Attraction-area based geo-clustering for LTE vehicular crowdsensing data offloading

TY - CHAP

T1 - Attraction-area based geo-clustering for LTE vehicular crowdsensing data offloading

AU - Nunes, Douglas F.S.

AU - Moreira, Edson S.

AU - Kimura, Bruno Y.L.

AU - Sastry, Nishanth

AU - Mahmoodi, Toktam

PY - 2017/11/21

Y1 - 2017/11/21

N2 - Vehicular CrowdSensing (VCS) is an emerging solution designed to remotely collect data from smart vehicles. It enables a dynamic and large-scale phenomena monitoring just by exploring the variety of technologies which have been embedded in modern cars. However, VCS applications might generate a huge amount of data traffic between vehicles and the remote monitoring center, which tends to overload the LTE networks. In this paper, we describe and analyze a gEo-clUstering approaCh for Lte vehIcular crowDsEnsing dAta offloadiNg (EUCLIDEAN). It takes advantage of opportunistic vehicle-to-vehicle (V2V) communications to support the VCS data upload process, preserving, as much as possible, the cellular network resources. In general, it is shown from the presented results that our proposal is a feasible and an effective scheme to reduce up to 92.98 % of the global demand for LTE transmissions while performing vehicle-based sensing tasks in urban areas. The most encouraging results were perceived mainly under high-density conditions (i.e., above 125 vehicles/km2), where our solution provides the best benefits in terms of cellular network data offloading.

AB - Vehicular CrowdSensing (VCS) is an emerging solution designed to remotely collect data from smart vehicles. It enables a dynamic and large-scale phenomena monitoring just by exploring the variety of technologies which have been embedded in modern cars. However, VCS applications might generate a huge amount of data traffic between vehicles and the remote monitoring center, which tends to overload the LTE networks. In this paper, we describe and analyze a gEo-clUstering approaCh for Lte vehIcular crowDsEnsing dAta offloadiNg (EUCLIDEAN). It takes advantage of opportunistic vehicle-to-vehicle (V2V) communications to support the VCS data upload process, preserving, as much as possible, the cellular network resources. In general, it is shown from the presented results that our proposal is a feasible and an effective scheme to reduce up to 92.98 % of the global demand for LTE transmissions while performing vehicle-based sensing tasks in urban areas. The most encouraging results were perceived mainly under high-density conditions (i.e., above 125 vehicles/km2), where our solution provides the best benefits in terms of cellular network data offloading.

KW - LTE Data Offloading

KW - VANET

KW - Vehicular CrowdSensing

UR - http://www.scopus.com/inward/record.url?scp=85049916073&partnerID=8YFLogxK

U2 - 10.1145/3127540.3127576

DO - 10.1145/3127540.3127576

M3 - Conference paper

AN - SCOPUS:85049916073

VL - 2017-November

SP - 323

EP - 327

BT - MSWiM 2017 - Proceedings of the 20th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

PB - Association for Computing Machinery, Inc

T2 - 20th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems, MSWiM 2017

Y2 - 21 November 2017 through 25 November 2017

ER -