TY - GEN
T1 - Roadside Unit Allocation for Fog-based Information Sharing in Vehicular Networks
AU - Magsino, Elmer R.
AU - Ho, Ivan Wang Hei
PY - 2018/11/4
Y1 - 2018/11/4
N2 - As more intelligent vehicles will ply the roads in the near future, a rapid increase of sensed environment data is anticipated. Information based on these acquired data needs to be extracted and shared in the most efficient way. To realize this, roadside units (RSUs) acting as hotspots and fog computing nodes should work together with vehicles in vehicular networks and intelligent transportation systems. In this paper, we consider a set of intersections in the city of Beijing as potential locations for strategically allocating fog computing hotspots to maximize the information shared among vehicles and fog nodes. Using empirical findings from mobility traces such as vehicular density, total daily number of transmissions, transmitted data size, and space mean speed, we propose the Information Sharing via Roadside unit Allocation (ISRA) strategy to determine the optimal locations for these fog computing hotspots. Simulation results show that for a given deployment limit, ISRA, when compared to three other conventional deployment schemes, is able to share on average 6%, 10% and 47% more road information with fewer packet transmissions (energy efficiency of 83%) in the vehicular network. In addition, ISRA is able to balance the information load among adjacent RSU fog nodes for better resource management.
AB - As more intelligent vehicles will ply the roads in the near future, a rapid increase of sensed environment data is anticipated. Information based on these acquired data needs to be extracted and shared in the most efficient way. To realize this, roadside units (RSUs) acting as hotspots and fog computing nodes should work together with vehicles in vehicular networks and intelligent transportation systems. In this paper, we consider a set of intersections in the city of Beijing as potential locations for strategically allocating fog computing hotspots to maximize the information shared among vehicles and fog nodes. Using empirical findings from mobility traces such as vehicular density, total daily number of transmissions, transmitted data size, and space mean speed, we propose the Information Sharing via Roadside unit Allocation (ISRA) strategy to determine the optimal locations for these fog computing hotspots. Simulation results show that for a given deployment limit, ISRA, when compared to three other conventional deployment schemes, is able to share on average 6%, 10% and 47% more road information with fewer packet transmissions (energy efficiency of 83%) in the vehicular network. In addition, ISRA is able to balance the information load among adjacent RSU fog nodes for better resource management.
KW - Empirical GPS Traces
KW - Fog Computing Applications
KW - Roadside Unit
KW - Vehicular Networks
UR - http://www.scopus.com/inward/record.url?scp=85058211029&partnerID=8YFLogxK
U2 - 10.1145/3277893.3277897
DO - 10.1145/3277893.3277897
M3 - Conference article published in proceeding or book
AN - SCOPUS:85058211029
T3 - CitiFog 2018 - Proceedings of the 1st Workshop on Smart Cities and Fog Computing, Part of SenSys 2018
SP - 7
EP - 12
BT - CitiFog 2018 - Proceedings of the 1st Workshop on Smart Cities and Fog Computing, Part of SenSys 2018
A2 - Krishnamachari, Bhaskar
A2 - Ramachandran, Gowri Sankar
PB - Association for Computing Machinery, Inc
T2 - 1st ACM International Workshop on Smart Cities and Fog Computing, CitiFog 2018, co-located with ACM SenSys 2018 and BuildSys 2018
Y2 - 4 November 2018
ER -
