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Vasileios Megas

dblp:245/3133 · DBLP profile ↗
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2ranked-venue papers
1as first author
1since 2021 · last 2024
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 2 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Network optimization and economics · 44% Vehicular, aerial and satellite networks · 28% Internet architecture and protocols · 28%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Vehicular, aerial and satellite networks › aerial networks
flying ad-hoc networks
0.812024
A Combined Topology Formation and Rate Allocation Algorithm for Aeronautical Ad Hoc Networks · IEEE Trans. Mob. Comput. 2024
Network optimization and economics › resource allocation
rate allocation
0.812024
A Combined Topology Formation and Rate Allocation Algorithm for Aeronautical Ad Hoc Networks · IEEE Trans. Mob. Comput. 2024
Internet architecture and protocols › network topology
topology generation
0.812024
A Combined Topology Formation and Rate Allocation Algorithm for Aeronautical Ad Hoc Networks · IEEE Trans. Mob. Comput. 2024
Network optimization and economics › network flow
flow assignment
0.212024
A Combined Topology Formation and Rate Allocation Algorithm for Aeronautical Ad Hoc Networks · IEEE Trans. Mob. Comput. 2024
Network optimization and economics › network flow
multicommodity flow
0.212024
A Combined Topology Formation and Rate Allocation Algorithm for Aeronautical Ad Hoc Networks · IEEE Trans. Mob. Comput. 2024

Methods — techniques the papers use, named apart from their topics

mixed integer linear programming · 0.8heuristic algorithm · 0.8
YearPublicationVenuePosition
2024 A Combined Topology Formation and Rate Allocation Algorithm for Aeronautical Ad Hoc Networks
abstract
This paper addresses the problem of providing internet connectivity to aircraft flying above the ocean without using satellite connectivity given the lack of ground network infrastructure in the relevant oceanic areas. Is it possible to guarantee a minimum flow rate to each aircraft flying over an ocean by forming an aeronautical ad hoc network and connecting that network to internet via a set of limited number of ground base stations at the coast as anchor points? We formulated the problem as mixed-integer-linear programming (MILP) to maximize the number of aircraft with flow data rate above a certain threshold. Since this multi-commodity flow problem is at least NP-complete, we propose a two-phase heuristic algorithm to efficiently form topology and assign flows to each aircraft by maximizing the minimum flow. The performance of the heuristic algorithm is evaluated over the North Atlantic Corridor, heuristic performs only 8% less than the optimal result with low densities. In high network densities, the connectivity percentage changes from 70% to 40% under 75 Mbps data rate threshold. Furthermore, the connectivity percentage is investigated for different network parameters such as altitude and compared to upper and lower bounds and a baseline algorithm.
Vasileios Megas, Sandra Hoppe, Mustafa Özger, Dominic A. Schupke, Cicek Cavdar
IEEE Trans. Mob. Comput.1
2019 Combined Optimal Topology Formation and Rate Allocation for Aircraft to Aircraft Communications
abstract
Providing broadband in-flight Internet connectivity to aircraft is challenging. Today's options include satellite communications (SC) and direct air-to-ground communication (DA2GC). To overcome data rate, delay and cost limitations of SC and coverage limitations of DA2GC, one can extend DA2GC with air-to-air communication (A2AC) by enabling multi-hop communication. To investigate the A2AC performance, we construct a mixed integer linear programming (MILP) problem of DA2GC and A2AC, jointly considering interference in topology formation and flow assignment. Our objective is to maximize the number of aircraft that can be connected with a given specific minimum data rate threshold. The evaluation is performed for low aircraft density scenarios over the North Atlantic. We show that in the investigated scenarios, over 90 % of aircraft can have at least 50 Mbps, some being up to 1600 kilometers away from the closest base station (BS). Furthermore, we identify antenna capabilities as an important factor for A2AC performance.
Sandra Hofmann, Vasileios Megas, Mustafa Özger, Dominic A. Schupke, Frank H. P. Fitzek, Cicek Cavdar
ICC2