Abstract
Objective: Green computing meets the needs of a low-carbon society and it is an important aspect of promoting social sustainable development and technological progress. In the investigation, green computing for resource management and allocation issues is only discussed. Therefore, in the context of the 5G communication network, the investigation of the data classification and resource optimization of the Internet of Things are conducted. Method: The virtualization architecture of the heterogeneous wireless network resource based on 5G technology is designed. The related investigation is conducted based on 5G network and Internet of Things technology. Under the traditional method, the transfer learning is introduced to improve the AdaBoost (Adaptive Boosting) algorithm to classify the data. The investigated complete resource reuse method is used to optimize resources. A method that a sub-channel can be reused by a cellular link and any number of D2D links at the same time is proposed to conduct resource optimization investigation. Results: The investigation indicates that the classification accuracy of the algorithm is excellent for the data classification of the Internet of Things and has different advantages in various aspects compared with other algorithms. The designed algorithm can find a larger set of resource reuse and have a significant increase in spectrum utilization efficiency. Conclusion: The investigation can contribute to the boom in the Internet of Things in terms of data classification and resource optimization based on 5G.
- [1] . 2019. Stochastic performance analysis of network function virtualization in future Internet. IEEE Journal on Selected Areas in Communications 37, 3 (2019), 613–626.Google Scholar
Cross Ref
- [2] . 2016. Internet of Things and big data analytics for smart and connected communities. IEEE Access 4 (2016), 766--773.Google Scholar
Cross Ref
- [3] . 2017. A survey on Internet of Things: Architecture, enabling technologies, security and privacy, and applications. IEEE Internet of Things Journal 4, 5 (2017), 1125–1142.Google Scholar
Cross Ref
- [4] . 2016. An efficient tree-based self-organizing protocol for Internet of Things. IEEE Access 4 (2016), 3535–3546.Google Scholar
Cross Ref
- [5] . 2017. Big health application system based on health Internet of Things and big data. IEEE Access 5 (2016), 7885–7897.Google Scholar
Cross Ref
- [6] . 2017. Software engineering for the Internet of Things. IEEE Software 34, 1 (2017), 24–28.Google Scholar
Cross Ref
- [7] . 2020. A novel approach for big data classification and transportation in rail networks. IEEE Transactions on Intelligent Transportation Systems 21, 3 (2020), 1239–1249.Google Scholar
Cross Ref
- [8] . 2017. Mobile unmanned aerial vehicles (UAVs) for energy-efficient Internet of Things communications. IEEE Transactions on Wireless Communications 16, 11 (2017), 7574–7589.Google Scholar
Cross Ref
- [9] . 2019. Network architectures for demanding 5G performance requirements: Tailored toward specific needs of efficiency and flexibility. IEEE Vehicular Technology Magazine 14, 2 (2019), 33–43.Google Scholar
Cross Ref
- [10] . 2017. A survey on 5G networks for the Internet of Things: Communication technologies and challenges. IEEE Access 6 (2017), 3619--3647.Google Scholar
- [11] . 2017. Internet of Things architecture: Recent advances, taxonomy, requirements, and open challenges. IEEE Wireless Communications 24, 3 (2017), 10–16.Google Scholar
Digital Library
- [12] . 2017. A survey on the edge computing for the Internet of Things. IEEE Access 6 (2017), 6900–6919.Google Scholar
- [13] . 2019. Random forest for big data classification in the Internet of Things using optimal features. International Journal of Machine Learning and Cybernetics 10, 10 (2019), 2609–2618.Google Scholar
Cross Ref
- [14] . 2018. Incremental-precision based feature computation and multi-level classification for low-energy Internet-of-Things. IEEE Journal on Emerging and Selected Topics in Circuits and Systems 8, 4 (2018), 822–835.Google Scholar
Cross Ref
- [15] . 2019. Optimal cloud resource allocation with cost performance tradeoff based on Internet of Things. IEEE Internet of Things Journal 6, 4 (2019), 6876–6886.Google Scholar
Cross Ref
- [16] . 2018. A novel multichannel Internet of Things based on dynamic spectrum sharing in 5G communication. IEEE Internet of Things Journal 6, 4 (2018), 5962–5970.Google Scholar
Cross Ref
- [17] . 2018. Integration of LoRaWAN and 4G/5G for the Industrial Internet of Things. IEEE Communications Magazine 56, 2 (2018), 60–67. Google Scholar
Digital Library
- [18] . 2018. Biologically inspired resource allocation for network slices in 5G-enabled Internet of Things. IEEE Internet of Things Journal 6, 6 (2018), 9266–9279.Google Scholar
Cross Ref
- [19] . 2018. Effective features to classify big data using social Internet of Things. IEEE Access 6 (2018), 24196–24204.Google Scholar
Cross Ref
- [20] . 2017. Securing Internet of Things with software defined networking. IEEE Communications Magazine 56, 9 (2017), 186–192.Google Scholar
Cross Ref
- [21] . 2018. A feature-based learning system for Internet of Things applications. IEEE Internet of Things Journal 6, 2 (2018), 1928–1937.Google Scholar
Cross Ref
- [22] . 2017. Federated Internet of Things and cloud computing pervasive patient health monitoring system. IEEE Communications Magazine 55, 1 (2017), 48–53. Google Scholar
Digital Library
- [23] . 2017. A collaborative Internet of Things architecture for smart cities and environmental monitoring. IEEE Internet of Things Journal 5, 2 (2017), 592–605.Google Scholar
Cross Ref
- [24] . 2017. Context-aware computing, learning, and big data in Internet of Things: A survey. IEEE Internet of Things Journal 5, 1 (2017), 1–27.Google Scholar
Cross Ref
- [25] . 2017. Deep convolutional computation model for feature learning on big data in Internet of Things. IEEE Transactions on Industrial Informatics 14, 2 (2017), 790–798.Google Scholar
Cross Ref
- [26] . 2018. UAV-aided MIMO communications for 5G Internet of Things. IEEE Internet of Things Journal 6, 2 (2018), 1731–1740.Google Scholar
Cross Ref
- [27] . 2019. Fog computing for 5G tactile industrial Internet of Things: QoE-aware resource allocation model. IEEE Transactions on Industrial Informatics 15, 5 (2019), 3085–3092.Google Scholar
Cross Ref
- [28] . 2018. Nonorthogonal interleave-grid multiple access scheme for industrial Internet of Things in 5G network. IEEE Transactions on Industrial Informatics 14, 12 (2018), 5436–5446.Google Scholar
Cross Ref
- [29] . 2017. Action recognition using 3D histograms of texture and a multi-class boosting classifier. IEEE Transactions on Image Processing 26, 10 (2017), 4648–4660.Google Scholar
Digital Library
- [30] . 2017. Step-up DC–DC converters: A comprehensive review of voltage-boosting techniques, topologies, and applications. IEEE Transactions on Power Electronics 32, 12 (2017), 9143–9178.Google Scholar
Cross Ref
- [31] . 2019. Feature learning viewpoint of AdaBoost and a new algorithm. IEEE Access 7 (2019), 149890–149899.Google Scholar
Cross Ref
- [32] . 2018. Credit card fraud detection using AdaBoost and majority voting. IEEE Access 6 (2018), 14277–14284.Google Scholar
Cross Ref
- [33] . 2019. Mobile Internet of Things under data physical fusion technology. IEEE Internet of Things Journal 7, 5 (2019), 4616--4624.Google Scholar
Cross Ref
- [34] . 2019. Exploring unsupervised learning techniques for the Internet of Things. IEEE Transactions on Industrial Informatics 16, 4 (2019), 2621--2628.Google Scholar
- [35] . 2019. Interaction of edge-cloud computing based on SDN and NFV for next generation IoT. IEEE Internet of Things Journal 7, 7 (2019), 5706--5712.Google Scholar
Cross Ref
- [36] . 2019. A machine learning approach for IoT cultural data. Journal of Ambient Intelligence and Humanized Computing (2019), 1–12.Google Scholar
- [37] . 2019. BIM big data storage in WebVRGIS. IEEE Transactions on Industrial Informatics 16, 4 (2019), 2566--2573.Google Scholar
- [38] . 2020. What should 6G be? Nature Electronics 3, 1 (2020), 20–29.Google Scholar
Cross Ref
- [39] . 2019. Decision making in IoT environment through unsupervised learning. IEEE Intelligent Systems 35, 1 (2019), 27--35.Google Scholar
- [40] . 2019. Intelligent security planning for regional distributed energy internet. IEEE Transactions on Industrial Informatics 16, 5 (2019), 3540--3547.Google Scholar
- [41] . 2020. LMM: Latency-aware micro-service mashup in mobile edge computing environment. Neural Computing and Applications 32, 19 (2020), 15411--15425.Google Scholar
- [42] . 2020. Cognitive computing and wireless communications on the edge for healthcare service robots. Computer Communications 149 (2020), 99--106.Google Scholar
Digital Library
- [43] . 2019. Infrastructure monitoring and operation for smart cities based on IoT system. IEEE Transactions on Industrial Informatics 16, 3 (2019), 1957--1962.Google Scholar
- [44] . 2020. Automated colorization of a grayscale image with seed points propagation. IEEE Transactions on Multimedia 22, 7 (2020), 1756--1768.Google Scholar
Cross Ref
- [45] . 2019. Scalable digital neuromorphic architecture for large-scale biophysically meaningful neural network with multi-compartment neurons. IEEE Transactions on Neural Networks and Learning Systems 31, 1 (2019), 148–162.Google Scholar
Cross Ref
Index Terms
Transfer Learning-powered Resource Optimization for Green Computing in 5G-Aided Industrial Internet of Things
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