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Traffic-aware Gateway Placement for High-capacity Flying Networks

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André Coelho, Helder Fontes, Rui Campos, Manuel Ricardo

Networking and Internet Architecture · Submitted 19 Dec 2019

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim The obtained results demonstrate significant gains regarding aggregate throughput and delay.

how it is stated · asserted 1.00 read the record →

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arXiv ID1912.09413 (version 2)
Pith IDIS6LBP4N, Pith's permanent record of this paper and its review
CitationAndr\'e Coelho, Helder Fontes, Manuel Ricardo, Rui Campos. "Traffic-aware Gateway Placement for High-capacity Flying Networks." arXiv:1912.09413 (2019). https://pith.science/paper/IS6LBP4N
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The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 6,149 input tokens.

What the abstract itself states, as probabilities: claims first 0.15 · states limitation 0.18 · human participants 0.02 · controlled comparison 0.14 · randomized assignment 0.01 · states quantitative result 0.06 · compares with prior results 0.28 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v2. Results and the main claim are underlined; .

The ability to operate virtually anywhere and carry payload makes Unmanned Aerial Vehicles (UAVs) perfect platforms to carry communications nodes, including Wi-Fi Access Points (APs) and cellular Base Stations (BSs). This is paving the way to the deployment of flying networks that enable communications to ground users on demand. Still, flying networks impose significant challenges in order to meet the Quality of Experience expectations. State of the art works addressed these challenges, but have been focused on routing and the placement of the UAVs as APs and BSs serving the ground users, overlooking the backhaul network design. The main contribution of this paper is a centralized traffic-aware Gateway UAV Placement (GWP) algorithm for flying networks with controlled topology. GWP takes advantage of the knowledge of the offered traffic and the future topologies of the flying network to enable backhaul communications paths with high enough capacity. The performance achieved using the GWP algorithm is evaluated using ns-3 simulations. The obtained results demonstrate significant gains regarding aggregate throughput and delay.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 The ability to operate virtually anywhere and carry payload makes Unmanned Aerial Vehicles (UAVs) perfect platforms to carry communications nodes, including Wi-Fi Access Points (APs) and cellular Base Stations (BSs). background 1.00 0.05 0.02 asserted 1.00
s1 This is paving the way to the deployment of flying networks that enable communications to ground users on demand. background 1.00 0.05 0.02 asserted 0.84
s2 Still, flying networks impose significant challenges in order to meet the Quality of Experience expectations. background 0.98 0.06 0.02 asserted 1.00
s3 State of the art works addressed these challenges, but have been focused on routing and the placement of the UAVs as APs and BSs serving the ground users, overlooking the backhaul network design. gap 1.00 0.06 0.03 asserted 1.00
s4 The main contribution of this paper is a centralized traffic-aware Gateway UAV Placement (GWP) algorithm for flying networks with controlled topology. contribution 1.00 0.90 0.27 asserted 1.00
s5 GWP takes advantage of the knowledge of the offered traffic and the future topologies of the flying network to enable backhaul communications paths with high enough capacity. method 0.80 0.67 0.17 asserted 0.97
s6 The performance achieved using the GWP algorithm is evaluated using ns-3 simulations. method 1.00 0.94 0.04 asserted 0.96
s7 The obtained results demonstrate significant gains regarding aggregate throughput and delay. result 0.95 0.96 0.70 asserted 1.00

What kind of paper the classifier reports this is: method or tool 1.00 · evidence from simulation or computation 1.00.

What was examined, and what was not

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not examined
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  • P abstract
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  • T body sentences
  • C citations
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Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

The ability to operate virtually anywhere and carry payload makes Unmanned Aerial Vehicles (UAVs) perfect platforms to carry communications nodes, including Wi-Fi Access Points (APs) and cellular Base Stations (BSs). This is paving the way to the deployment of flying networks that enable communications to ground users on demand. Still, flying networks impose significant challenges in order to meet the Quality of Experience expectations. State of the art works addressed these challenges, but have been focused on routing and the placement of the UAVs as APs and BSs serving the ground users, overlooking the backhaul network design. The main contribution of this paper is a centralized traffic-aware Gateway UAV Placement (GWP) algorithm for flying networks with controlled topology. GWP takes advantage of the knowledge of the offered traffic and the future topologies of the flying network to enable backhaul communications paths with high enough capacity. The performance achieved using the GWP algorithm is evaluated using ns-3 simulations. The obtained results demonstrate significant gains regarding aggregate throughput and delay.

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