarm communication systems exhibit added complexity due to a multitude of environmental and physical conditions. Testing these types of systems is challenging and incurs high engineering and deployment costs. In this work, we propose a scalable MANET emulation …

Addressing Security Challenges In Embedded Systems And Multi-Tenant Fpgas, Georgios Provelengios

Doctoral Dissertations

Embedded systems and field-programmable gate arrays (FPGAs) have become crucial parts of the infrastructure that supports our modern technological world. Given the multitude of threats that are present, the need for secure computing systems is undeniably greater than ever. Embedded systems and FPGAs are governed by characteristics that create unique security challenges and vulnerabilities. Despite their array of uses, embedded systems are often built with modest microprocessors that do not support the conventional security solutions used by workstations, such as virus scanners. In the first part of this dissertation, a microprocessor defense mechanism that uses a hardware monitor to protect …

Network Virtualization And Emulation Using Docker, Openvswitch And Mininet-Based Link Emulation, Narendra Prabhu

Masters Theses

With the advent of virtualization and artificial intelligence, research on networked systems has progressed substantially. As the technology progresses, we expect a boom in not only the systems research but also in the network of systems domain. It is paramount that we understand and develop methodologies to connect and communicate among the plethora of devices and systems that exist today. One such area is mobile ad-hoc and space communication, which further complicates the task of networking due to myriad of environmental and physical conditions. Developing and testing such systems is an important step considering the large investment required to build …

Design And Implementation Of Path Finding And Verification In The Internet, Hao Cai

Doctoral Dissertations

In the Internet, network traffic between endpoints typically follows one path that is determined by the control plane. Endpoints have little control over the choice of which path their network traffic takes and little ability to verify if the traffic indeed follows a specific path. With the emergence of software-defined networking (SDN), more control over connections can be exercised, and thus the opportunity for novel solutions exists. However, there remain concerns about the attack surface exposed by fine-grained control, which may allow attackers to inject and redirect traffic. To address these opportunities and concerns, we consider two specific challenges: (1) …

Sundown: Model-Driven Per-Panel Solar Anomaly Detection For Residential Arrays, Menghong Feng

Masters Theses

There has been significant growth in both utility-scale and residential-scale solar installa- tions in recent years, driven by rapid technology improvements and falling prices. Unlike utility-scale solar farms that are professionally managed and maintained, smaller residential- scale installations often lack sensing and instrumentation for performance monitoring and fault detection. As a result, faults may go undetected for long periods of time, resulting in generation and revenue losses for the homeowner. In this thesis, we present SunDown, a sensorless approach designed to detect per-panel faults in residential solar arrays. SunDown does not require any new sensors for its fault detection and …

Towards Optimized Traffic Provisioning And Adaptive Cache Management For Content Delivery, Aditya Sundarrajan

Doctoral Dissertations

Content delivery networks (CDNs) deploy hundreds of thousands of servers around the world to cache and serve trillions of user requests every day for a diverse set of content such as web pages, videos, software downloads and images. In this dissertation, we propose algorithms to provision traffic across cache servers and manage the content they host to achieve performance objectives such as maximizing the cache hit rate, minimizing the bandwidth cost of the network and minimizing the energy consumption of the servers. Traffic provisioning is the process of determining the set of content domains hosted on the servers. We propose …

Trustworthy Systems And Protocols For The Internet Of Things, Arman Pouraghily

Doctoral Dissertations

Processor-based embedded systems are integrated into many aspects of everyday life such as industrial control, automotive systems, healthcare, the Internet of Things, etc. As Moore’s law progresses, these embedded systems have moved from simple microcontrollers to full-scale embedded computing systems with multiple processor cores and operating systems support. At the same time, the security of these devices has also become a key concern. Our main focus in this work is the security and privacy of the embedded systems used in IoT systems. In the first part of this work, we take a look at the security of embedded systems from …

Qoe-Aware Content Distribution Systems For Adaptive Bitrate Video Streaming, Divyashri Bhat

Doctoral Dissertations

A prodigious increase in video streaming content along with a simultaneous rise in end system capabilities has led to the proliferation of adaptive bit rate video streaming users in the Internet. Today, video streaming services range from Video-on-Demand services like traditional IP TV to more recent technologies such as immersive 3D experiences for live sports events. In order to meet the demands of these services, the multimedia and networking research community continues to strive toward efficiently delivering high quality content across the Internet while also trying to minimize content storage and delivery costs. The introduction of flexible and adaptable technologies …

A Parallel Direct Method For Finite Element Electromagnetic Computations Based On Domain Decomposition, Javad Moshfegh

Doctoral Dissertations

High performance parallel computing and direct (factorization-based) solution methods have been the two main trends in electromagnetic computations in recent years. When time-harmonic (frequency-domain) Maxwell's equation are directly discretized with the Finite Element Method (FEM) or other Partial Differential Equation (PDE) methods, the resulting linear system of equations is sparse and indefinite, thus harder to efficiently factorize serially or in parallel than alternative methods e.g. integral equation solutions, that result in dense linear systems. State-of-the-art sparse matrix direct solvers such as MUMPS and PARDISO don't scale favorably, have low parallel efficiency and high memory footprint. This work introduces a new …

Cmos Compatible Memristor Networks For Brain-Inspired Computing, Can Li

Doctoral Dissertations

In the past decades, the computing capability has shown an exponential growth trend, which is observed as Moore’s law. However, this growth speed is slowing down in recent years mostly because the down-scaled size of transistors is approaching their physical limit. On the other hand, recent advances in software, especially in big data analysis and artificial intelligence, call for a break-through in computing hardware. The memristor, or the resistive switching device, is believed to be a potential building block of the future generation of integrated circuits. The underlying mechanism of this device is different from that of complementary metal-oxide-semiconductor (CMOS) …

Transiency-Driven Resource Management For Cloud Computing Platforms, Prateek Sharma

Doctoral Dissertations

Modern distributed server applications are hosted on enterprise or cloud data centers that provide computing, storage, and networking capabilities to these applications. These applications are built using the implicit assumption that the underlying servers will be stable and normally available, barring for occasional faults. In many emerging scenarios, however, data centers and clouds only provide transient, rather than continuous, availability of their servers. Transiency in modern distributed systems arises in many contexts, such as green data centers powered using renewable intermittent sources, and cloud platforms that provide lower-cost transient servers which can be unilaterally revoked by the cloud operator. Transient …

Hybrid Black-Box Solar Analytics And Their Privacy Implications, Dong Chen

Doctoral Dissertations

The aggregate solar capacity in the U.S. is rising rapidly due to continuing decreases in the cost of solar modules. For example, the installed cost per Watt (W) for residential photovoltaics (PVs) decreased by 6X from 2009 to 2018 (from $8/W to $1.2/W), resulting in the installed aggregate solar capacity increasing 128X from 2009 to 2018 (from 435 megawatts to 55.9 gigawatts). This increasing solar capacity is imposing operational challenges on utilities in balancing electricity's real-time supply and demand, as solar generation is more stochastic and less predictable than aggregate demand. To address this problem, both academia and utilities have …

An Architecture Evaluation And Implementation Of A Soft Gpgpu For Fpgas, Kevin Andryc

Doctoral Dissertations

Embedded and mobile systems must be able to execute a variety of different types of code, often with minimal available hardware. Many embedded systems now come with a simple processor and an FPGA, but not more energy-hungry components, such as a GPGPU. In this dissertation we present FlexGrip, a soft architecture which allows for the execution of GPGPU code on an FPGA without the need to recompile the design. The architecture is optimized for FPGA implementation to effectively support the conditional and thread-based execution characteristics of GPGPU execution without FPGA design recompilation. This architecture supports direct CUDA compilation to a …

Analog Computing Using 1t1r Crossbar Arrays, Yunning Li

Masters Theses

Memristor is a novel passive electronic device and a promising candidate for new generation non-volatile memory and analog computing. Analog computing based on memristors has been explored in this study. Due to the lack of commercial electrical testing instruments for those emerging devices and crossbar arrays, we have designed and built testing circuits to implement analog and parallel computing operations. With the setup developed in this study, we have successfully demonstrated image processing functions utilizing large memristor crossbar arrays. We further designed and experimentally demonstrated the first memristor based field programmable analog array (FPAA), which was successfully configured for audio …

The Construction Of Open Data Portal Using Dkan For Integrate To Multiple Japanese Local Government Open Data, Toshikazu Seto, Yoshihide Sekimoto

Free and Open Source Software for Geospatial (FOSS4G) Conference Proceedings

In recent years, the Code for Japan, a civic tech community in Japan, has focused on the context of the FOSS4G. Consequently, the Japanese have published open data in more than 150 local governments, but these data are almost simply provided as a file on their website. And also CKAN portal are used less than 20 cities. In this study, we built open data platform that uses DKAN for integrated open data distribution of Japanese local governments.

Adaft: A Resource-Efficient Framework For Adaptive Fault-Tolerance In Cyber-Physical Systems, Ye Xu

Doctoral Dissertations

Cyber-physical systems frequently have to use massive redundancy to meet application requirements for high reliability. While such redundancy is required, it can be activated adaptively, based on the current state of the controlled plant. Most of the time the physical plant is in a state that allows for a lower level of fault-tolerance. Avoiding the continuous deployment of massive fault-tolerance will greatly reduce the workload of CPSs. In this dissertation, we demonstrate a software simulation framework (AdaFT) that can automatically generate the sub-spaces within which our adaptive fault-tolerance can be applied. We also show the theoretical benefits of AdaFT, and …

Analyzing Spark Performance On Spot Instances, Jiannan Tian

Masters Theses

Amazon Spot Instances provide inexpensive service for high-performance computing. With spot instances, it is possible to get at most 90% off as discount in costs by bidding spare Amazon Elastic Computer Cloud (Amazon EC2) instances. In exchange for low cost, spot instances bring the reduced reliability onto the computing environment, because this kind of instance could be revoked abruptly by the providers due to supply and demand, and higher-priority customers are first served.

To achieve high performance on instances with compromised reliability, Spark is applied to run jobs. In this thesis, a wide set of spark experiments are conducted to …

Efficient Scaling Of A Web Proxy Cluster, Hao Zhang

Masters Theses

With the continuing growth in network traffic and increasing diversity in web content, web caching, together with various network functions (NFs), has been introduced to enhance security, optimize network performance, and save expenses. In a large enterprise network with more than tens of thousands of users, a single proxy server is not enough to handle a large number of requests and turns to group processing. When multiple web cache proxies are working as a cluster, they talk with each other and share cached objects by using internet cache protocol (ICP). This leads to poor scalability.

This thesis describes the development …

Accelerated Iterative Algorithms With Asynchronous Accumulative Updates On A Heterogeneous Cluster, Sandesh Gubbi Virupaksha

Masters Theses

In recent years with the exponential growth in web-based applications the amount of data generated has increased tremendously. Quick and accurate analysis of this 'big data' is indispensable to make better business decisions and reduce operational cost. The challenges faced by modern day data centers to process big data are multi fold: to keep up the pace of processing with increased data volume and increased data velocity, deal with system scalability and reduce energy costs. Today's data centers employ a variety of distributed computing frameworks running on a cluster of commodity hardware which include general purpose processors to process big …

Processor Temperature And Reliability Estimation Using Activity Counters, Mayank Chhablani

Masters Theses

With the advent of technology scaling lifetime reliability is an emerging threat in high-performance and deadline-critical systems. High on-chip thermal gradients accelerates localised thermal elevations (hotspots) which increases the aging rate of the semiconductor devices. As a result, reliable operation of the processors has become a challenging task. Therefore, cost effective schemes for estimating temperature and reliability are crucial. In this work we present a reliability estimation scheme that is based on a light-weight temperature estimation technique that monitors hardware events. Unlike previously pro- posed hardware counter-based approaches, our approach involves a linear-temporal-feedback estimator, taking into account the effects of …

Modifying Instruction Sets In The Gem5 Simulator To Support Fault Tolerant Designs, Chuan Zhang

Masters Theses

Traditional fault tolerant techniques such as hardware or time redundancy incur high overhead and are inefficient for checking arithmetic operations. Our objective is to study an alternative approach of adding new instructions to check arithmetic operations. These checking instructions either rely on error detecting code or calculate approximate results and consequently, consume much less execution time. To evaluate the effectiveness of such an approach we wish to modify several benchmarks to use checking instructions and run simulation experiments to find out their execution time and memory usage. However, the checking instructions are not included in the instruction set and as …

Skybridge: A New Nanoscale 3-D Computing Framework For Future Integrated Circuits, Mostafizur Rahman

Doctoral Dissertations

Continuous scaling of CMOS has been the major catalyst in miniaturization of integrated circuits (ICs) and crucial for global socio-economic progress. However, continuing the traditional way of scaling to sub-20nm technologies is proving to be very difficult as MOSFETs are reaching their fundamental performance limits [1] and interconnection bottleneck is dominating IC operational power and performance [2]. Migrating to 3-D, as a way to advance scaling, has been elusive due to inherent customization and manufacturing requirements in CMOS architecture that are incompatible with 3-D organization. Partial attempts with die-die [3] and layer-layer [4] stacking have their own limitations [5]. We …

On Thermal Sensor Calibration And Software Techniques For Many-Core Thermal Management, Shiting Lu

Doctoral Dissertations

The high power density of a many-core processor results in increased temperature which negatively impacts system reliability and performance. Dynamic thermal management applies thermal-aware techniques at run time to avoid overheating using temperature information collected from on-chip thermal sensors. Temperature sensing and thermal control schemes are two critical technologies for successfully maintaining thermal safety. In this dissertation, on-line thermal sensor calibration schemes are developed to provide accurate temperature information. Software-based dynamic thermal management techniques are proposed using calibrated thermal sensors. Due to process variation and silicon aging, on-chip thermal sensors require periodic calibration before use in DTM. However, the calibration …

Design And Implementation Of An Economy Plane For The Internet, Xinming Chen

Doctoral Dissertations

The Internet has been very successful in supporting many network applications. As the diversity of uses for the Internet has increased, many protocols and services have been developed by the industry and the research community. However, many of them failed to get deployed in the Internet. One challenge of deploying these novel ideas in operational network is that the network providers need to be involved in the process. Many novel network protocols and services, like multicast and end-to-end QoS, need the support from network providers. However, since network providers are typically driven by business reasons, if they can not get …

Physically Equivalent Intelligent Systems For Reasoning Under Uncertainty At Nanoscale, Santosh Khasanvis

Doctoral Dissertations

Machines today lack the inherent ability to reason and make decisions, or operate in the presence of uncertainty. Machine-learning methods such as Bayesian Networks (BNs) are widely acknowledged for their ability to uncover relationships and generate causal models for complex interactions. However, their massive computational requirement, when implemented on conventional computers, hinders their usefulness in many critical problem areas e.g., genetic basis of diseases, macro finance, text classification, environment monitoring, etc. We propose a new non-von Neumann technology framework purposefully architected across all layers for solving these problems efficiently through physical equivalence, enabled by emerging nanotechnology. The architecture builds …