A User-Centric QoS-Aware Multi-Path Service Provisioning in Mobile Edge Computing

被引:3
|
作者
Malik, Saif U. R. [1 ]
Kanwal, Tehsin [2 ]
Khan, Samee U. [3 ]
Malik, Hassan [4 ]
Pervaiz, Haris [5 ]
机构
[1] Cybernetica AS, EE-12618 Tallinn, Estonia
[2] COMSATS Univ Islamabad, Dept Comp Sci, Islamabad 45550, Pakistan
[3] Mississippi State Univ, Dept Elect & Comp Engn, Starkville, MS 39762 USA
[4] Edge Hill Univ, Dept Comp Sci, Ormskirk L39 4QP, England
[5] Univ Lancaster, Sch Comp & Commun SCC, Lancaster LA1 4YW, England
来源
IEEE ACCESS | 2021年 / 9卷
关键词
Task analysis; Quality of service; Resource management; Optimization; Base stations; Servers; Energy consumption; Mobile edge computing; Internet of Things (IoT); quality of service (QoS); service provisioning; multi-path routing; high level petri nets; RESOURCE-ALLOCATION; JOINT OPTIMIZATION; COMPUTATION; SECURITY; FOG; 5G;
D O I
10.1109/ACCESS.2021.3070104
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Recent development in modern wireless applications and services, such as augmented reality, image processing, and network gaming requires persistent computing on average commercial wireless devices to perform complex tasks with low latency. The traditional cloud systems are unable to meet those requirements solely. In the said perspective, Mobile Edge Computing (MEC) serves as a proxy between the things (devices) and the cloud, pushing the computations at the edge of the network. The MEC provides an effective solution to fulfill the demands of low-latency applications and services by executing most of the tasks within the proximity of users. The main challenge, however, is that too many simultaneous service requests created by wireless access produce severe interference, resulting in a decreased rate of data transmission. In this paper, we made an attempt to overcome the aforesaid limitation by proposing a user-centric QoS-aware multi-path service provisioning approach. A densely deployed base station MEC environment has overlapping coverage regions. We exploit such regions to distribute the service requests in a way that avoid hotspots and bottlenecks. Our approach is adaptive and can tune to different parameters based on service requirements. We performed several experiments to evaluate the effectiveness of our approach and compared it with the traditional Greedy approach. The results revealed that our approach improves the network state by 26.95% and average waiting time by 35.56% as compared to the Greedy approach. In addition, the QoS violations were also reduced by the fraction of 16.
引用
收藏
页码:56020 / 56030
页数:11
相关论文
共 50 条
  • [41] A balancing scheme for QoS-aware service provisioning in OPS networks
    Bian, Weiwei
    Wang, Hongxiang
    Ji, Yuefeng
    PHOTONIC NETWORK COMMUNICATIONS, 2012, 23 (02) : 198 - 203
  • [42] Automated Query Relaxation Mechanism for QoS-Aware Service Provisioning
    Bhattacharya, Adrija
    Choudhury, Sankhayan
    ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2022, 47 (02) : 1717 - 1732
  • [43] Mobile Transparent Computing: A Novel User-Centric Approach to Unify Device, Edge, and Cloud
    Zhou, Yuezhi
    Yang, Bowen
    Wu, Chao
    Ren, Ju
    Zhang, Yaoxue
    IEEE NETWORK, 2019, 33 (02): : 132 - 137
  • [44] Energy-Efficient Blockchain-Enabled User-Centric Mobile Edge Computing
    Qin, Langtian
    Lu, Hancheng
    Chen, Yuang
    Gu, Zhuojia
    Zhao, Dan
    Wu, Feng
    IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING, 2024, 10 (04) : 1452 - 1466
  • [45] QoS-aware Energy Saving Scheme and Traffic Management in Mobile Edge Computing Networks
    Alnoman, Ali
    Anpalagan, Alagan
    IWCMC 2021: 2021 17TH INTERNATIONAL WIRELESS COMMUNICATIONS & MOBILE COMPUTING CONFERENCE (IWCMC), 2021, : 1925 - 1930
  • [46] Utility-Centric Service Provisioning in Multi-Access Edge Computing
    Xuan-Qui Pham
    Tien-Dung Nguyen
    VanDung Nguyen
    Eui-Nam Huh
    APPLIED SCIENCES-BASEL, 2019, 9 (18):
  • [47] Cooperation Resource Efficient User-Centric Clustering for QoS Provisioning in Uplink CoMP
    Zhang, Zhe
    Wang, Ning
    Zhang, Jiankang
    Mu, Xiaomin
    Wong, Kon Max
    2017 IEEE 18TH INTERNATIONAL WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS (SPAWC), 2017,
  • [48] QoS-Aware Service Composition for Converged Network-Cloud Service Provisioning
    Huang, Jun
    Liu, Guoquan
    Duan, Qiang
    Yan, Yuhong
    2014 IEEE INTERNATIONAL CONFERENCE ON SERVICES COMPUTING (SCC 2014), 2014, : 67 - 74
  • [49] QoS-Aware VNF Placement and Service Chaining for IoT Applications in Multi-Tier Mobile Edge Networks
    Xu, Zichuan
    Zhang, Zhiheng
    Liang, Weifa
    Xia, Qiufen
    Rana, Omer
    Wu, Guowei
    ACM TRANSACTIONS ON SENSOR NETWORKS, 2020, 16 (03)
  • [50] QoSRHMM: A QoS-Aware ring-based hierarchical multi-path multicast routing protocol
    Wang, GJ
    Luo, J
    Cao, JN
    Chan, KCC
    PARALLEL AND DISTRIBUTED PROCESSING AND APPLICATIONS, PROCEEDINGS, 2004, 3358 : 568 - 577