Fog computing-based beam allocation and co-operative task distribution model for green 5G mobile network

被引:0
|
作者
Deb, Priti [1 ,2 ]
De, Debashis [1 ,3 ]
机构
[1] Maulana Abul Kalam Azad Univ Technol, Ctr Mobile Cloud Comp, Dept Comp Sci & Engn, Nadia 741249, W Bengal, India
[2] Inst Engn & Management, MCA Dept Management House,D-1,Sect 5, Kolkata 700091, W Bengal, India
[3] Univ Western Australia, Dept Phys, 35 Stirling Hwy, Crawley, WA 6009, Australia
关键词
Femtolet; Beamforming; Delay; 5G; Power-efficient; IoT; Fog computing; JOINT OPTIMIZATION; CLOUD; ENERGY; FEMTOLET; SYSTEMS; DELAY;
D O I
10.1007/s11334-022-00487-x
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
The communication and computation world is being gone through a lack of proper power consumption models in multi-tier small cell-based heterogeneous networks. Efficient spectrum utilization with proper task distribution is an emerging criterion for 5G-based wireless communication. Delay incurred by task offloading degrades the quality of services (QoS). To reduce power consumption, delay, and increase spectral efficiency, fog-based power-efficient beam allocation and task distribution model for IoT network are proposed. Femtolet acts as a base station and performs also computational assignments like a cloudlet. Hence, femtolet can act as a fog device. Femtolet allocates beam to each IoT device based on maximum spectral efficiency. Secondly, the task distribution is performed. If the femtolet itself can perform tasks, it processes them and sends back to the IoT device. The global femtolet concept appears when two or more femtolets are needed to perform tasks. The connection between IoT devices (IoTD) and femtolet is done by 5G beamforming. Mixed integer linear programming is formulated. Power consumption, delay, and spectral efficiency are the QoS factors of the IoT network. The simulation result demonstrates that proposed architecture decreases power consumption and delay by 23-47% and 15-25%, respectively, than cloud-sensitive approaches. The proposed approach enhances spectral efficiency and SINR by 12-15% and 15-25%, respectively. The comparative analysis with existing approaches shows that this model is novel, green, and fast.
引用
收藏
页码:869 / 880
页数:12
相关论文
共 50 条
  • [21] Weighted Majority Cooperative Game Based Dynamic Small Cell Clustering and Resource Allocation for 5G Green Mobile Network
    Ghosh, Subha
    De, Debashis
    WIRELESS PERSONAL COMMUNICATIONS, 2020, 111 (03) : 1391 - 1411
  • [22] Weighted Majority Cooperative Game Based Dynamic Small Cell Clustering and Resource Allocation for 5G Green Mobile Network
    Subha Ghosh
    Debashis De
    Wireless Personal Communications, 2020, 111 : 1391 - 1411
  • [23] A Fog Computing Model for VANET to Reduce Latency and Delay Using 5G Network in Smart City Transportation
    Farooqi, Abdul Majid
    Alam, M. Afshar
    Hassan, Syed Imtiyaz
    Idrees, Sheikh Mohammad
    APPLIED SCIENCES-BASEL, 2022, 12 (04):
  • [24] Green resource allocation method for intelligent medical treatment-oriented service in a 5G mobile network
    Wang, Yupeng
    Liu, Tianlong
    Choi, Chang
    Wang, Haoxiang
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2020, 32 (01):
  • [25] Mobile Edge Computing-Based Real-Time English Translation With 5G-Driven Network Support
    Wang, Liguo
    Yang, Haibin
    INTERNATIONAL JOURNAL OF DISTRIBUTED SYSTEMS AND TECHNOLOGIES, 2022, 13 (02)
  • [26] A joint optimization scheme for task offloading and resource allocation based on edge computing in 5G communication networks
    Yang, Shi
    COMPUTER COMMUNICATIONS, 2020, 160 : 759 - 768
  • [27] A SMDP Based Virtual Resource Allocation Model for Multimedia Services in 5G Network
    Liang, Hongbin
    Zheng, Lei
    Li, Wei
    Chen, Qingchun
    2016 IEEE 84TH VEHICULAR TECHNOLOGY CONFERENCE (VTC FALL), 2016,
  • [28] Multiaccess Edge Computing-Based Simulation as a Service for 5G Mobile Applications: A Case Study of Tollgate Selection for Autonomous Vehicles
    Lee, Junhee
    Kang, Sungjoo
    Jeon, Jaeho
    Chun, Ingeol
    WIRELESS COMMUNICATIONS & MOBILE COMPUTING, 2020, 2020
  • [29] 5G communication resource allocation strategy for mobile edge computing based on deep deterministic policy gradient
    He, Jun
    JOURNAL OF ENGINEERING-JOE, 2023, 2023 (03):
  • [30] Cost-Effective User Allocation in 5G NOMA-Based Mobile Edge Computing Systems
    Lai, Phu
    He, Qiang
    Cui, Guangming
    Chen, Feifei
    Grundy, John
    Abdelrazek, Mohamed
    Hosking, John
    Yang, Yun
    IEEE TRANSACTIONS ON MOBILE COMPUTING, 2022, 21 (12) : 4263 - 4278