NCAnt: A Network Coding-Based Multipath Data Transmission Scheme for Multi-UAV Formation Flying Networks

Yin, Jun; Lei, Ye; Yang, Yuwang

doi:10.1109/lcomm.2020.3039846

Cited by 20 publications

(8 citation statements)

References 6 publications

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“…Here are some literatures introducing multipath routing in UAV swarms from different perspectives. In [6], a network coding-aware multipath routing protocol was proposed, which was based on the ant colony algorithm and achieved end-to-end reliable transmission by maximizing the coding opportunity. In [7], in order to restore, construct, and select k-disjoint paths, an industry-oriented canonical particle swarm (CPS) optimized data delivery framework was introduced.…”

Section: Related Workmentioning

confidence: 99%

“…Affected by the dynamics and instability of UAVs, single-path routing is easily interrupted when the sensing data is transmitted between UAVs, causing additional latency on retransmissions. To facilitate the distribution of the traffic load and also to avoid the route failure, there is a need to exploit the multipath routing from the perspective of path diversity to improve the multihop transmission efficiency and stability in UAV swarm ad hoc networks [6]. From the appropriate multipath routing perspective, it is expected that the stable multipath routing will increase both the end-to-end throughput and the connection reliability.…”

Section: Introductionmentioning

confidence: 99%

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Multipath Stability Routing in Cognitive UAV Swarm for Emergency Communications: A Hypergraph Matching Approach

Wang

Zhang

2022

Wireless Communications and Mobile Computing

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With the rapid development of unmanned aerial vehicles (UAVs), it has been considered as an effective solution for emergency communications. In order to solve the contradiction between the rapid growth of user equipments and the shortage of spectrum resources as well as the problem that a single UAV cannot meet the multimission requirements, we integrate the cognitive radio spectrum access and UAVs to form a cognitive UAV swarm. Since most of the base stations cannot work properly in disaster scenarios, cognitive UAV swarm transmits the collected information through multihop routing in the form of a decentralized distributed ad hoc network. In order to solve the problems of low robustness of single paths and unstable links, we explore a multipath stability optimization problem and then propose a multipath stable routing algorithm based on the multidimensional hypergraph matching method. The results show that compared with the greedy algorithm, the proposed algorithm can obtain higher path stability while obtaining multiple node disjoint paths. Finally, this paper provides a reference value for establishing multipath routing of UAV ad hoc networks in emergency communication scenarios.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multipath Stability Routing in Cognitive UAV Swarm for Emergency Communications: A Hypergraph Matching Approach

Wang

Zhang

2022

Wireless Communications and Mobile Computing

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“…Due to the devices' mobility in time, collaborative scheduling calls also for an efficient setup of routing protocols (e.g., static, proactive, reactive, hybrid, geographic/position-based or hierarchical routing protocols), as addressed for example in [2], [14]. Similarly, in [27], due to network variations and local topology changes during UAVs' aerial fleet flight, the focus of Han et al is put specifically on solving the problem of multipath routing transmission in terms of multipath establishment and maintenance. Also in [28], Rosati et al deal with the issue of maintaining communication links between the UAVs by also providing a comparison between two different routing algorithms for ad-hoc networks, such as the optimized link-state routing (OLSR) and the predictive OLSR (P-OLSR), which exploit GPS information available at drones.…”

Section: Related Workmentioning

confidence: 99%

Optimizing FANET Lifetime for 5G Softwarized Network Provisioning

Cappello

Colajanni

Daniele

et al. 2022

IEEE Trans. Netw. Serv. Manage.

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Recently, Flying Ad Hoc Networks (FANET) have been proposed to empower 5G networks to support complex missions and provide ubiquitous connectivity to heterogeneous devices. However, it is needed to cope with the limited UAV capabilities (e.g., limited available energy to supply engines and computing elements, limited computing capabilities), as well as with the need to provide network and application services as foreseen in highly dynamic and time varying 5G ecosystems. This paper presents for the first time a comprehensive framework that integrates a FANET with a 5G network, with the aim of providing services that can be even chained with each other. This model is comprehensive in the sense that it takes into account physical constraints of the devices, as well as features and requirements of traffic flows. For this framework, the paper proposes a mathematical optimization model, allowing Virtual Function (VF) placement and chaining, aimed at minimizing energy consumption and service unsatisfaction probabilities of the FANET as a whole without employing heuristics for the solution of the problem. Two placement strategies named MLP and WMP are introduced and compared with the standard placement strategy named NoShP. An extensive numerical analysis shows that MLP and WMP allow us to well catch network dynamics and to reduce the number of virtual functions needed while decreasing the power consumption, so increasing UAV flight time and network lifetime.

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“…The present initial SpaRec study has focused on single-path multi-hop networks. Future research should extend the SpaRec strategies to multi-path multi-hop networks [83]- [85]. Multi-path networks pose several new challenges, such as different delays and erasure probabilities on the different paths that need to be accounted for in the coding of the packet transmissions for the different paths.…”

Section: Summary and Future Workmentioning

confidence: 99%

SpaRec: Sparse Systematic RLNC Recoding in Multi-Hop Networks

et al. 2021

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Sparse Random Linear Network Coding (RLNC) reduces the computational complexity of the RLNC decoding through a low density of the non-zero coding coefficients, which can be achieved through sending uncoded (systematic) packets. However, conventional recoding of sparse RLNC coded packets at an intermediate node in a multi-hop network increases the density of non-zero coding coefficients. We develop and evaluate sparsity-preserving recoding (SpaRec) strategies that preserve the low density of non-zero coding coefficients of sparse RLNC with systematic packets. We develop SpaRec strategies with and without decoding at the intermediate nodes, with and without a specified coding rate, as well as with finite and infinite recoding window lengths. We evaluate the SpaRec strategies in multi-hop networks in terms of packet loss, packet delivery delay, as well as recoding and decoding (computation) throughput. We find that the SpaRec strategies substantially improve the RLNC performance compared to conventional recoding.

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NCAnt: A Network Coding-Based Multipath Data Transmission Scheme for Multi-UAV Formation Flying Networks

Cited by 20 publications

References 6 publications

Multipath Stability Routing in Cognitive UAV Swarm for Emergency Communications: A Hypergraph Matching Approach

Multipath Stability Routing in Cognitive UAV Swarm for Emergency Communications: A Hypergraph Matching Approach

Optimizing FANET Lifetime for 5G Softwarized Network Provisioning

SpaRec: Sparse Systematic RLNC Recoding in Multi-Hop Networks

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