Offloading Data through Unmanned Aerial Vehicles: A Dependability Evaluation

Brito, Carlos; Silva, Leonardo; Callou, Gustavo; Nguyen, Tuan Anh; Dai, Min; Lee, Jae-Woo; Silva, Francisco Airton

doi:10.3390/electronics10161916

Cited by 6 publications

(6 citation statements)

References 46 publications

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“…Inhibitor arcs either block or permit tokens to move between places. Additionally, each token is associated with a specific place [27].…”

Section: Modelmentioning

confidence: 99%

Event-Based Moving Target Defense in Cloud Computing with VM Migration: A Performance Modeling Approach

Santos,

Brito,

Fé

et al. 2024

IEEE Access

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The domain of information security is undergoing significant evolution to address the increasingly complex challenges aimed at bolstering system resilience against attacks. The Moving Target Defense (MTD) methodology, which entails altering the system's configuration-for instance, by relocating virtual machines (VM) or modifying IP addresses-serves to dynamically modify vulnerable components of a system. This strategy effectively disorients potential attackers, complicating their efforts to comprehend or anticipate the system's configuration. Moreover, MTD can be proactively utilized by, for example, relocating VMs from a network segment that has been compromised. Consequently, MTD emerges as a viable approach for mitigating security concerns, particularly within cloud computing frameworks. A critical facet of MTD involves the system migration across different hardware, presenting logistical and strategic challenges that necessitate a thorough evaluation of factors such as operational downtime and the impact on system performance. Analytical models, particularly those based on stochastic Petri nets (SPN), offer a methodological advantage in strategizing MTD implementations by facilitating the assessment of potential outcomes in a non-live environment. This paper proposes an advanced model that extends prior research through the integration of an event-based MTD mechanism, which encompasses both the probability of intrusion detection and the ability to discern potential threats. Through the application of diverse migration initiation policies, this study aims to identify more efficacious strategies under specific conditions. The findings indicate that reliance on event-detection policies is advantageous when the system possesses a detection accuracy exceeding 50%, underscoring the critical role of precise intrusion detection in the efficacy of MTD strategies.

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“…Inhibitor arcs either block or permit tokens to move between places. Additionally, each token is associated with a specific place [27].…”

Section: Modelmentioning

confidence: 99%

Event-Based Moving Target Defense in Cloud Computing with VM Migration: A Performance Modeling Approach

Santos,

Brito,

Fé

et al. 2024

IEEE Access

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“…In their model data is transferred through the Base stations and processed in the cloud. Then, responses are returned to the IoT devices ( Brito et al 2021). Alhelaly et al developed an allocation and computation offloading model with multi-user and multi UAV.…”

Section: Cloud Computing Optimizationmentioning

confidence: 99%

Integrating unmanned and manned UAVs data network based on combined Bayesian belief network and multi-objective reinforcement learning algorithm

et al. 2023

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This paper presents and assesses the feasibility and potential of a novel concept: the operation of multiple unmanned vehicles (UAV) commanded and supported by a manned “Tender” air vehicle carrying a pilot and flight manager(s). The "Tender" is equipped to flexibly and economically monitor and manage multiple diverse UAVs over otherwise inaccessible terrain through wireless communication. Further, this paper seeks to find the optimal trajectories for UAVs to collect data from sensors in a predefined continuous space. We formulate the path-planning problem for a cooperative, and a diverse swarm of UAVs tasked with optimizing multiple objectives simultaneously with the goal of maximizing accumulated data within a given flight time within cloud data processing constraints as well as minimizing the probable imposed risk during UAVs mission. To this end, as the problem is formulated as a convex optimization model, and we propose a low complexity Multi-Objective Reinforcement Learning (MORL) algorithm with a provable performance guarantee to solve the problem efficiently. We show that the MORL architecture can be successfully trained and allows each UAV to map each observation of the network state to an action to make optimal movement decisions.

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“…Inhibitor arcs block or allow tokens to pass from one place to another. Additionally, a token is assigned to a specific place [16]. Figure 1 illustrates the components of an SPN model.…”

Section: Stochastic Petri Netsmentioning

confidence: 99%

Smart Poultry Supported by Edge-Fog-Cloud Continuum: A Performance Evaluation Using Petri Nets

Barbosa,

Sabino,

Lima

et al. 2023

Preprint

Self Cite

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The Internet of Things (IoT) application in agriculture provides rural poultry farmers with automated tools and decision support systems to increase productivity and profit. The integration of Edge, Fog, and Cloud Computing technologies in this scenario enables real-time data collection, processing, and analysis. This, in turn, empowers poultry farmers to make informed decisions, enhancing production efficiency and ensuring poultry quality. However, when implementing IoT devices, the challenge arises in dealing with a large volume of generated data. Delays in data transfer between the Edge, Fog, and Cloud layers can impact the system's real-time responsiveness. Slowness in the system's responsiveness can compromise performance, especially in poultry monitoring systems, which are time-sensitive, and an error could result in losses. This work proposes a Stochastic Petri Net (SPN) model to analyze the performance of an integrated smart poultry house with Edge, Fog, and Cloud Computing. The proposed model covers the analysis of metrics such as average response time, resource utilization, discard probability, and system throughput. Furthermore, the highly flexible model allows developers and system administrators to calibrate various parameters.

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Offloading Data through Unmanned Aerial Vehicles: A Dependability Evaluation

Cited by 6 publications

References 46 publications

Event-Based Moving Target Defense in Cloud Computing with VM Migration: A Performance Modeling Approach

Event-Based Moving Target Defense in Cloud Computing with VM Migration: A Performance Modeling Approach

Integrating unmanned and manned UAVs data network based on combined Bayesian belief network and multi-objective reinforcement learning algorithm

Smart Poultry Supported by Edge-Fog-Cloud Continuum: A Performance Evaluation Using Petri Nets

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