A survey: energy-efficient sensor and VM selection approaches in green computing for X-IoT applications

被引:14
|
作者
Mekala M.S. [1 ]
Viswanathan P. [2 ]
机构
[1] SCOPE, VIT University, Vellore
[2] SITE, VIT University, Vellore
关键词
agro-industry; Cloud computing; environmental monitoring; internet of things; measurement approaches; sensor selection methods; VM migration;
D O I
10.1080/1206212X.2018.1558511
中图分类号
学科分类号
摘要
Cloud computing (CC) enables enumerable services to manipulate sensor data generated from X-internet of things (IoT) applications. It is accomplished by selecting an accurate decision-making system, sensors, and VMs. This paper reviews energy-efficient sensor, resource-based VM selection approaches for X-IoT applications. It is prompted to distinguish measurement functions, architectures, VM scheduling mechanism challenges. The first field was surveyed to identify the technical measurement variables of agriculture and the second field to distinguish the difficulties of sensor selection, communication impact on the rate of sensor data generation. The last field represents VM consolidation approaches based on a type of task, resource, and energy utilization rate impact on balancing the resources of VMs during sudden changes in the network field. The precise implementation details of selected articles are bounded with sensor energy consumption, edge computing modules, and communication strategies. The outcomes of investigation consolidate a sensor-cloud framework that implies prevailing solution to CC for X-IoT. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.
引用
收藏
页码:290 / 305
页数:15
相关论文
共 50 条
  • [41] Energy-Efficient Task Offloading for Time-Sensitive Applications in Fog Computing
    Jiang, Yu-Lin
    Chen, Ya-Shu
    Yang, Su-Wei
    Wu, Chia-Hsueh
    IEEE SYSTEMS JOURNAL, 2019, 13 (03): : 2930 - 2941
  • [42] EOMR: An Energy-Efficient Optimal Multi-path Routing Protocol to Improve QoS in Wireless Sensor Network for IoT Applications
    Kavita Jaiswal
    Veena Anand
    Wireless Personal Communications, 2020, 111 : 2493 - 2515
  • [43] CPAC: Energy-Efficient Algorithm for IoT Sensor Networks Based on Enhanced Hybrid Intelligent Swarm
    Wang, Qi
    Liu, Wei
    Yu, Hualong
    Zheng, Shang
    Gao, Shang
    Granelli, Fabrizio
    CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES, 2019, 121 (01): : 83 - 103
  • [44] An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics
    Conti, Francesco
    Schilling, Robert
    Schiavone, Pasquale Davide
    Pullini, Antonio
    Rossi, Davide
    Gurkaynak, Frank Kagan
    Muehlberghuber, Michael
    Gautschi, Michael
    Loi, Igor
    Haugou, Germain
    Mangard, Stefan
    Benini, Luca
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2017, 64 (09) : 2481 - 2494
  • [45] EEDTO: An Energy-Efficient Dynamic Task Offloading Algorithm for Blockchain-Enabled IoT-Edge-Cloud Orchestrated Computing
    Wu, Huaming
    Wolter, Katinka
    Jiao, Pengfei
    Deng, Yingjun
    Zhao, Yubin
    Xu, Minxian
    IEEE INTERNET OF THINGS JOURNAL, 2021, 8 (04): : 2163 - 2176
  • [46] Energy-Efficient Collaborative Task Computation Offloading in Cloud-Assisted Edge Computing for IoT Sensors
    Liu, Fagui
    Huang, Zhenxi
    Wang, Liangming
    SENSORS, 2019, 19 (05)
  • [47] Energy-Efficient and Delay-Guaranteed Workload Allocation in IoT-Edge-Cloud Computing Systems
    Guo, Mian
    Li, Lei
    Guan, Quansheng
    IEEE ACCESS, 2019, 7 : 78685 - 78697
  • [48] Green Visual Sensor of Plant: An Energy-Efficient Compressive Video Sensing in the Internet of Things
    Li, Ran
    Yang, Yihao
    Sun, Fengyuan
    FRONTIERS IN PLANT SCIENCE, 2022, 13
  • [49] Efficient Green Solution for a Balanced Energy Consumption and Delay in the IoT-Fog-Cloud Computing
    Mebrek, Adila
    Merghem-Boulahia, Leila
    Esseghir, Moez
    2017 IEEE 16TH INTERNATIONAL SYMPOSIUM ON NETWORK COMPUTING AND APPLICATIONS (NCA), 2017, : 231 - 234
  • [50] Energy-Efficient Resource Allocation Strategy in Massive IoT for Industrial 6G Applications
    Mukherjee, Amrit
    Goswami, Pratik
    Khan, Mohammad Ayoub
    Li Manman
    Yang, Lixia
    Pillai, Prashant
    IEEE INTERNET OF THINGS JOURNAL, 2021, 8 (07) : 5194 - 5201