TY - GEN
T1 - Towards Real-Time and Temporal Information Services in Vehicular Networks via Multi-Objective Optimization
AU - Dai, Penglin
AU - Liu, Kai
AU - Feng, Liang
AU - Zhuge, Qingfeng
AU - Lee, Victor Chung Sing
AU - Son, Sang Hyuk
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/12/22
Y1 - 2016/12/22
N2 - Real-time and temporal information services are intrinsic characteristics in vehicular networks, where the timeliness of data dissemination and the maintenance of data quality interplay with each other and influence overall system performance. In this work, we present the system architecture where multiple road side units (RSUs) are cooperated to provide information services, and the vehicles can upload up-to-date information to RSUs via vehicle-to-infrastructure (V2I) communication. On this basis, we formulate the distributed temporal data management (DTDM) problem as a two-objective problem, which aims to enhance overall system performance on both the service quality and the service ratio simultaneously. Further, we propose a multiobjective evolutionary algorithm called MO-DTDM to obtain a set of pareto solutions and analyze how to fulfill given requirements on system performance with obtained pareto solutions. Finally, we build the simulation model and give a comprehensive performance evaluation, which demonstrates the superiority of the proposed optimization method.
AB - Real-time and temporal information services are intrinsic characteristics in vehicular networks, where the timeliness of data dissemination and the maintenance of data quality interplay with each other and influence overall system performance. In this work, we present the system architecture where multiple road side units (RSUs) are cooperated to provide information services, and the vehicles can upload up-to-date information to RSUs via vehicle-to-infrastructure (V2I) communication. On this basis, we formulate the distributed temporal data management (DTDM) problem as a two-objective problem, which aims to enhance overall system performance on both the service quality and the service ratio simultaneously. Further, we propose a multiobjective evolutionary algorithm called MO-DTDM to obtain a set of pareto solutions and analyze how to fulfill given requirements on system performance with obtained pareto solutions. Finally, we build the simulation model and give a comprehensive performance evaluation, which demonstrates the superiority of the proposed optimization method.
KW - multi-objective optimization
KW - real-time data dissemination
KW - temporal information service
KW - vehicular networks
UR - https://www.scopus.com/pages/publications/85010069475
U2 - 10.1109/LCN.2016.117
DO - 10.1109/LCN.2016.117
M3 - 会议稿件
AN - SCOPUS:85010069475
T3 - Proceedings - Conference on Local Computer Networks, LCN
SP - 671
EP - 679
BT - Proceedings - 2016 IEEE 41st Conference on Local Computer Networks, LCN 2016
PB - IEEE Computer Society
T2 - 41st IEEE Conference on Local Computer Networks, LCN 2016
Y2 - 7 November 2016 through 10 November 2016
ER -