Real-Time Cache-Aided Route Planning Based on Mobile Edge Computing

被引:13
|
作者
Yao, Yuan [1 ]
Xiao, Bin [2 ]
Wang, Wen [3 ]
Yang, Gang [1 ]
Zhou, Xingshe [1 ]
Peng, Zhe [4 ]
机构
[1] Northwestern Polytech Univ, Sch Comp Sci, Xian, Peoples R China
[2] Hong Kong Polytech Univ, Dept Comp, Hong Kong, Peoples R China
[3] China Aeronaut Comp Tech Res Inst, Xian, Peoples R China
[4] Hong Kong Baptist Univ, Dept Comp Sci, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
Planning; Servers; Edge computing; Roads; Navigation; Delays; Cloud computing;
D O I
10.1109/MWC.001.1900559
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Route planning is considered as one of the fundamental technologies in the navigation system, which finds an optimal route between a pair of source and target locations. Navigation services are required to provide real-time responses to route planning queries to promote user experiences on the road under different situations, such as sudden detour, unpredictable traffic congestion and loss of GPS signals. However, most commercial navigation products search the optimal path at the remote central server which suffer from several inherent limitations. First, the communication between the access network and the remote central server has a large uncertain Internet-induced time delay. Second, the computational cost of retrieving an optimal path is increasing exponentially with the distance from the source location to the destination in a large-scale road network. To address the above issues, we propose a real-time Cache-Aided Route Planning System based on Mobile Edge Computing (CARPS-MEC), aiming to greatly shorten the communication and computation time of route planning queries by caching those frequently requested paths. Different from traditional cache based route planning algorithms which require an exact path matching from point to point, CARPSMEC makes a rough path matching from region to region. Thus, it only needs to process unmatched road segments on a MEC server which is closer to the end users. This will significantly reduce the transmission latency due to the uncertainty of the Internet. Experiment results demonstrate that CARPS-MEC can increase the cache hit ratio and reduce the response time greatly.
引用
收藏
页码:155 / 161
页数:7
相关论文
共 50 条
  • [21] The analysis of intelligent real-time image recognition technology based on mobile edge computing and deep learning
    Shen, Tao
    Gao, Chan
    Xu, Dawei
    JOURNAL OF REAL-TIME IMAGE PROCESSING, 2021, 18 (04) : 1157 - 1166
  • [22] REAL-TIME ROUTE PLANNING IN ROAD NETWORKS
    GUZOLEK, J
    KOCH, E
    CONFERENCE RECORD OF PAPERS PRESENTED AT THE FIRST VEHICLE NAVIGATION AND INFORMATION SYSTEMS CONFERENCE ( VNIS 89 ), 1989, : 165 - 169
  • [23] Robust algorithm for real-time route planning
    Szczerba, RJ
    Galkowski, P
    Glickstein, IS
    Ternullo, N
    IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2000, 36 (03) : 869 - 878
  • [24] A study on real-time image processing applications with edge computing support for mobile devices
    Mattia, Gabriele Proietti
    Beraldi, Roberto
    PROCEEDINGS OF THE 2021 IEEE/ACM 25TH INTERNATIONAL SYMPOSIUM ON DISTRIBUTED SIMULATION AND REAL TIME APPLICATIONS (DS-RT 2021), 2021,
  • [25] Cache-aided full-duplex: delivery time analysis and optimization
    Vu, Thang X.
    Trinh, Anh Vu
    Chatzinotas, Symeon
    Tran, Xuan Nam
    WIRELESS NETWORKS, 2020, 26 (06) : 4403 - 4410
  • [26] A Learning Algorithm for Real-time Service In Vehicular Networks with Mobile-Edge Computing
    Dai, Penglin
    Liu, Kai
    Wu, Xiao
    Xing, Huanlai
    Yu, Zhaofei
    Lee, Victor C. S.
    ICC 2019 - 2019 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), 2019,
  • [27] Cache-aided full-duplex: delivery time analysis and optimization
    Thang X. Vu
    Anh Vu Trinh
    Symeon Chatzinotas
    Xuan Nam Tran
    Wireless Networks, 2020, 26 : 4403 - 4410
  • [28] Real-time Route Planning using Mobile Air Pollution Detectors and Citizen Scientists
    Sinnott, Richard O.
    Wang, Yuan
    Wang, Yiqun
    2021 17TH INTERNATIONAL CONFERENCE ON WIRELESS AND MOBILE COMPUTING, NETWORKING AND COMMUNICATIONS (WIMOB 2021), 2021, : 139 - 144
  • [29] Real-Time Data Prefetching in Mobile Computing
    Issam, Khalloufi
    Omar, El Beqqali
    2015 IEEE/ACS 12TH INTERNATIONAL CONFERENCE OF COMPUTER SYSTEMS AND APPLICATIONS (AICCSA), 2015,
  • [30] Real-time broadcast algorithm for mobile computing
    Lim, SH
    Kim, JH
    JOURNAL OF SYSTEMS AND SOFTWARE, 2004, 69 (1-2) : 173 - 181