Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- San Jose State University (4)
- University of Kentucky (4)
- City University of New York (CUNY) (2)
- University of Massachusetts Amherst (2)
- University of New Orleans (2)
-
- California Polytechnic State University, San Luis Obispo (1)
- California State University, San Bernardino (1)
- Dartmouth College (1)
- Louisiana State University (1)
- Michigan Technological University (1)
- Minnesota State University, Mankato (1)
- Old Dominion University (1)
- Singapore Management University (1)
- University of Arkansas, Fayetteville (1)
- University of Louisville (1)
- University of Nevada, Las Vegas (1)
- University of Tennessee, Knoxville (1)
- Western Michigan University (1)
- Keyword
-
- Community detection (2)
- Delay tolerant network (2)
- API hooks (1)
- Algorithms (1)
- Anomaly Detection (1)
-
- Anomaly detection (1)
- Attractors (1)
- Battery (1)
- Blockchain (1)
- BookSim (1)
- CAmkES (1)
- COVID-19 (1)
- Cellular automata (1)
- Citrix (1)
- Coding Theory (1)
- Cognitive radio networks (1)
- Complex adaptive systems (1)
- Computer Science (1)
- Computer algorithms (1)
- Computer system health monitoring (1)
- Cyber security (1)
- DAG (1)
- Data Streams (1)
- Data protection (1)
- Decentralized POMDP (1)
- Denial-of-service (DoS). Internet Control Message Protocol (ICMP). User Datagram Protocol (UDP). Open Systems Interconnection Layers Attacks (OSI). Self-Organize-Map (SOM). Multilayer perceptron (MLP). (1)
- Distributed Computing (1)
- Distributed computing (1)
- Dynamical systems (1)
- Electricity grid (1)
- Publication Year
- Publication
-
- Master's Projects (4)
- Theses and Dissertations--Computer Science (4)
- Dissertations, Theses, and Capstone Projects (2)
- Doctoral Dissertations (2)
- University of New Orleans Theses and Dissertations (2)
-
- All Graduate Theses, Dissertations, and Other Capstone Projects (1)
- Computer Science Theses & Dissertations (1)
- Computer Science and Computer Engineering Undergraduate Honors Theses (1)
- Dartmouth College Undergraduate Theses (1)
- Dissertations (1)
- Dissertations and Theses Collection (Open Access) (1)
- Dissertations, Master's Theses and Master's Reports (1)
- Electronic Theses and Dissertations (1)
- Electronic Theses, Projects, and Dissertations (1)
- LSU Master's Theses (1)
- Master's Theses (1)
- Masters Theses (1)
- UNLV Theses, Dissertations, Professional Papers, and Capstones (1)
Articles 1 - 27 of 27
Full-Text Articles in OS and Networks
Improving Connectivity For Remote Cancer Patient Symptom Monitoring And Reporting In Rural Medically Underserved Regions, Esther Max-Onakpoya
Improving Connectivity For Remote Cancer Patient Symptom Monitoring And Reporting In Rural Medically Underserved Regions, Esther Max-Onakpoya
Theses and Dissertations--Computer Science
Rural residents are often faced with many disparities when compared to their urban counterparts. Two key areas where these disparities are apparent are access to health and Internet services. Improved access to healthcare services has the potential to increase residents' quality of life and life expectancy. Additionally, improved access to Internet services can create significant social returns in increasing job and educational opportunities, and improving access to healthcare. Therefore, this dissertation focuses on the intersection between access to Internet and healthcare services in rural areas. More specifically, it attempts to analyze systems that can be used to improve Internet access …
Coded Distributed Function Computation, Pedro J. Soto
Coded Distributed Function Computation, Pedro J. Soto
Dissertations, Theses, and Capstone Projects
A ubiquitous problem in computer science research is the optimization of computation on large data sets. Such computations are usually too large to be performed on one machine and therefore the task needs to be distributed amongst a network of machines. However, a common problem within distributed computing is the mitigation of delays caused by faulty machines. This can be performed by the use of coding theory to optimize the amount of redundancy needed to handle such faults. This problem differs from classical coding theory since it is concerned with the dynamic coded computation on data rather than just statically …
Counting And Sampling Small Structures In Graph And Hypergraph Data Streams, Themistoklis Haris
Counting And Sampling Small Structures In Graph And Hypergraph Data Streams, Themistoklis Haris
Dartmouth College Undergraduate Theses
In this thesis, we explore the problem of approximating the number of elementary substructures called simplices in large k-uniform hypergraphs. The hypergraphs are assumed to be too large to be stored in memory, so we adopt a data stream model, where the hypergraph is defined by a sequence of hyperedges.
First we propose an algorithm that (ε, δ)-estimates the number of simplices using O(m1+1/k / T) bits of space. In addition, we prove that no constant-pass streaming algorithm can (ε, δ)- approximate the number of simplices using less than O( m 1+1/k / T ) bits of space. Thus …
Fake News Analysis And Graph Classification On A Covid-19 Twitter Dataset, Kriti Gupta
Fake News Analysis And Graph Classification On A Covid-19 Twitter Dataset, Kriti Gupta
Master's Projects
Earlier researches have showed that the spread of fake news through social media can have a huge impact to society and also to individuals in an extremely negative way. In this work we aim to study the spread of fake news compared to real news in a social network. We do that by performing classical social network analysis to discover various characteristics, and formulate the problem as a binary classification, where we have graphs modeling the spread of fake and real news. For our experiments we rely on how news are propagated through a popular social media services such as …
Semi-Supervised Spatial-Temporal Feature Learning On Anomaly-Based Network Intrusion Detection, Huy Mai
Semi-Supervised Spatial-Temporal Feature Learning On Anomaly-Based Network Intrusion Detection, Huy Mai
Computer Science and Computer Engineering Undergraduate Honors Theses
Due to a rapid increase in network traffic, it is growing more imperative to have systems that detect attacks that are both known and unknown to networks. Anomaly-based detection methods utilize deep learning techniques, including semi-supervised learning, in order to effectively detect these attacks. Semi-supervision is advantageous as it doesn't fully depend on the labelling of network traffic data points, which may be a daunting task especially considering the amount of traffic data collected. Even though deep learning models such as the convolutional neural network have been integrated into a number of proposed network intrusion detection systems in recent years, …
Xtreme-Noc: Extreme Gradient Boosting Based Latency Model For Network-On-Chip Architectures, Ilma Sheriff
Xtreme-Noc: Extreme Gradient Boosting Based Latency Model For Network-On-Chip Architectures, Ilma Sheriff
All Graduate Theses, Dissertations, and Other Capstone Projects
Multiprocessor System-on-Chip (MPSoC) integrating heterogeneous processing elements (CPU, GPU, Accelerators, memory, I/O modules ,etc.) are the de-facto design choice to meet the ever-increasing performance/Watt requirements from modern computing machines. Although at consumer level the number of processing elements (PE) are limited to 8-16, for high end servers, the number of PEs can scale up to hundreds. A Network-on-Chip (NoC) is a microscale network that facilitates the packetized communication among the PEs in such complex computational systems. Due to the heterogeneous integration of the cores, execution of diverse (serial and parallel) applications on the PEs, application mapping strategies, and many other …
Algorithms For Massive, Expensive, Or Otherwise Inconvenient Graphs, David Tench
Algorithms For Massive, Expensive, Or Otherwise Inconvenient Graphs, David Tench
Doctoral Dissertations
A long-standing assumption common in algorithm design is that any part of the input is accessible at any time for unit cost. However, as we work with increasingly large data sets, or as we build smaller devices, we must revisit this assumption. In this thesis, I present some of my work on graph algorithms designed for circumstances where traditional assumptions about inputs do not apply.
1. Classical graph algorithms require direct access to the input graph and this is not feasible when the graph is too large to fit in memory. For computation on massive graphs we consider the dynamic …
Accelerating The Information-Theoretic Approach Of Community Detection Using Distributed And Hybrid Memory Parallel Schemes, Md Abdul Motaleb Faysal
Accelerating The Information-Theoretic Approach Of Community Detection Using Distributed And Hybrid Memory Parallel Schemes, Md Abdul Motaleb Faysal
University of New Orleans Theses and Dissertations
There are several approaches for discovering communities in a network (graph). Despite being approximating in nature, discovering communities based on the laws of Information Theory has a proven standard of accuracy. The information-theoretic algorithm known as Infomap developed a decade ago for detecting communities, did not foresee the tremendous growth of social networking, multimedia, and massive information boom. To discover communities in massive networks, we have designed a distributed-memory-parallel Infomap in the MPI framework. Our design reaches scalability of over 500 processes capable of processing networks with millions of edges while maintaining quality comparable to the sequential Infomap. We have …
Automated Extraction Of Network Activity From Memory Resident Code, Austin Nicholas Sellers
Automated Extraction Of Network Activity From Memory Resident Code, Austin Nicholas Sellers
LSU Master's Theses
Advancements in malware development, including the use of file-less and memory-only payloads, have led to a significant interest in the use of volatile memory analysis by digital forensics practitioners. Memory analysis can uncover a wealth of information not available via traditional analysis, such as the discovery of injected code, hooked APIs, and more. Unfortunately, the process of analyzing such malicious code is largely left to analysts who must manually reverse engineer the code to discover its intent. This task is not only slow and error-prone, but is also generally left only to senior-level analysts to perform, given that significant reverse …
Software-Defined Infrastructure For Iot-Based Energy Systems, Stephen Lee
Software-Defined Infrastructure For Iot-Based Energy Systems, Stephen Lee
Doctoral Dissertations
Internet of Things (IoT) devices are becoming an essential part of our everyday lives. These physical devices are connected to the internet and can measure or control the environment around us. Further, IoT devices are increasingly being used to monitor buildings, farms, health, and transportation. As these connected devices become more pervasive, these devices will generate vast amounts of data that can be used to gain insights and build intelligence into the system. At the same time, large-scale deployment of these devices will raise new challenges in efficiently managing and controlling them. In this thesis, I argue that the IoT …
Formally Designing And Implementing Cyber Security Mechanisms In Industrial Control Networks., Mehdi Sabraoui
Formally Designing And Implementing Cyber Security Mechanisms In Industrial Control Networks., Mehdi Sabraoui
Electronic Theses and Dissertations
This dissertation describes progress in the state-of-the-art for developing and deploying formally verified cyber security devices in industrial control networks. It begins by detailing the unique struggles that are faced in industrial control networks and why concepts and technologies developed for securing traditional networks might not be appropriate. It uses these unique struggles and examples of contemporary cyber-attacks targeting control systems to argue that progress in securing control systems is best met with formal verification of systems, their specifications, and their security properties. This dissertation then presents a development process and identifies two technologies, TLA+ and seL4, that can be …
Network Alignment In Heterogeneous Social Networks, Priyanka Kasbekar
Network Alignment In Heterogeneous Social Networks, Priyanka Kasbekar
Master's Projects
Online Social Networks (OSN) have numerous applications and an ever growing user base. This has led to users being a part of multiple social networks at the same time. Identifying a similar user from one social network on another social network will give in- formation about a user’s behavior on different platforms. It further helps in community detection and link prediction tasks. The process of identifying or aligning users in multiple networks is called Network Alignment. More the information we have about the nodes / users better the results of Network Alignment. Unlike other related work in this field that …
Optimal Gateway Placement In Low-Cost Smart Cities, Oluwashina Madamori
Optimal Gateway Placement In Low-Cost Smart Cities, Oluwashina Madamori
Theses and Dissertations--Computer Science
Rapid urbanization burdens city infrastructure and creates the need for local governments to maximize the usage of resources to serve its citizens. Smart city projects aim to alleviate the urbanization problem by deploying a vast amount of Internet-of-things (IoT) devices to monitor and manage environmental conditions and infrastructure. However, smart city projects can be extremely expensive to deploy and manage partly due to the cost of providing Internet connectivity via 5G or WiFi to IoT devices. This thesis proposes the use of delay tolerant networks (DTNs) as a backbone for smart city communication; enabling developing communities to become smart cities …
Reinforcement Learning For Collective Multi-Agent Decision Making, Duc Thien Nguyen
Reinforcement Learning For Collective Multi-Agent Decision Making, Duc Thien Nguyen
Dissertations and Theses Collection (Open Access)
In this thesis, we study reinforcement learning algorithms to collectively optimize decentralized policy in a large population of autonomous agents. We notice one of the main bottlenecks in large multi-agent system is the size of the joint trajectory of agents which quickly increases with the number of participating agents. Furthermore, the noiseof actions concurrently executed by different agents in a large system makes it difficult for each agent to estimate the value of its own actions, which is well-known as the multi-agent credit assignment problem. We propose a compact representation for multi-agent systems using the aggregate counts to address …
Ultra-Fast And Memory-Efficient Lookups For Cloud, Networked Systems, And Massive Data Management, Ye Yu
Ultra-Fast And Memory-Efficient Lookups For Cloud, Networked Systems, And Massive Data Management, Ye Yu
Theses and Dissertations--Computer Science
Systems that process big data (e.g., high-traffic networks and large-scale storage) prefer data structures and algorithms with small memory and fast processing speed. Efficient and fast algorithms play an essential role in system design, despite the improvement of hardware. This dissertation is organized around a novel algorithm called Othello Hashing. Othello Hashing supports ultra-fast and memory-efficient key-value lookup, and it fits the requirements of the core algorithms of many large-scale systems and big data applications. Using Othello hashing, combined with domain expertise in cloud, computer networks, big data, and bioinformatics, I developed the following applications that resolve several major …
Morphogenesis And Growth Driven By Selection Of Dynamical Properties, Yuri Cantor
Morphogenesis And Growth Driven By Selection Of Dynamical Properties, Yuri Cantor
Dissertations, Theses, and Capstone Projects
Organisms are understood to be complex adaptive systems that evolved to thrive in hostile environments. Though widely studied, the phenomena of organism development and growth, and their relationship to organism dynamics is not well understood. Indeed, the large number of components, their interconnectivity, and complex system interactions all obscure our ability to see, describe, and understand the functioning of biological organisms.
Here we take a synthetic and computational approach to the problem, abstracting the organism as a cellular automaton. Such systems are discrete digital models of real-world environments, making them more accessible and easier to study then their physical world …
Community Detection In Social Networks, Ketki Kulkarni
Community Detection In Social Networks, Ketki Kulkarni
Master's Projects
The rise of the Internet has brought people closer. The number of interactions between people across the globe has gone substantially up due to social awareness, the advancements of the technology, and digital interaction. Social networking sites have built societies, communities virtually. Often these societies are displayed as a network of nodes depicting people and edges depicting relationships, links. This is a good and e cient way to store, model and represent systems which have a complex and rich information. Towards that goal we need to nd e ective, quick methods to analyze social networks. One of the possible solution …
Influence Detection And Spread Estimation In Social Networks, Madhura Kaple
Influence Detection And Spread Estimation In Social Networks, Madhura Kaple
Master's Projects
A social network is an online platform, where people communicate and share information with each other. Popular social network features, which make them di erent from traditional communication platforms, are: following a user, re-tweeting a post, liking and commenting on a post etc. Many companies use various social networking platforms extensively as a medium for marketing their products. A xed amount of budget is alloted by the companies to maximize the positive in uence of their product. Every social network consists of a set of users (people) with connections between them. Each user has the potential to extend its in …
Packet Filter Approach To Detect Denial Of Service Attacks, Essa Yahya M Muharish
Packet Filter Approach To Detect Denial Of Service Attacks, Essa Yahya M Muharish
Electronic Theses, Projects, and Dissertations
Denial of service attacks (DoS) are a common threat to many online services. These attacks aim to overcome the availability of an online service with massive traffic from multiple sources. By spoofing legitimate users, an attacker floods a target system with a high quantity of packets or connections to crash its network resources, bandwidth, equipment, or servers. Packet filtering methods are the most known way to prevent these attacks via identifying and blocking the spoofed attack from reaching its target. In this project, the extent of the DoS attacks problem and attempts to prevent it are explored. The attacks categories …
On The Limits And Practice Of Automatically Designing Self-Stabilization, Alex Klinkhamer
On The Limits And Practice Of Automatically Designing Self-Stabilization, Alex Klinkhamer
Dissertations, Master's Theses and Master's Reports
A protocol is said to be self-stabilizing when the distributed system executing it is guaranteed to recover from any fault that does not cause permanent damage. Designing such protocols is hard since they must recover from all possible states, therefore we investigate how feasible it is to synthesize them automatically. We show that synthesizing stabilization on a fixed topology is NP-complete in the number of system states. When a solution is found, we further show that verifying its correctness on a general topology (with any number of processes) is undecidable, even for very simple unidirectional rings. Despite these negative results, …
In Perfect Xen, A Performance Study Of The Emerging Xen Scheduler, Ryan Hnarakis
In Perfect Xen, A Performance Study Of The Emerging Xen Scheduler, Ryan Hnarakis
Master's Theses
Fifty percent of Fortune 500 companies trust Xen, an open-source bare-metal hypervisor, to virtualize their websites and mission critical services in the cloud. Providing superior fault tolerance, scalability, and migration, virtualization allows these companies to run several isolated operating systems simultaneously on the same physical server. These isolated operating systems, called virtual machines, require a virtual traffic guard to cooperate with one another. This guard known as the Credit2 scheduler along with the newest Xen hypervisor was recently developed to supersede the older schedulers. Since wasted CPU cycles can be costly, the Credit2 prototype must undergo significant performance validation before …
Reaper – Toward Automating Mobile Cloud Communication, Daniel R. Ward
Reaper – Toward Automating Mobile Cloud Communication, Daniel R. Ward
University of New Orleans Theses and Dissertations
Mobile devices connected to cloud based services are becoming a mainstream method of delivery up-to-date and context aware information to users. Connecting mobile applications to cloud service require significant developer effort. Yet this communication code usually follows certain patterns, varying accordingly to the specific type of data sent and received from the server. By analyzing the causes of theses variations, we can create a system that can automate the code creation for communication from a mobile device to a cloud server. To automate code creation, a general pattern must extracted. This general solution can then be applied to any database …
A Study Of Possible Optimizations For The Task Scheduler ‘Quark’ On The Shared Memory Architecture, Vijay Gopal Joshi
A Study Of Possible Optimizations For The Task Scheduler ‘Quark’ On The Shared Memory Architecture, Vijay Gopal Joshi
Masters Theses
Multicore processors are replacing most of the single core processors nowadays.
Current trends show that there will be increasing numbers of cores on a single chip in the coming future. However, programming multicore processors remains bug prone and less productive. Thus, making use of a runtime to schedule tasks on multicore processor hides most of the complexities of parallel programming to improve productivity. QUARK is one of the runtimes available for the multicore processors. This work looks at identifying and solving performance bottlenecks for QUARK on the shared memory architecture. The problem of finding bottlenecks is divided into two parts, …
Automatic Detection Of Abnormal Behavior In Computing Systems, James Frank Roberts
Automatic Detection Of Abnormal Behavior In Computing Systems, James Frank Roberts
Theses and Dissertations--Computer Science
I present RAACD, a software suite that detects misbehaving computers in large computing systems and presents information about those machines to the system administrator. I build this system using preexisting anomaly detection techniques. I evaluate my methods using simple synthesized data, real data containing coerced abnormal behavior, and real data containing naturally occurring abnormal behavior. I find that the system adequately detects abnormal behavior and significantly reduces the amount of uninteresting computer health data presented to a system administrator.
Message Passing Algorithm For Different Problems Sum, Mean, Guide And Sorting In A Rooted Tree Network., Sabaresh Nageswara Rao Maddula
Message Passing Algorithm For Different Problems Sum, Mean, Guide And Sorting In A Rooted Tree Network., Sabaresh Nageswara Rao Maddula
UNLV Theses, Dissertations, Professional Papers, and Capstones
In this thesis, we give message passing algorithms in distributed environment for five different problems of a rooted tree having n nodes. In the first algorithm, every node has a value; the root calculates the sum of those values, and sends it to all the nodes in the network. In the second algorithm, the root computes the value of mean of values of all the nodes, and sends it to all nodes of the network. The third algorithm calculates the guide pairs. Guide pair of a node x is an ordered pair (pre_index(x), post_index(x)), where pre_index(x) and post_index(x) are the …
Efficient Reinforcement Learning In Multiple-Agent Systems And Its Application In Cognitive Radio Networks, Jing Zhang
Efficient Reinforcement Learning In Multiple-Agent Systems And Its Application In Cognitive Radio Networks, Jing Zhang
Dissertations
The objective of reinforcement learning in multiple-agent systems is to find an efficient learning method for the agents to behave optimally. Finding Nash equilibrium has become the common learning target for the optimality. However, finding Nash equilibrium is a PPAD (Polynomial Parity Arguments on Directed graphs)-complete problem. The conventional methods can find Nash equilibrium for some special types of Markov games.
This dissertation proposes a new reinforcement learning algorithm to improve the search efficiency and effectiveness for multiple-agent systems. This algorithm is based on the definition of Nash equilibrium and utilizes the greedy and rational features of the agents. When …
Group Key Management In Wireless Ad-Hoc And Sensor Networks, Mohammed A. Moharrum
Group Key Management In Wireless Ad-Hoc And Sensor Networks, Mohammed A. Moharrum
Computer Science Theses & Dissertations
A growing number of secure group applications in both civilian and military domains is being deployed in WAHNs. A Wireless Ad-hoc Network (WARN) is a collection of autonomous nodes or terminals that communicate with each other by forming a multi-hop radio network and maintaining connectivity in a decentralized manner. A Mobile Ad-hoc Network (MANET) is a special type of WARN with mobile users. MANET nodes have limited communication, computational capabilities, and power. Wireless Sensor Networks (WSNs) are sensor networks with massive numbers of small, inexpensive devices pervasive throughout electrical and mechanical systems and ubiquitous throughout the environment that monitor and …