research-article

LAMA: Location-Assisted Medium Access for Position-Beaconing Applications

Authors:

Holger Döbler,

Björn ScheuermannAuthors Info & Claims

MSWIM '19: Proceedings of the 22nd International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

Pages 253 - 260

https://doi.org/10.1145/3345768.3355925

Published: 25 November 2019 Publication History

Abstract

It is nowadays common in all kinds of traffic-maritime, air, road-that vehicles use beaconing systems to broadcast their position and other navigational data to nearby vehicles to improve situational awareness. MAC protocols for the beaconing use case face special challenges: protocol overhead has a significant performance impact due to small packet size, fair and frequent access to the channel is required, and the broadcast nature limits the applicability of hand shakes. We propose LAMA, a MAC protocol for position awareness beaconing that is based on the locally shared position information. Our contention-free approach uses neither handshakes nor forwarding of state, thereby requiring only small constant protocol overhead per beacon and scaling well with large neighbor counts. Yet, it successfully suppresses interference, including hidden-terminal-type, while maximizing channel utilization through coordinated spatial reuse. In a quantitative evaluation using the ns-3 discrete event simulator we compare LAMA against SO-TDMA, the MAC protocol used in the maritime automatic identification system. We find that LAMA outperforms SO-TDMA with respect to several metrics in synthetic random topologies as well as in scenarios based on real vessel traffic traces.

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Cited By

Kaur JBhatti STan KPopoola OImran MGhannam RAbbasi QAbbas H(2024)Contextual beamforming: Exploiting location and AI for enhanced wireless telecommunication performanceAPL Machine Learning10.1063/5.01764222:1Online publication date: 26-Feb-2024
https://doi.org/10.1063/5.0176422
Döbler HScheuermann B(2023)CAMELAMA: Cooperative awareness and spaceborne monitoring enabled by location-assisted medium accessComputer Communications10.1016/j.comcom.2023.07.015210(205-216)Online publication date: Oct-2023
https://doi.org/10.1016/j.comcom.2023.07.015
Dobler HScheuermann B(2022)CAMELAMA: Cooperative Awareness and spaceborne Monitoring Enabled by Location-Assisted Medium Access2022 17th Wireless On-Demand Network Systems and Services Conference (WONS)10.23919/WONS54113.2022.9764567(1-8)Online publication date: 30-Mar-2022
https://doi.org/10.23919/WONS54113.2022.9764567

Index Terms

LAMA: Location-Assisted Medium Access for Position-Beaconing Applications
1. Networks

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Published In

cover image ACM Conferences

MSWIM '19: Proceedings of the 22nd International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

November 2019

340 pages

ISBN:9781450369046

DOI:10.1145/3345768

General Chair:
Antonio A. F. Loureiro
Federal University of Minas Gerais, Brazil
,
Program Chairs:
Salil Kanhere
University of New South Wales, Australia
,
Paolo Bellavista
University of Bologna, Italy

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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SIGSIM: ACM Special Interest Group on Simulation and Modeling

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Association for Computing Machinery

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Publication History

Published: 25 November 2019

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Deutsche Forschungsgemeinschaft

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MSWiM '19

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SIGSIM

MSWiM '19: 22nd Int'l ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

November 25 - 29, 2019

FL, Miami Beach, USA

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Overall Acceptance Rate 398 of 1,577 submissions, 25%

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Cited By

Kaur JBhatti STan KPopoola OImran MGhannam RAbbasi QAbbas H(2024)Contextual beamforming: Exploiting location and AI for enhanced wireless telecommunication performanceAPL Machine Learning10.1063/5.01764222:1Online publication date: 26-Feb-2024
https://doi.org/10.1063/5.0176422
Döbler HScheuermann B(2023)CAMELAMA: Cooperative awareness and spaceborne monitoring enabled by location-assisted medium accessComputer Communications10.1016/j.comcom.2023.07.015210(205-216)Online publication date: Oct-2023
https://doi.org/10.1016/j.comcom.2023.07.015
Dobler HScheuermann B(2022)CAMELAMA: Cooperative Awareness and spaceborne Monitoring Enabled by Location-Assisted Medium Access2022 17th Wireless On-Demand Network Systems and Services Conference (WONS)10.23919/WONS54113.2022.9764567(1-8)Online publication date: 30-Mar-2022
https://doi.org/10.23919/WONS54113.2022.9764567

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