Toward IoT fog computing-enabled system energy consumption modeling and optimization by adaptive TCP/IP protocol

被引:3
|
作者
Masri, Aladdin [1 ]
Al-Jabi, Muhannad [1 ]
机构
[1] An Najah Natl Univ, Comp Engn Dept, Nablus, Palestine
关键词
IoT; Wireless networks; TCP; Energy consumption; MTU size; FOG computing; INTERNET; THINGS;
D O I
10.7717/peerj-cs.653
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Nowadays, due to the fast-growing wireless technologies and delay-sensitive applications, Internet of things (IoT) and fog computing will assemble the paradigm Fog of IoT. Since the spread of fog computing, the optimum design of networking and computing resources over the wireless access network would play a vital role in the empower of computing-intensive and delay-sensitive applications under the extent of the energy-limited wireless Fog of IoT. Such applications consume considarable amount of energy when sending and receiving data. Although there many approaches to attain energy efficiency already exist, few of them address the TCP protocol or the MTU size. In this work, we present an effective model to reduce energy consumption. Initially, we measured the consumed energy based on the actual parameters and real traffic for different values of MTU. After that, the work is generalized to estimate the energy consumption for the whole network for different values of its parameters. The experiments were made on different devices and by using different techniques. The results show clearly an inverse proportional relationship between the MTU size and the amount of the consumed energy. The results are promising and can be merged with the existing work to get the optimal solution to reduce the energy consumption in IoT and wireless networks.
引用
收藏
页码:1 / 23
页数:23
相关论文
共 10 条
  • [1] Energy-efficient Fog Computing-enabled Data Transmission Protocol in Tactile Internet-based Applications
    Idrees, Ali Kadhum
    Ali-Yahiya, Tara
    Idrees, Sara Kadhum
    Couturier, Raphael
    37TH ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING, 2022, : 206 - 209
  • [2] Joint Optimization of Energy Consumption and Network Latency in Blockchain-Enabled Fog Computing Networks
    Huang Xiaoge
    Yin Hongbo
    Cao Bin
    Wang Yongsheng
    Chen Qianbin
    Zhang Jie
    China Communications, 2024, 21 (04) : 104 - 119
  • [3] Joint optimization of energy consumption and network latency in blockchain-enabled fog computing networks
    Huang, Xiaoge
    Yin, Hongbo
    Cao, Bin
    Wang, Yongsheng
    Chen, Qianbin
    Zhang, Jie
    CHINA COMMUNICATIONS, 2024, 21 (04) : 104 - 119
  • [4] Energy-Aware Offloading and Power Optimization in Full-Duplex Mobile Edge Computing-Enabled Cellular IoT Networks
    Cheng, Yulun
    Zhao, Haitao
    Xia, Wenchao
    IEEE SENSORS JOURNAL, 2022, 22 (24) : 24607 - 24618
  • [5] Integration of Edge Computing-Enabled IoT Monitoring and Sharded Blockchain in a Renewable Energy-Based Smart Grid System
    Alaguraj, Ramaraj
    Kathirvel, Chinnasamy
    ELECTRIC POWER COMPONENTS AND SYSTEMS, 2023,
  • [6] Joint optimization of energy consumption and time delay in IoT-fog-cloud computing environments using NSGA-II metaheuristic algorithm
    Vahid Jafari
    Mohammad Hossein Rezvani
    Journal of Ambient Intelligence and Humanized Computing, 2023, 14 : 1675 - 1698
  • [7] Joint optimization of energy consumption and time delay in IoT-fog-cloud computing environments using NSGA-II metaheuristic algorithm
    Jafari, Vahid
    Rezvani, Mohammad Hossein
    JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2021, 14 (3) : 1675 - 1698
  • [8] An efficient gray system theory-based routing protocol for energy consumption management in the Internet of Things using fog and cloud computing
    Mohammad Reza Akbari
    Hamid Barati
    Ali Barati
    Computing, 2022, 104 : 1307 - 1335
  • [9] An efficient gray system theory-based routing protocol for energy consumption management in the Internet of Things using fog and cloud computing
    Akbari, Mohammad Reza
    Barati, Hamid
    Barati, Ali
    COMPUTING, 2022, 104 (06) : 1307 - 1335
  • [10] Modeling and Optimization of Fiber Quality and Energy Consumption during Refining Based on Adaptive Neuro-fuzzy Inference System and Subtractive Clustering
    Gao, Yunbo
    Hua, Jun
    Cai, Liping
    Chen, Guangwei
    Jia, Na
    Zhu, Liangkuan
    Wang, Hui
    BIORESOURCES, 2018, 13 (01): : 789 - 803