arXiv subjects

Guanqun Song

Publications and source records attributed to Guanqun Song.

At least 19 recordsLinked to original sources

arXiv2025

Chain Reactions in Space: Analyzing the Impact of Satellite Collisions and Debris Accumulation

The exponential increase in artificial satellites, growing from 852 in 2004 to over 9,000 in 2023, has intensified the risk of the Kessler Syndrome: a cascading chain reaction of orbital collisions. This paper analyzes the dynamics of space debris accumulation to identify the primary orbital features contributing to this systemic risk. We compiled and analyzed Two-Line Element (TLE) datasets from Space-Track.org and historical collision data using a Python-based data mining approach. Specifically, we derived satellite velocities using the Vis-Viva equation and evaluated the correlation of five key features, launch piece count, orbital period, apogee, perigee, and Radar Cross Section (RCS) size, with debris density. Our evaluation reveals that apogee and orbital period exhibit the strongest correlation with the risk of the Kessler Syndrome, indicating that satellites in higher orbits pose a disproportionately greater threat to long-term sustainability due to navigational constraints. Contrary to common assumptions, our data suggests that velocity and object size (RCS) show negligible direct correlation with collision incidence in the current dataset. Based on these findings, we propose mitigation strategies focusing on integrating AI-driven autonomous navigation systems and deploying advanced radiation-resistant shielding materials to enhance the resilience of high-orbit assets.

astro-ph.EP↗

arXiv2025

SLASh: Simulation of LISLs Aboard LEO Satellite Shells

Recent advances in satellite technology have introduced a new frontier of wireless networking by establishing Low Earth Orbit (LEO) Satellite networks that work to connect difficult to reach areas and improve global connectivity. These novel advancements lack robust open-source simulation models that can highlight potential bottlenecks or potential wasted resources, wasting terrestrial users and the companies that provide these networks time and money. To that end, we propose SLASh, a highly-customizable satellite network simulation which allows users to design a simulated network with specific characteristics, and constructs them analog to real-world conditions. Additionally, SLASh can generate abstract telemetry that can be simulated moving throughout the network, allowing users to compare network capabilities across a variety of frameworks.

cs.NI↗

arXiv2025

Satellite Cybersecurity Across Orbital Altitudes: Analyzing Ground-Based Threats to LEO, MEO, and GEO

The rapid proliferation of satellite constellations, particularly in Low Earth Orbit (LEO), has fundamentally altered the global space infrastructure, shifting the risk landscape from purely kinetic collisions to complex cyber-physical threats. While traditional safety frameworks focus on debris mitigation, ground-based adversaries increasingly exploit radio-frequency links, supply chain vulnerabilities, and software update pathways to degrade space assets. This paper presents a comparative analysis of satellite cybersecurity across LEO, Medium Earth Orbit (MEO), and Geostationary Earth Orbit (GEO) regimes. By synthesizing data from 60 publicly documented security incidents with key vulnerability proxies--including Telemetry, Tracking, and Command (TT&C) anomalies, encryption weaknesses, and environmental stressors--we characterize how orbital altitude dictates attack feasibility and impact. Our evaluation reveals distinct threat profiles: GEO systems are predominantly targeted via high-frequency uplink exposure, whereas LEO constellations face unique risks stemming from limited power budgets, hardware constraints, and susceptibility to thermal and radiation-induced faults. We further bridge the gap between security and sustainability, arguing that unmitigated cyber vulnerabilities accelerate hardware obsolescence and debris accumulation, undermining efforts toward carbon-neutral space operations. The results demonstrate that weak encryption and command path irregularities are the most consistent predictors of adversarial success across all orbits.

cs.CR↗

arXiv2025

Investigating How MacBook Accessories Evolve across Generations, and Their Potential Environmental, Economical Impacts

The technological transition of MacBook charging solutions from MagSafe to USB-C, followed by a return to MagSafe 3, encapsulates the dynamic interplay between technological advancement, environmental considerations, and economic factors. This study delves into the broad implications of these charging technology shifts, particularly focusing on the environmental repercussions associated with electronic waste and the economic impacts felt by both manufacturers and consumers. By investigating the lifecycle of these technologies - from development and market introduction through to their eventual obsolescence - this paper underscores the importance of devising strategies that not only foster technological innovation but also prioritize environmental sustainability and economic feasibility. This comprehensive analysis illuminates the crucial factors influencing the evolution of charging technologies and their wider societal and environmental implications, advocating for a balanced approach that ensures technological progress does not compromise ecological health or economic stability.

cs.CY↗

arXiv2025

EdgeFlex-Transformer: Transformer Inference for Edge Devices

Deploying large-scale transformer models on edge devices presents significant challenges due to strict constraints on memory, compute, and latency. In this work, we propose a lightweight yet effective multi-stage optimization pipeline designed to compress and accelerate Vision Transformers (ViTs) for deployment in resource-constrained environments. Our methodology combines activation profiling, memory-aware pruning, selective mixed-precision execution, and activation-aware quantization (AWQ) to reduce the model's memory footprint without requiring costly retraining or task-specific fine-tuning. Starting from a ViT-Huge backbone with 632 million parameters, we first identify low-importance channels using activation statistics collected via forward hooks, followed by structured pruning to shrink the MLP layers under a target memory budget. We further apply FP16 conversion to selected components and leverage AWQ to quantize the remaining model weights and activations to INT8 with minimal accuracy degradation. Our experiments on CIFAR-10 demonstrate that the fully optimized model achieves a 76% reduction in peak memory usage and over 6x lower latency, while retaining or even improving accuracy compared to the original FP32 baseline. This framework offers a practical path toward efficient transformer inference on edge platforms, and opens future avenues for integrating dynamic sparsity and Mixture-of-Experts (MoE) architectures to further scale performance across diverse tasks.

cs.LG↗

arXiv2025

On-device Large Multi-modal Agent for Human Activity Recognition

Human Activity Recognition (HAR) has been an active area of research, with applications ranging from healthcare to smart environments. The recent advancements in Large Language Models (LLMs) have opened new possibilities to leverage their capabilities in HAR, enabling not just activity classification but also interpretability and human-like interaction. In this paper, we present a Large Multi-Modal Agent designed for HAR, which integrates the power of LLMs to enhance both performance and user engagement. The proposed framework not only delivers activity classification but also bridges the gap between technical outputs and user-friendly insights through its reasoning and question-answering capabilities. We conduct extensive evaluations using widely adopted HAR datasets, including HHAR, Shoaib, Motionsense to assess the performance of our framework. The results demonstrate that our model achieves high classification accuracy comparable to state-of-the-art methods while significantly improving interpretability through its reasoning and Q&A capabilities.

cs.LG↗

arXiv2025

Analysis of Security in OS-Level Virtualization

Virtualization is a technique that allows multiple instances typically running different guest operating systems on top of single physical hardware. A hypervisor, a layer of software running on top of the host operating system, typically runs and manages these different guest operating systems. Rather than to run different services on different servers for reliability and security reasons, companies started to employ virtualization over their servers to run these services within a single server. This approach proves beneficial to the companies as it provides much better reliability, stronger isolation, improved security and resource utilization compared to running services on multiple servers. Although hypervisor based virtualization offers better resource utilization and stronger isolation, it also suffers from high overhead as the host operating system has to maintain different guest operating systems. To tackle this issue, another form of virtualization known as Operating System-level virtualization has emerged. This virtualization provides light-weight, minimal and efficient virtualization, as the different instances are run on top of the same host operating system, sharing the resources of the host operating system. But due to instances sharing the same host operating system affects the isolation of the instances. In this paper, we will first establish the basic concepts of virtualization and point out the differences between the hyper-visor based virtualization and operating system-level virtualization. Next, we will discuss the container creation life-cycle which helps in forming a container threat model for the container systems, which allows to map different potential attack vectors within these systems. Finally, we will discuss a case study, which further looks at isolation provided by the containers.

cs.CR↗

arXiv2024

Optimizing Global Quantum Communication via Satellite Constellations

In this paper, we investigate the optimization of global quantum communication through satellite constellations. We address the challenge of quantum key distribution (QKD) across vast distances and the limitations posed by terrestrial fiber-optic networks. Our research focuses on the configuration of satellite constellations to improve QKD between ground stations and the application of innovative orbital mechanics to reduce latency in quantum information transfer. We introduce a novel approach using quantum relay satellites in Molniya orbits, enhancing communication efficiency and coverage. The use of these high eccentricity orbits allows us to extend the operational presence of satellites over targeted hemispheres, thus maximizing the quantum network's reach. Our findings provide a strategic framework for deploying quantum satellites and relay systems to achieve a robust and efficient global quantum communication network.

quant-ph↗

arXiv2024

Achieving Carbon Neutrality for I/O Devices

Achieving carbon neutrality has become a critical goal in mitigating the environmental impacts of human activities, particularly in the face of global climate challenges. Input/Output (I/O) devices, such as keyboards, mice, displays, and printers, contribute significantly to greenhouse gas emissions through their manufacturing, operation, and disposal processes. In this paper, we explores sustainable strategies for achieving carbon neutrality in I/O devices, emphasizing the importance of environmentally conscious design and development. Through a comprehensive review of existing literature and best approaches, we introduces a framework to outline approaches for reducing the carbon footprint of I/O devices. The result underscore the necessity of integrating sustainability into the lifecycle of I/O devices to support global carbon neutrality goals and promote long-term environmental sustainability.

cs.CY↗

arXiv2024

Environmental and Economic Impact of I/O Device Obsolescence

This paper analyzes the proportion of Input/output devices made obsolete by changes in technology generations. This obsolescence may be by new software/hardware generations rendering otherwise functional devices unusable. Concluding with brief analysis on the economic and environmental impacts of the e-waste produced.

cs.CY↗

arXiv2024

Energy Efficient LoRaWAN in LEO Satellites

LPWAN service's inexpensive cost and long range capabilities make it a promising addition and countless satellite companies have started taking advantage of this technology to connect IoT users across the globe. However, LEO satellites have the unique challenge of using rechargeable batteries and green solar energy to power their components. LPWAN technology is not optimized to maximize battery lifespan of network nodes. By incorporating a MAC protocol that maximizes node the battery lifespan across the network, we can reduce battery waste and usage of scarce Earth resources to develop satellite batteries.

cs.ET↗

arXiv2024

Heat: Satellite's meat is GPU's poison

In satellite applications, managing thermal conditions is a significant challenge due to the extreme fluctuations in temperature during orbital cycles. One of the solutions is to heat the satellite when it is not exposed to sunlight, which could protect the satellites from extremely low temperatures. However, heat dissipation is necessary for Graphics Processing Units (GPUs) to operate properly and efficiently. In this way, this paper investigates the use of GPU as a means of passive heating in low-earth orbit (LEO) satellites. Our approach uses GPUs to generate heat during the eclipse phase of satellite orbits, substituting traditional heating systems, while the GPUs are also cooled down during this process. The results highlight the potential advantages and limitations of this method, including the cost implications, operational restrictions, and the technical complexity involved. Also, this paper explores the thermal behavior of GPUs under different computational loads, specifically focusing on execution-dominated and FLOP-dominated workloads. Moreover, this paper discusses future directions for improving GPU-based heating solutions, including further cost analysis, system optimization, and practical testing in real satellite missions.

cs.DC↗

arXiv2024

Technological Progress and Obsolescence: Analyzing the Environmental Economic Impacts of MacBook Pro I/O Devices

This study investigates how the new release of MacBook Pro I/O devices affects the obsolescence of related accessories. We also explore how these accessories will impact the environment and the economic consequences. As technology progresses, each new MacBook Pro releases outdated prior accessories, making more electronic waste. This phenomenon makes modern people need to change their traditional consumption patterns. We analyze changes in I/O ports and compatibility between MacBook Pro versions to determine which accessories are obsolete and estimate their environmental impact. Our research focuses on the sustainability of current accessories. We explore alternate methods of reusing, recycling, and disposing of these accessories in order to reduce waste and environmental impact. In addition, we will explore the economic consequences of rapid technological advances that make accessories obsolete too quickly. Thereby assessing the impact of such changes on consumers, manufacturers, and the technology industry. This study aims to respond to the rapid advancement of technology while promoting more sustainable approaches to waste management and product design. As the MacBook Pro I/O unit evolves, certain accessories become obsolete with each subsequent version. The purpose of this study is to identify and quantify the environmental and economic impacts of parts end-of-life. We can detect which accessories have become obsolete and assess the environmental impact by comparing I/O port changes and compatibility across MacBook Pro generations. In response to these environmental images, methods are developed to reuse, recycle, and dispose of obsolete accessories to reduce waste and promote sustainable development. Additionally, we evaluate the economic impact of obsolete equipment on consumers and producers.

cs.CY↗

arXiv2023

The Inner Workings of Windows Security

The year 2022 saw a significant increase in Microsoft vulnerabilities, reaching an all-time high in the past decade. With new vulnerabilities constantly emerging, there is an urgent need for proactive approaches to harden systems and protect them from potential cyber threats. This project aims to investigate the vulnerabilities of the Windows Operating System and explore the effectiveness of key security features such as BitLocker, Microsoft Defender, and Windows Firewall in addressing these threats. To achieve this, various security threats are simulated in controlled environments using coded examples, allowing for a thorough evaluation of the security solutions' effectiveness. Based on the results, this study will provide recommendations for mitigation strategies to enhance system security and strengthen the protection provided by Windows security features. By identifying potential weaknesses and areas of improvement in the Windows security infrastructure, this project will contribute to the development of more robust and resilient security solutions that can better safeguard systems against emerging cyber threats.

cs.CR↗

arXiv2023

Data Classification With Multiprocessing

Classification is one of the most important tasks in Machine Learning (ML) and with recent advancements in artificial intelligence (AI) it is important to find efficient ways to implement it. Generally, the choice of classification algorithm depends on the data it is dealing with, and accuracy of the algorithm depends on the hyperparameters it is tuned with. One way is to check the accuracy of the algorithms by executing it with different hyperparameters serially and then selecting the parameters that give the highest accuracy to predict the final output. This paper proposes another way where the algorithm is parallelly trained with different hyperparameters to reduce the execution time. In the end, results from all the trained variations of the algorithms are ensembled to exploit the parallelism and improve the accuracy of prediction. Python multiprocessing is used to test this hypothesis with different classification algorithms such as K-Nearest Neighbors (KNN), Support Vector Machines (SVM), random forest and decision tree and reviews factors affecting parallelism. Ensembled output considers the predictions from all processes and final class is the one predicted by maximum number of processes. Doing this increases the reliability of predictions. We conclude that ensembling improves accuracy and multiprocessing reduces execution time for selected algorithms.

cs.LG↗

arXiv2023

Design and Implementation Considerations for a Virtual File System Using an Inode Data Structure

Virtual file systems are a tool to centralize and mobilize a file system that could otherwise be complex and consist of multiple hierarchies, hard disks, and more. In this paper, we discuss the design of Unix-based file systems and how this type of file system layout using inode data structures and a disk emulator can be implemented as a single-file virtual file system in Linux. We explore the ways that virtual file systems are vulnerable to security attacks and introduce straightforward solutions that can be implemented to help prevent or mitigate the consequences of such attacks.

cs.OS↗

arXiv2023

Map-Reduce for Multiprocessing Large Data and Multi-threading for Data Scraping

This document is the final project report for our advanced operating system class. During this project, we mainly focused on applying multiprocessing and multi-threading technology to our whole project and utilized the map-reduce algorithm in our data cleaning and data analysis process. In general, our project can be divided into two components: data scraping and data processing, where the previous part was almost web wrangling with employing potential multiprocessing or multi-threading technology to speed up the whole process. And after we collect and scrape a large amount value of data as mentioned above, we can use them as input to implement data cleaning and data analysis, during this period, we take advantage of the map-reduce algorithm to increase efficiency.

math.NA↗

arXiv2023

Security in 5G Networks -- How 5G networks help Mitigate Location Tracking Vulnerability

As 5G networks become more mainstream, privacy has come to the forefront of end users. More scrutiny has been shown to previous generation cellular technologies such as 3G and 4G on how they handle sensitive metadata transmitted from an end user mobile device to base stations during registration with a cellular network. These generation cellular networks do not enforce any encryption on this information transmitted during this process, giving malicious actors an easy way to intercept the information. Such an interception can allow an adversary to locate end users with shocking accuracy. This paper investigates this problem in great detail and discusses how a newly introduced approach in 5G networks is helping combat this problem. The paper discusses the implications of this vulnerability and the technical details of the new approach, including the encryption schemes used to secure this sensitive information. Finally, the paper will discuss any limitations to this new approach.

cs.CR↗