MAESP: Mobility aware edge service placement in mobile edge networks

被引:15
|
作者
Zhao, Xuhui [1 ,2 ]
Shi, Yan [1 ]
Chen, Shanzhi [3 ]
机构
[1] Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Beijing, Peoples R China
[2] Henan Univ Sci & Technol, Luoyang, Peoples R China
[3] China Acad Telecommun Technol, State Key Lab Wireless Mobile Commun, Beijing, Peoples R China
基金
美国国家科学基金会;
关键词
Mobile edge networks; User mobility; Service placement; Multi-objective context multi-armed bandit; POLICY;
D O I
10.1016/j.comnet.2020.107435
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Mobile edge networks can provide ultra-low latency by deploying services at the edge of networks. However, it is impracticable to place services on all the edge servers due to limited deployment cost requirement. It is desirable to make the optimal edge application placement decisions in a minimum response time and deployment cost, which involve two possibly conflicting objectives. An important issue here is that the number of edge application request from mobile users, which is the key factor determining the realization of two objectives, can vary considerably and the number of edge application request usually unknown before deploying edge application in a particular edge site. It has been found recently that human mobility (location and time features) have a strong influence on what kinds of application that mobile users choose to use. Based on the above observation, we investigate the mobility aware edge service placement problem aiming at optimizing service latency and deployment cost. The problem is formulated as a multi-objective optimization problem and can be solved by multi-objective context multi-armed bandit with a dominant objective. The features of user mobility (time, location) are considered as the context information guiding the edge application placement decisions. We develop mobility-aware edge service placement (MAESP) method and analyse performance measures of MAESP using the 2-dimensional (2D) regret. We show that the 2D regret of MAESP are sublinear in the number of rounds. Based on a real-world dataset, we carry out extensive simulations to evaluate the performance of MAESP. The results show that MAESP outperforms the benchmark algorithms.
引用
收藏
页数:13
相关论文
共 50 条
  • [21] An energy-aware Edge Server Placement Algorithm in Mobile Edge Computing
    Li, Yuanzhe
    Wang, Shangguang
    2018 IEEE INTERNATIONAL CONFERENCE ON EDGE COMPUTING (IEEE EDGE), 2018, : 66 - 73
  • [22] User allocation-aware edge cloud placement in mobile edge computing
    Guo, Yan
    Wang, Shangguang
    Zhou, Ao
    Xu, Jinliang
    Yuan, Jie
    Hsu, Ching-Hsien
    SOFTWARE-PRACTICE & EXPERIENCE, 2020, 50 (05): : 489 - 502
  • [23] Correction to: Mobility-aware computational offloading in mobile edge networks: a survey
    Sardar Khaliq uz Zaman
    Ali Imran Jehangiri
    Tahir Maqsood
    Zulfiqar Ahmad
    Arif Iqbal Umar
    Junaid Shuja
    Eisa Alanazi
    Waleed Alasmary
    Cluster Computing, 2021, 24 : 3851 - 3851
  • [24] Mobility-aware Service Function Chaining in 5G Wireless Networks with Mobile Edge Computing
    Chen, Yan-Ting
    Liao, Wanjiun
    ICC 2019 - 2019 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), 2019,
  • [25] On Cost Aware Cloudlet Placement for Mobile Edge Computing
    Fan, Qiang
    Ansari, Nirwan
    IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2019, 6 (04) : 926 - 937
  • [26] Deep Reinforcement Learning-Based Mobility-Aware UAV Content Caching and Placement in Mobile Edge Networks
    Anokye, Stephen
    Ayepah-Mensah, Daniel
    Seid, Abegaz Mohammed
    Boateng, Gordon Owusu
    Sun, Guolin
    IEEE SYSTEMS JOURNAL, 2022, 16 (01): : 275 - 286
  • [27] On Cost Aware Cloudlet Placement for Mobile Edge Computing
    Qiang Fan
    Nirwan Ansari
    IEEE/CAA Journal of Automatica Sinica, 2019, 6 (04) : 926 - 937
  • [28] Privacy-aware service placement for mobile edge computing via federated learning
    Qian, Yongfeng
    Hub, Long
    Chen, Jing
    Guan, Xin
    Hassan, Mohammad Mehedi
    Alelaiwi, Abdulhameed
    INFORMATION SCIENCES, 2019, 505 : 562 - 570
  • [29] Latency-aware Service Placement for GenAI at the Edge
    Thapa, Bipul B.
    Mashayekhy, Lena
    DISRUPTIVE TECHNOLOGIES IN INFORMATION SCIENCES VIII, 2024, 13058
  • [30] Mobility-Aware Delay-Sensitive Service Provisioning for Mobile Edge Computing
    Ma, Yu
    Liang, Weifa
    Guo, Song
    IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (IEEE INFOCOM 2019 WKSHPS), 2019, : 270 - 276