Energy Saving Technology of 5G Base Station Based on Internet of Things Collaborative Control

Chang, Kuo-Song; Chu, Kai-Chun; Wang, Hsiao-Chuan; Lin, Yuh-Chung; Pan, Jeng‐Shyang

doi:10.1109/access.2020.2973648

Cited by 134 publications

(34 citation statements)

References 24 publications

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“…The architecture of edge computing is the latest enhancement of network processing capabilities, in which computing/storage capabilities are placed near the end user [ 35 ]. Therefore, the cellular network that provides CIoT services and provides the functions of edge computing is very suitable for the widespread applications of IoT in the future.…”

Section: Discussionmentioning

confidence: 99%

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Optimal Consensus with Dual Abnormality Mode of Cellular IoT Based on Edge Computing

Pan

Wang

2021

Sensors

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The continuous development of fifth-generation (5G) networks is the main driving force for the growth of Internet of Things (IoT) applications. It is expected that the 5G network will greatly expand the applications of the IoT, thereby promoting the operation of cellular networks, the security and network challenges of the IoT, and pushing the future of the Internet to the edge. Because the IoT can make anything in anyplace be connected together at any time, it can provide ubiquitous services. With the establishment and use of 5G wireless networks, the cellular IoT (CIoT) will be developed and applied. In order to provide more reliable CIoT applications, a reliable network topology is very important. Reaching a consensus is one of the most important issues in providing a highly reliable CIoT design. Therefore, it is necessary to reach a consensus so that even if some components in the system is abnormal, the application in the system can still execute correctly in CIoT. In this study, a protocol of consensus is discussed in CIoT with dual abnormality mode that combines dormant abnormality and malicious abnormality. The protocol proposed in this research not only allows all normal components in CIoT to reach a consensus with the minimum times of data exchange, but also allows the maximum number of dormant and malicious abnormal components in CIoT. In the meantime, the protocol can make all normal components in CIoT satisfy the constraints of reaching consensus: Termination, Agreement, and Integrity.

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Section: Discussionmentioning

confidence: 99%

“…In the related applications of CIoT, millions of CIoT PEs can be connected to a single base station (BS) for data collection [ 35 ]. In some time-sensitive applications, transmitting the data sensed by CIoT PE directly through the Internet may not meet the time requirement.…”

Section: The Network Structurementioning

confidence: 99%

Optimal Consensus with Dual Abnormality Mode of Cellular IoT Based on Edge Computing

Pan

Wang

2021

Sensors

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“…From miniature sensors in the environment to large data storage physical systems to detect the input process. Through various communication and information technologies, CPS provides users with security application access and support, service and data sharing privileges [8][9][10].…”

Section: Cpss and Iotmentioning

confidence: 99%

Application of Advanced Framework Technology in Smart Cities to Improve Resource Utilization

Chu¹,

Chang²,

Wang³

et al. 2021

Smart Cities - Their Framework and Applications

Self Cite

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Nowadays, the application technology and demand are growth; there have been millions of solutions for user communication in smart cities. However, the quality of the autonomy of handheld devices and the information exchange of applications are functions of requesting services or participating in communications. Therefore, it is very difficult and tedious to implement resource management and control in such an environment. This study here proposes distributed cyber-physical systems (CPS) for agent-based middleware framework (AMF) using to achieve technology, thereby improving the reliability of environmental communication in smart cities. The technical solution has the characteristics of avoiding the problem of data source interruption because of the proxy technology of the linear calculation model. The aforementioned agents are independent and autonomous of each other in terms of providing seamless resource sharing and response scheduling, and have nothing to do with communication time and request queries. In this study, the architecture mainly uses the best linear calculation model to classify overlapping agents, and then allocates non-overlapping resources, and finally analyzes the overall architecture operation performance by responding to processed queries, storage utilization and resource usage, pause time and response.

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“…For a cluster sleeping method, Chang et al [ 11 ] utilized a genetic algorithm to achieve dynamic matching of energy consumption and Li et al [ 12 ] proposed a Gauss–Seidel method to optimize resources in HetNets. In [ 13 ], a low complexity algorithm based on the many-to-many matching game between the virtual SMSs, and the users were proposed to solve the problems of exponential growth of mobile data traffic and energy saving.…”

Section: Related Workmentioning

confidence: 99%

A Turbo Q-Learning (TQL) for Energy Efficiency Optimization in Heterogeneous Networks

Wang

et al. 2020

Entropy

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In order to maximize energy efficiency in heterogeneous networks (HetNets), a turbo Q-Learning (TQL) combined with multistage decision process and tabular Q-Learning is proposed to optimize the resource configuration. For the large dimensions of action space, the problem of energy efficiency optimization is designed as a multistage decision process in this paper, according to the resource allocation of optimization objectives, the initial problem is divided into several subproblems which are solved by tabular Q-Learning, and the traditional exponential increasing size of action space is decomposed into linear increase. By iterating the solutions of subproblems, the initial problem is solved. The simple stability analysis of the algorithm is given in this paper. As to the large dimension of state space, we use a deep neural network (DNN) to classify states where the optimization policy of novel Q-Learning is set to label samples. Thus far, the dimensions of action and state space have been solved. The simulation results show that our approach is convergent, improves the convergence speed by 60% while maintaining almost the same energy efficiency and having the characteristics of system adjustment.

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Energy Saving Technology of 5G Base Station Based on Internet of Things Collaborative Control

Cited by 134 publications

References 24 publications

Optimal Consensus with Dual Abnormality Mode of Cellular IoT Based on Edge Computing

Optimal Consensus with Dual Abnormality Mode of Cellular IoT Based on Edge Computing

Application of Advanced Framework Technology in Smart Cities to Improve Resource Utilization

A Turbo Q-Learning (TQL) for Energy Efficiency Optimization in Heterogeneous Networks

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