A Survey on UAV Computing Platforms: A Hardware Reliability Perspective

Ahmed, Faiz; Jenihhin, Maksim

doi:10.3390/s22166286

Cited by 35 publications

(14 citation statements)

References 108 publications

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“…The complexity of unmanned aerial vehicles necessitates a high level of software and hardware integration to enable their autonomous operation, flight dynamics, payload integration, real-time communication, and navigation. The dynamic contexts in which these systems operate can also contribute to their complexity [4]. In order to ensure the security, dependability, and efficacy of UAVs for their intended usage in cloud settings, it is essential to build and deploy a solid security strategy [5].…”

Section: Introductionmentioning

confidence: 99%

“…The Payload class's toString method can be used to convert the payload into a string for further analysis. 4.…”

mentioning

confidence: 99%

“…If a potential collision is identified, the system may trigger additional events or raise alerts to notify administrators and initiate mitigation procedures. 4.…”

mentioning

confidence: 99%

“…This class coordinates the overall defense mechanism and communicates with other system components, such as intrusion detection systems, firewalls, or network administrators, as needed. 4.…”

mentioning

confidence: 99%

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A Study of the Data Security Attack and Defense Pattern in a Centralized UAV–Cloud Architecture

Airlangga

Liu

2023

Drones

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An unmanned aerial vehicle (UAV) is an autonomous flying robot that has attracted the interest of several communities because of its capacity to increase the safety and productivity of labor. In terms of software engineering, UAV system development is extremely difficult because the focus is not only on functional requirement fulfillment, but also on nonfunctional requirements such as security and safety, which play a crucial role in mission success. Consequently, architecture robustness is very important, and one of the most common architectures developed is based on a centralized pattern in which all UAVs are controlled from a central location. Even though this is a very important problem, many developers must expend a great deal of effort to adapt and improve security. This is because there are few practical perspectives of security development in the context of UAV system development; therefore, the study of attack and defense patterns in centralized architecture is required to fill this knowledge gap. This paper concentrates on enhancing the security aspect of UAV system development by examining attack and defense patterns in centralized architectures. We contribute to the field by identifying 26 attack variations, presenting corresponding countermeasures from a software analyst’s standpoint, and supplying a node.js code template for developers to strengthen their systems’ security. Our comprehensive analysis evaluates the proposed defense strategies in terms of time and space complexity, ensuring their effectiveness. By providing a focused and in-depth perspective on security patterns, our research offers crucial guidance for communities and developers working on UAV-based systems, facilitating the development of more secure and robust solutions.

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Section: Introductionmentioning

confidence: 99%

“…The Payload class's toString method can be used to convert the payload into a string for further analysis. 4.…”

mentioning

confidence: 99%

“…If a potential collision is identified, the system may trigger additional events or raise alerts to notify administrators and initiate mitigation procedures. 4.…”

mentioning

confidence: 99%

mentioning

confidence: 99%

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A Study of the Data Security Attack and Defense Pattern in a Centralized UAV–Cloud Architecture

Airlangga

Liu

2023

Drones

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“…They also enumerate specific applications in which UAVs make a contribution: search and rescue [6][7][8][9], remote sensing [10][11][12], construction and infrastructure inspections [13][14][15], and precision agriculture [16][17][18]. There is a growing level of technological advancement in the areas of sensors [19][20][21], generated computing power [22], materials, as well as in the area of aggregation and data processing during the flight [23]. Reliability and a high level of safety are required for autonomously controlled flying robots-especially in transport and entertainment applications.…”

Section: Introductionmentioning

confidence: 99%

UAV Fault Detection Methods, State-of-the-Art

Puchalski

Giernacki

2022

Drones

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The continual expansion of the range of applications for unmanned aerial vehicles (UAVs) is resulting in the development of more and more sophisticated systems. The greater the complexity of the UAV, the greater the likelihood that a component will fail. Due to the fact that drones often operate in close proximity to humans, the reliability of flying robots, which directly affects the level of safety, is becoming more important. This review article presents recent research works on fault detection on unmanned flying systems. They include papers published between January 2016 and August 2022. Web of Science and Google Scholar databases were used to search for articles. Terminology related to fault detection of unmanned aerial vehicles was used as keywords. The articles were analyzed, each paper was briefly summarized and the most important details concerning each of the described articles were summarized in the table.

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DRL‐Based Computation‐Efficient Offloading and Power Control for UAV‐Assisted MEC Networks

Priya,

Nandhini,

Uma

et al. 2024

Trans Emerging Tel Tech

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Mobile edge computing (MEC) has achieved significant attention due to the availability of computational tasks in specific scenarios such as emergency applications like forest fire and earthquake remedies. The computationally demanding policy and user offloading policy are challenging problems to address in the energy constrained unmanned aerial vehicle (UAV) network. In this work, the computational task offloading, and power management is solved by using the multi‐agent deterministic power management algorithm (MADPM) based on deep reinforcement learning. Every UAV works together as a team to understand the actor critic environment and to make decisions that will help achieve the goals. This involves transferring computational tasks from UAVs to more powerful ground stations or other UAVs to save energy and enhance performance. It requires intelligent decision‐making to determine which tasks to offload and when. The joint optimization problem is verified with the simulation results and the proposed work is enabled with MEC in achieving the emergence of UAV related applications. Our simulations show that the MADPM algorithm, as suggested, enhances task offloading efficiency by 35% and reduces power consumption by 25% when compared with current methods. These findings underscore the ability of our method to greatly improve the UAV operational capacities.

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A Survey on UAV Computing Platforms: A Hardware Reliability Perspective

Cited by 35 publications

References 108 publications

A Study of the Data Security Attack and Defense Pattern in a Centralized UAV–Cloud Architecture

A Study of the Data Security Attack and Defense Pattern in a Centralized UAV–Cloud Architecture

UAV Fault Detection Methods, State-of-the-Art

DRL‐Based Computation‐Efficient Offloading and Power Control for UAV‐Assisted MEC Networks

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