Physical Sciences and Mathematics Commons^™

Optimizing Collective Communication For Scalable Scientific Computing And Deep Learning, Jiali Li

Doctoral Dissertations

In the realm of distributed computing, collective operations involve coordinated communication and synchronization among multiple processing units, enabling efficient data exchange and collaboration. Scientific applications, such as simulations, computational fluid dynamics, and scalable deep learning, require complex computations that can be parallelized across multiple nodes in a distributed system. These applications often involve data-dependent communication patterns, where collective operations are critical for achieving high performance in data exchange. Optimizing collective operations for scientific applications and deep learning involves improving the algorithms, communication patterns, and data distribution strategies to minimize communication overhead and maximize computational efficiency.

Within the context of this …

Health Care Equity Through Intelligent Edge Computing And Augmented Reality/Virtual Reality: A Systematic Review, Vishal Lakshminarayanan, Aswathy Ravikumar, Harini Sriraman, Sujatha Alla, Vijay Kumar Chattu

Engineering Management & Systems Engineering Faculty Publications

Intellectual capital is a scarce resource in the healthcare industry. Making the most of this resource is the first step toward achieving a completely intelligent healthcare system. However, most existing centralized and deep learning-based systems are unable to adapt to the growing volume of global health records and face application issues. To balance the scarcity of healthcare resources, the emerging trend of IoMT (Internet of Medical Things) and edge computing will be very practical and cost-effective. A full examination of the transformational role of intelligent edge computing in the IoMT era to attain health care equity is offered in this …

Towards Practicalization Of Blockchain-Based Decentralized Applications, Songlin He

Dissertations

Blockchain can be defined as an immutable ledger for recording transactions, maintained in a distributed network of mutually untrusting peers. Blockchain technology has been widely applied to various fields beyond its initial usage of cryptocurrency. However, blockchain itself is insufficient to meet all the desired security or efficiency requirements for diversified application scenarios. This dissertation focuses on two core functionalities that blockchain provides, i.e., robust storage and reliable computation. Three concrete application scenarios including Internet of Things (IoT), cybersecurity management (CSM), and peer-to-peer (P2P) content delivery network (CDN) are utilized to elaborate the general design principles for these two main …

Practical Considerations And Applications For Autonomous Robot Swarms, Rory Alan Hector

LSU Doctoral Dissertations

In recent years, the study of autonomous entities such as unmanned vehicles has begun to revolutionize both military and civilian devices. One important research focus of autonomous entities has been coordination problems for autonomous robot swarms. Traditionally, robot models are used for algorithms that account for the minimum specifications needed to operate the swarm. However, these theoretical models also gloss over important practical details. Some of these details, such as time, have been considered before (as epochs of execution). In this dissertation, we examine these details in the context of several problems and introduce new performance measures to capture practical …

Optimization Of Real-Time Wireless Sensor Based Big Data With Deep Autoencoder Network: A Tourism Sector Application With Distributed Computing, Beki̇r Aksoy, Utku Kose

Turkish Journal of Electrical Engineering and Computer Sciences

Internet usage has increased rapidly with the development of information communication technologies. The increase in internet usage led to the growth of data volumes on the internet and the emergence of the big data concept. Therefore, it has become even more important to analyze the data and make it meaningful. In this study, 690 million queries and approximately 5.9 quadrillion data collected daily from different servers were recorded on the Redis servers by using real-time big data analysis method and load balance structure for a company operating in the tourism sector. Here, wireless networks were used as a triggering factor …

Toward Energy Efficient Systems Design For Data Centers, Bing Luo

Wayne State University Dissertations

Surge growth of numerous cloud services, Internet of Things, and edge computing promotes continuous increasing demand for data centers worldwide. Significant electricity consumption of data centers has tremendous implications on both operating and capital expense. The power infrastructure, along with the cooling system cost a multi-million or even billion dollar project to add new data center capacities. Given the high cost of large-scale data centers, it is important to fully utilize the capacity of data centers to reduce the Total Cost of Ownership. The data center is designed with a space budget and power budget. With the adoption of high-density …

Storage Systems For Mobile-Cloud Applications, Nafize R. Paiker

Dissertations

Mobile devices have become the major computing platform in todays world. However, some apps on mobile devices still suffer from insufficient computing and energy resources. A key solution is to offload resource-demanding computing tasks from mobile devices to the cloud. This leads to a scenario where computing tasks in the same application run concurrently on both the mobile device and the cloud.

This dissertation aims to ensure that the tasks in a mobile app that employs offloading can access and share files concurrently on the mobile and the cloud in a manner that is efficient, consistent, and transparent to locations. …

Itu-Prp: Parallel And Distributed Computing Middleware For Java Developers, Enis Spahi, D. Turgay Altilar

International Journal of Business and Technology

ITU-PRP provides a Parallel Programming Framework for Java Developers on which they can adapt their sequential application code to operate on a distributed multi-host parallel environment. Developers would implement parallel models, such as Loop Parallelism, Divide and Conquer, Master-Slave and Fork-Join by the help of an API Library provided under framework. Produced parallel applications would be submitted to a middleware called Parallel Running Platform (PRP), on which parallel resources for parallel processing are being organized and performed. The middleware creates Task Plans (TP) according to application’s parallel model, assigns best available resource Hosts, in order to perform fast parallel processing. …

Distributed Iterative Graph Processing Using Nosql With Data Locality, Ayam Pokhrel

LSU Master's Theses

A tremendous amount of data is generated every day from a wide range of sources such as social networks, sensors, and application logs. Among them, graph data is one type that represents valuable relationships between various entities. Analytics of large graphs has become an essential part of business processes and scientific studies because it leads to deep and meaningful insights into the related domain based on the connections between various entities. However, the optimal processing of large-scale iterative graph computations is very challenging due to the issues like fault tolerance, high memory requirement, parallelization, and scalability. Most of the contemporary …

Automated Tree-Level Forest Quantification Using Airborne Lidar, Hamid Hamraz

Theses and Dissertations--Computer Science

Traditional forest management relies on a small field sample and interpretation of aerial photography that not only are costly to execute but also yield inaccurate estimates of the entire forest in question. Airborne light detection and ranging (LiDAR) is a remote sensing technology that records point clouds representing the 3D structure of a forest canopy and the terrain underneath. We present a method for segmenting individual trees from the LiDAR point clouds without making prior assumptions about tree crown shapes and sizes. We then present a method that vertically stratifies the point cloud to an overstory and multiple understory tree …

Remote Sensing Of Forests Using Discrete Return Airborne Lidar, Hamid Hamraz, Marco A. Contreras

Forestry and Natural Resources Faculty Publications

Airborne discrete return light detection and ranging (LiDAR) point clouds covering forested areas can be processed to segment individual trees and retrieve their morphological attributes. Segmenting individual trees in natural deciduous forests, however, remained a challenge because of the complex and multi-layered canopy. In this chapter, we present (i) a robust segmentation method that avoids a priori assumptions about the canopy structure, (ii) a vertical canopy stratification procedure that improves segmentation of understory trees, (iii) an occlusion model for estimating the point density of each canopy stratum, and (iv) a distributed computing approach for efficient processing at the forest level. …

Programming Frameworks For Mobile Sensing, Hillol Debnath

Dissertations

The proliferation of smart mobile devices in people’s daily lives is making context-aware computing a reality. A plethora of sensors available in these devices can be utilized to understand users’ context better. Apps can provide more relevant data or services to the user based on improved understanding of user’s context. With the advent of cloud-assisted mobile platforms, apps can also perform collaborative computation over the sensing data collected from a group of users. However, there are still two main issues: (1) A lack of simple and effective personal sensing frameworks: existing frameworks do not provide support for real-time fusing of …

Distributed Knowledge Discovery For Diverse Data, Hossein Hamooni

Computer Science ETDs

In the era of new technologies, computer scientists deal with massive data of size hundreds of terabytes. Smart cities, social networks, health care systems, large sensor networks, etc. are constantly generating new data. It is non-trivial to extract knowledge from big datasets because traditional data mining algorithms run impractically on such big datasets. However, distributed systems have come to aid this problem while introducing new challenges in designing scalable algorithms. The transition from traditional algorithms to the ones that can be run on a distributed platform should be done carefully. Researchers should design the modern distributed algorithms based on the …

Evaluation Of Deep Learning Frameworks Over Different Hpc Architectures, Shayan Shams, Richard Platania, Kisung Lee, Seung Jong Park

Computer Science Faculty Research & Creative Works

Recent advances in deep learning have enabled researchers across many disciplines to uncover new insights about large datasets. Deep neural networks have shown applicability to image, time-series, textual, and other data, all of which are available in a plethora of research fields. However, their computational complexity and large memory overhead requires advanced software and hardware technologies to train neural networks in a reasonable amount of time. To make this possible, there has been an influx in development of deep learning software that aim to leverage advanced hardware resources. In order to better understand the performance implications of deep learning frameworks …

Survey Of Autonomic Computing And Experiments On Jmx-Based Autonomic Features, Adel R. Azzam

University of New Orleans Theses and Dissertations

Autonomic Computing (AC) aims at solving the problem of managing the rapidly-growing complexity of Information Technology systems, by creating self-managing systems. In this thesis, we have surveyed the progress of the AC field, and studied the requirements, models and architectures of AC. The commonly recognized AC requirements are four properties - self-configuring, self-healing, self-optimizing, and self-protecting. The recommended software architecture is the MAPE-K model containing four modules, namely - monitor, analyze, plan and execute, as well as the knowledge repository.

In the modern software marketplace, Java Management Extensions (JMX) has facilitated one function of the AC requirements - monitoring. Using …

On Efficiency Of Distributed Password Recovery, Radek Hranický, Martin Holkovič, Petr Matoušek

Journal of Digital Forensics, Security and Law

One of the major challenges in digital forensics today is data encryption. Due to the leaked information about unlawful sniffing, many users decided to protect their data by encryption. In case of criminal activities, forensic experts are challenged how to decipher suspect's data that are subject to investigation. A common method how to overcome password-based protection is a brute force password recovery using GPU-accelerated hardware. This approach seems to be expensive. This paper presents an alternative approach using task distribution based on BOINC platform. The cost, time and energy efficiency of this approach is discussed and compared to the GPU-based …

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, …

Dynamic Data Management In A Data Grid Environment, Björn Barrefors

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

A data grid is a geographically distributed set of resources providing a facility for computationally intensive analysis of large datasets to a large number of geographically distributed users. In the scientific community, data grids have become increasingly popular as scientific research is driven by large datasets. Until recently, developments in data management for data grids have focused on management of data at lower layers in the data grid architecture. With dataset sizes expected to approach exabyte scale in coming years, data management in data grids are facing a new set of challenges. In particularly, the problem of automatically placing and …

Randomized Algorithms For Approximating A Connected Dominating Set In Wireless Sensor Networks, Akshaye Dhawan, Michelle Tanco, Aaron Yeiser

Mathematics and Computer Science Faculty Publications

A Connected Dominating Set (CDS) of a graph representing a Wireless Sensor Network can be used as a virtual backbone for routing through the network. Since the sensors in the network are constrained by limited battery life, we desire a minimal CDS for the network, a known NP-hard problem. In this paper we present three randomized algorithms for constructing a CDS. We evaluate our algorithms using simulations and compare them to the two-hop K2 algorithm and two other greedy algorithms from the literature. After pruning, the randomized algorithms construct a CDS that are generally equivalent in size to those constructed …

Gpuhelib And Distributedhelib: Distributed Computing Variants Of Helib, A Homomorphic Encryption Library, Ethan Andrew Frame

Master's Theses

Homomorphic Encryption, an encryption scheme only developed in the last five years, allows for arbitrary operations to be performed on encrypted data. Using this scheme, a user can encrypt data, and send it to an online service. The online service can then perform an operation on the data and generate an encrypted result. This encrypted result is then sent back to the user, who decrypts it. This decryption produces the same data as if the operation performed by the online service had been performed on the unencrypted data. This is revolutionary because it allows for users to rely on online …

Itu-Prp: Parallel And Distributed Computing Middleware For Java Developers, Enis Spahi, D. Turgay Altilar

UBT International Conference

ITU-PRP provides a Parallel Programming Framework for Java Developers on which they can adapt their sequential application code to operate on a distributed multi-host parallel environment. Developers would implement parallel models, such as Loop Parallelism, Divide and Conquer, Master-Slave and Fork-Join by the help of an API Library provided under framework. Produced parallel applications would be submitted to a middleware called Parallel Running Platform (PRP), on which parallel resources for parallel processing are being organized and performed. The middleware creates Task Plans (TP) according to application’s parallel model, assigns best available resource Hosts, in order to perform fast parallel processing. …

Dcamp: Distributed Common Api For Measuring Performance, Alexander Paul Sideropoulos

Master's Theses

Although the nearing end of Moore’s Law has been predicted numerous times in the past, it will eventually come to pass. In forethought of this, many modern computing systems have become increasingly complex, distributed, and parallel. As software is developed on and for these complex systems, a common API is necessary for gathering vital performance related metrics while remaining transparent to the user, both in terms of system impact and ease of use.

Several distributed performance monitoring and testing systems have been proposed and implemented by both research and commercial institutions. However, most of these systems do not meet several …

Scaling Mcmc Inference And Belief Propagation To Large, Dense Graphical Models, Sameer Singh

Doctoral Dissertations

With the physical constraints of semiconductor-based electronics becoming increasingly limiting in the past decade, single-core CPUs have given way to multi-core and distributed computing platforms. At the same time, access to large data collections is progressively becoming commonplace due to the lowering cost of storage and bandwidth. Traditional machine learning paradigms that have been designed to operate sequentially on single processor architectures seem destined to become obsolete in this world of multi-core, multi-node systems and massive data sets. Inference for graphical models is one such example for which most existing algorithms are sequential in nature and are difficult to scale …

Reconfigurable Technologies For Next Generation Internet And Cluster Computing, Deepak C. Unnikrishnan

Open Access Dissertations

Modern web applications are marked by distinct networking and computing characteristics. As applications evolve, they continue to operate over a large monolithic framework of networking and computing equipment built from general-purpose microprocessors and Application Specific Integrated Circuits (ASICs) that offers few architectural choices. This dissertation presents techniques to diversify the next-generation Internet infrastructure by integrating Field-programmable Gate Arrays (FPGAs), a class of reconfigurable integrated circuits, with general-purpose microprocessor-based techniques. Specifically, our solutions are demonstrated in the context of two applications - network virtualization and distributed cluster computing.

Network virtualization enables the physical network infrastructure to be shared among several …

Incorporating The Nsf/Tcpp Curriculum Recommendations In A Liberal Arts Setting, Akshaye Dhawan

Mathematics and Computer Science Faculty Publications

This paper examines the integration of the NSF/TCPP Core Curriculum Recommendations in a liberal arts undergraduate setting. We examine how parallel and distributed computing concepts can be incorporated across the breadth of the undergraduate curriculum. As a model of such an integration, changes are proposed to Data Structures and Design and Analysis of Algorithms. These changes were implemented in Design and Analysis of Algorithms and the results were compared to previous iterations of that course taught by the same instructor. The student feedback received shows that the introduction of these topics made the course more engaging and conveyed an adequate …

Pdc Modules For Every Level: A Comprehensive Model For Incorporating Pdc Topics Into The Existing Undergraduate Curriculum, Konstantin Läufer, Chandra N. Sekharan, George K. Thiruvathukal

Konstantin Läufer

We propose to give a half-hour presentation on incorporating PDC topics into our existing undergraduate computer science curriculum. We first describe our experience with single-course and cross-curricular undergraduate PDC education since 1997. We then provide details about our proposed model for incorporating PDC topics into our undergraduate curriculum. To this end, we have distilled a set of consistent, regularly offered and required three-week core and advanced PDC modules from our previously offered PDC content.

Load Sharing Based On Moving Roles In Multiagent Systems, Şebnem Bora, Ali̇ Murat Ti̇ryaki̇, Oğuz Di̇kenelli̇

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we present a load-sharing approach based on the refactoring of agents. According to our approach, the role(s) that makes an agent overloaded is identified and transferred to less loaded agents. The excess workload of this heavily loaded agent is then transferred to the new agent. This approach defines a new agent, called the ``monitor agent,'' which monitors the workload of agents in the organization and decides about the refactoring of the agents. The monitor agent uses the platform ontology, which explicitly describes the components of the agent organization, including agents and their roles, plans, and workloads. This …

Pdc Modules For Every Level: A Comprehensive Model For Incorporating Pdc Topics Into The Existing Undergraduate Curriculum, Konstantin Läufer, Chandra N. Sekharan, George K. Thiruvathukal

George K. Thiruvathukal

We propose to give a half-hour presentation on incorporating PDC topics into our existing undergraduate computer science curriculum. We first describe our experience with single-course and cross-curricular undergraduate PDC education since 1997. We then provide details about our proposed model for incorporating PDC topics into our undergraduate curriculum. To this end, we have distilled a set of consistent, regularly offered and required three-week core and advanced PDC modules from our previously offered PDC content.

Pdc Modules For Every Level: A Comprehensive Model For Incorporating Pdc Topics Into The Existing Undergraduate Curriculum, Konstantin Läufer, Chandra N. Sekharan, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

We propose to give a half-hour presentation on incorporating PDC topics into our existing undergraduate computer science curriculum. We first describe our experience with single-course and cross-curricular undergraduate PDC education since 1997. We then provide details about our proposed model for incorporating PDC topics into our undergraduate curriculum. To this end, we have distilled a set of consistent, regularly offered and required three-week core and advanced PDC modules from our previously offered PDC content.

System Design And Algorithmic Development For Computational Steering In Distributed Environments, Qishi Wu, Michelle Zhu, Yi Gu, Nageswara S.V. Rao

Department of Computer Science Faculty Scholarship and Creative Works

Supporting visualization pipelines over wide-area networks is critical to enabling large-scale scientific applications that require visual feedback to interactively steer online computations. We propose a remote computational steering system that employs analytical models to estimate the cost of computing and communication components and optimizes the overall system performance in distributed environments with heterogeneous resources. We formulate and categorize the visualization pipeline configuration problems for maximum frame rate into three classes according to the constraints on node reuse or resource sharing, namely no, contiguous, and arbitrary reuse. We prove all three problems to be NP-complete and present heuristic approaches based on …