UAV Ad Hoc Network Routing Algorithms in Space–Air–Ground Integrated Networks: Challenges and Directions

Lu, Yuxi; Zhang, Peiying; Igorevich, Kostromitin Konstantin; Ren, Peng; Zhang, Hongxia; Duan, Youxiang; Zhu, Hailong

doi:10.3390/drones7070448

Cited by 25 publications

(2 citation statements)

References 136 publications

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“…Utilizing big data analysis and AI algorithms, it extracts valuable insights from vast data troves, facilitating intelligent decision-making. Additionally, SAGIN places significant emphasis on security and privacy, employing multi-layered security measures to ensure the safety of data and systems [9].…”

Section: Introductionmentioning

confidence: 99%

Routing Networking Technology Based on Improved Ant Colony Algorithm in Space-Air-Ground Integrated Network

Nie,

Chen,

Wang

et al. 2024

Preprint

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Space-Air-Ground Integrated networks comprise a multi-level heterogeneous integrated network that combines satellite-based, aerial, and terrestrial networks. With the increasing human exploration of space and growing demands for internet applications, Space-Air-Ground Integrated networks have gradually emerged as the direction for communication network development. These networks face various challenges such as extensive coverage, diverse communication node types, low-quality communication links, and simultaneous operation of multiple network protocols. However, the rapid development and widespread application of artificial intelligence and machine learning technologies in recent years have offered new perspectives and solutions for the communication architecture and routing algorithm research within Space-Air-Ground Integrated networks. In these networks, not all nodes can typically communicate directly with satellites; instead, a specific set of specialized communication nodes facilitates data communication between aerial and satellite networks due to their superior communication capabilities. Consequently, in contrast to traditional communication architectures, Space-Air-Ground Integrated networks, particularly in the terrestrial layer, often need to address challenges related to the diversity of communication node types and low-quality communication links. A well-designed routing approach becomes crucial in addressing these issues. Therefore, this paper proposes an AODV routing network protocol based on an Improved Ant Colony Algorithm (AC-AODV), specifically designed for the terrestrial layer within the Space-Air-Ground Integrated networks. By integrating information such as the type, energy, and location of communication nodes, this protocol aims to facilitate network communication. The objective is to guide information flow through nodes that are more suitable for communication, either by relaying communication or by connecting with satellites through specialized nodes. This approach alleviates the burden on ordinary nodes within the terrestrial communication network, thereby enhancing the overall network performance. In this protocol, specialized nodes hold a higher forwarding priority than regular nodes. When a source node needs to transmit data, it enters the route discovery phase, utilizing its own type, location, and energy information as heuristic data to calculate forwarding probabilities. Subsequently, it broadcasts route request (RREQ) messages to find the path. Upon receiving the RREQ message, the destination node sends an RREP message for updating information elements and selects the optimal path based on these information elements. Compared to AODV, AC-AODV shows significant improvements in performance metrics such as transmission latency, throughput, energy conversion rate, and packet loss rate.

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Section: Introductionmentioning

confidence: 99%

Routing Networking Technology Based on Improved Ant Colony Algorithm in Space-Air-Ground Integrated Network

Nie,

Chen,

Wang

et al. 2024

Preprint

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“…UAV adhoc networks are versatile and must be able to quickly respond and adapt themselves to evolving network environments [16,17]. Maintaining a perfect mesh network is impossible in the face of fading wireless channels, interference, dynamic topology changes, and formations [18,19].…”

Section: Introductionmentioning

confidence: 99%

Secure UAV adhoc network with blockchain technology

Alqarni

2024

PLoS ONE

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Recent advances in aerial robotics and wireless transceivers have generated an enormous interest in networks constituted by multiple compact unmanned aerial vehicles (UAVs). UAV adhoc networks, i.e., aerial networks with dynamic topology and no centralized control, are found suitable for a unique set of applications, yet their operation is vulnerable to cyberattacks. In many applications, such as IoT networks or emergency failover networks, UAVs augment and provide support to the sensor nodes or mobile nodes in the ground network in data acquisition and also improve the overall network performance. In this situation, ensuring the security of the adhoc UAV network and the integrity of data is paramount to accomplishing network mission objectives. In this paper, we propose a novel approach to secure UAV adhoc networks, referred to as the blockchain-assisted security framework (BCSF). We demonstrate that the proposed system provides security without sacrificing the performance of the network through blockchain technology adopted to the priority of the message to be communicated over the adhoc UAV network. Theoretical analysis for computing average latency is performed based on queuing theory models followed by an evaluation of the proposed BCSF approach through simulations that establish the superior performance of the proposed methodology in terms of transaction delay, data secrecy, data recovery, and energy efficiency.

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Broad Learning System Routing to Mitigate the Impact of Dynamic Changing Topology for 3D Flying Ad Hoc Networks

Zhang,

Chen,

et al. 2024

Mobile Netw Appl

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UAV Ad Hoc Network Routing Algorithms in Space–Air–Ground Integrated Networks: Challenges and Directions

Cited by 25 publications

References 136 publications

Routing Networking Technology Based on Improved Ant Colony Algorithm in Space-Air-Ground Integrated Network

Routing Networking Technology Based on Improved Ant Colony Algorithm in Space-Air-Ground Integrated Network

Secure UAV adhoc network with blockchain technology

Broad Learning System Routing to Mitigate the Impact of Dynamic Changing Topology for 3D Flying Ad Hoc Networks

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