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Research Anthology on Developing and Optimizing 5G Networks and the Impact on Society最新文献

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Dynamic Cache Management of Cloud RAN and Multi-Access Edge Computing for 5G Networks 5G网络云RAN和多接入边缘计算的动态缓存管理
Pub Date : 1900-01-01 DOI: 10.4018/978-1-7998-1152-7.ch006
Deepika Pathinga Rajendiran, Yihang Tang, M. Moh
Using a cache to improve efficiency and to save on the cost of a computer system has been a field that attracts many researchers, including those in the area of cellular network systems. The first part of this chapter focuses on adaptive cache management schemes for cloud radio access networks (CRAN) and multi-access edge computing (MEC) of 5G mobile technologies. Experimental results run through CloudSim show that the proposed adaptive algorithms are effective in increasing cache hit rate, guaranteeing QoS, and in reducing algorithm execution time. In second part of this chapter, a new cache management algorithm using Zipf distribution to address dynamic input is proposed for CRAN and MEC models. A performance test is also run using iFogSim to show the improvement made by the proposed algorithm over the original versions. This work contributes in the support of 5G for IoT by enhancing CRAN and MEC performance; it also contributes to how novel caching algorithms can resolve the unbalanced input load caused by changing distributions of the input traffic.
使用高速缓存来提高计算机系统的效率和节省成本一直是一个吸引许多研究人员的领域,包括蜂窝网络系统领域的研究人员。本章的第一部分重点介绍了5G移动技术的云无线接入网(CRAN)和多接入边缘计算(MEC)的自适应缓存管理方案。通过CloudSim运行的实验结果表明,所提出的自适应算法在提高缓存命中率、保证QoS和减少算法执行时间方面是有效的。在本章的第二部分,提出了一种新的缓存管理算法,该算法使用Zipf分布来处理CRAN和MEC模型的动态输入。还使用iFogSim运行了一个性能测试,以显示所提出的算法相对于原始版本所做的改进。这项工作通过提高CRAN和MEC性能,为支持5G物联网做出了贡献;它还有助于新的缓存算法如何解决由输入流量分布变化引起的不平衡输入负载。
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引用次数: 0
Connecting One Belt One Road Countries via Wireless Sensor Network 通过无线传感器网络连接bb100个国家
Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-8980-8.CH009
Kwok Tai Chui, W. Alhalabi, R. Liu, P. O. Pablos
The economy of China grows rapidly due to the advent of wireless networks. The networks provide connection between nodes (sensors, gateways, systems, people, etc.) for data transmission and communication seamlessly. This is a crucial element to achieve sustainable economics. It is worth mentioning that wireless communication is the optimal solution compared with wired communication given the fact that China has a huge land area and the largest population in the world. Traditional wireless technologies like 4G, Bluetooth, ZigBee, ISA 100.11a, and WirelessHART have been well addressed in literature. In this chapter, the focus is moved to 5G, LoRa, IEEE 802.11 af, ah, ax, and ay. Selected applications health monitoring, toxic gas monitoring, connected target coverage problem, and mobile crowd sensing are discussed in detail. Geographic routing, wireless charging, and wireless coexistence are challenging issues that need to be addressed in the near future.
由于无线网络的出现,中国的经济迅速增长。网络提供节点(传感器、网关、系统、人员等)之间的连接,实现数据的无缝传输和通信。这是实现可持续经济的关键因素。值得一提的是,与有线通信相比,无线通信是最优的解决方案,因为中国拥有巨大的土地面积和世界上最多的人口。传统的无线技术,如4G、蓝牙、ZigBee、ISA 100.11a和WirelessHART已经在文献中得到了很好的解决。本章将重点介绍5G、LoRa、IEEE 802.11 af、ah、ax和ay。详细讨论了选定的应用健康监测、有毒气体监测、连接目标覆盖问题和移动人群传感。地理路由、无线充电和无线共存是在不久的将来需要解决的具有挑战性的问题。
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引用次数: 0
Machine Learning in 5G Multimedia Communications 5G多媒体通信中的机器学习
Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-9643-1.ch017
D. Milovanovic, Z. Bojkovic, D. Kukolj
Machine learning (ML) has evolved to the point that this technique enhances communications and enables fifth-generation (5G) wireless networks. ML is great to get insights about complex networks that use large amounts of data, and for predictive and proactive adaptation to dynamic wireless environments. ML has become a crucial technology for mobile broadband communication. Special case goes to deep learning (DL) in immersive media. Through this chapter, the goal is to present open research challenges and applications of ML. An exploration of the potential of ML-based solution approaches in the context of 5G primary eMBB, mMTC, and uHSLLC services is presented, evaluating at the same time open issues for future research, including standardization activities of algorithms and data formats.
机器学习(ML)已经发展到这种技术可以增强通信并实现第五代(5G)无线网络的程度。ML非常适合深入了解使用大量数据的复杂网络,以及预测和主动适应动态无线环境。机器学习已经成为移动宽带通信的一项关键技术。沉浸式媒体中的深度学习(DL)是一个特例。通过本章,我们的目标是展示机器学习的开放式研究挑战和应用。在5G主要eMBB、mMTC和uHSLLC服务的背景下,探索基于机器学习的解决方案方法的潜力,同时评估未来研究的开放式问题,包括算法和数据格式的标准化活动。
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引用次数: 0
Future Networks 未来的网络
Pub Date : 1900-01-01 DOI: 10.4018/978-1-7998-7708-0.ch028
N. Perrot, Amal Benhamiche, Y. Carlinet, É. Gourdin
This chapter gives an insight into some challenging combinatorial optimization problems that have to be tackled to deliver efficient and appropriate decision algorithms to manage future networks. The first part of the chapter is dedicated to variants of routing optimization problems in future IP networks, and the second part is dedicated to two optimization problems related to network virtualization and 5G network slicing, the virtual network embedding problem and the service function chaining problem. Each of these optimization problems is described along with the main challenges to overcome, and a recent and extensive related state of the art is given, so as to highlight the most recent and promising approaches to solve them.
本章深入探讨了一些具有挑战性的组合优化问题,这些问题必须解决,以提供有效和适当的决策算法来管理未来的网络。本章第一部分研究了未来IP网络中路由优化问题的变体,第二部分研究了与网络虚拟化和5G网络切片相关的两个优化问题,即虚拟网络嵌入问题和业务功能链问题。这些优化问题中的每一个都与要克服的主要挑战一起描述,并给出了最近和广泛的相关技术状态,以便突出最新和有希望的解决方法。
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引用次数: 2
Interference Management Techniques for Device-to-Device Communications 设备对设备通信的干扰管理技术
Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-6210-8.CH010
Weston Mwashita, M. Odhiambo
The snowballing of many different electronic gadgets connected to different networks and to the internet is a clear indication that the much-anticipated internet of things (IoT) is fast becoming a reality. It is generally agreed that the next generation mobile networks should offer wireless connection to anything and anyone with a proper enabling device at any time leading to the full realization of IoT. Device-to device (D2D) communication is one technology that the research community believes will aid the implementation of the next generation of mobile networks, specifically 5G. Full roll out of D2D is however being impeded by the resulting interference. This chapter looks at the state-of-the-art research works on interference management technologies proposed for device-to-device communications. A comprehensive analysis of the proposed schemes is given and open challenges and issues that need to be considered by researchers in D2D communication for it to become a key enabler for 5G technology are highlighted and recommendations provided.
许多不同的电子设备连接到不同的网络和互联网,这清楚地表明,人们期待已久的物联网(IoT)正在迅速成为现实。人们普遍认为,下一代移动网络应该在任何时候通过适当的启用设备向任何事物和任何人提供无线连接,从而全面实现物联网。研究人员认为,设备对设备(D2D)通信技术将有助于实现下一代移动网络,特别是5G。然而,D2D的全面推出受到由此产生的干扰的阻碍。本章着眼于设备对设备通信中提出的干扰管理技术的最新研究工作。对拟议方案进行了全面分析,并强调了D2D通信研究人员需要考虑的开放挑战和问题,以使其成为5G技术的关键推动者,并提供了建议。
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引用次数: 2
SMARC
Pub Date : 1900-01-01 DOI: 10.4018/978-1-7998-7708-0.ch021
W. F. Elsadek, M. Mikhail
Next-generation network promises to integrate cross-domain carriers; thus, infrastructure can be provided as a service. 5G-PPP's vision is directed toward solving existing 4G LTE mobility challenges that congest core networks, disrupt multimedia and data transfer in high mobility situations such as trains or cars. This research adopts 5G methodology by using software-defined networking (SDN) to propose a novel mobile IP framework that facilitates seamless handover, ensures session continuity in standard and wide area coverage, and extends residential/enterprise indoor services across carriers under service level agreement while ensuring effective offload mechanism to avoid core network congestion. Performance excels existing protocols in setup and handover delays such as eliminating out-band signaling in bearer setup/release and isolating users' packets in virtual paths. Handover across cities in wide area motion becomes feasible with lower latency than LTE handover inside city. Extending indoor services across carriers becomes equivalent to LTE bearer setup inside a single carrier's PDN.
下一代网络承诺整合跨域运营商;因此,基础设施可以作为服务提供。5G-PPP的愿景是解决现有的4G LTE移动性挑战,这些挑战使核心网络拥挤,在火车或汽车等高移动性情况下破坏多媒体和数据传输。本研究采用5G方法,采用软件定义网络(SDN),提出了一种新的移动IP框架,实现无缝切换,确保标准和广域覆盖下的会话连续性,并在服务水平协议下跨运营商扩展住宅/企业室内业务,同时确保有效的卸载机制,避免核心网拥塞。性能优于现有协议的设置和切换延迟,如在承载设置/释放中消除带外信令和在虚拟路径中隔离用户数据包。广域运动下的城际切换比LTE城内切换具有更低的时延。跨运营商扩展室内业务相当于在单个运营商的PDN内设置LTE承载。
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引用次数: 0
Importance of Cloud Computing in 5G Radio Access Networks 云计算在5G无线接入网络中的重要性
Pub Date : 1900-01-01 DOI: 10.4018/978-1-7998-1152-7.ch010
Wael S. Afifi, A. El-Moursy, M. Saad, S. Nassar, H. El-Hennawy
The fifth generation of wireless networks (5G) will kick off with evolved mobile broadband services as promised by several mobile-related associations, researchers, and operators. Compared to 4G, 5G aims to provide greater data rates with lower latency and higher coverage to numerous users who stream ubiquitous multimedia services. 5G benefits the innovation of internet of things (IoT) as well. To this end, several modifications in the network architecture are required. This chapter is discussing the role of cloud computing centers in 5G networks, and how such integration could be implemented as found in the literature. The benefits of cloud/5G integration will be explained as well. In addition, some challenges related to the integration will be demonstrated.
正如几个移动相关协会、研究人员和运营商所承诺的那样,第五代无线网络(5G)将以演进的移动宽带服务开始。与4G相比,5G旨在为传输无处不在的多媒体服务的众多用户提供更高的数据速率、更低的延迟和更高的覆盖范围。5G也有利于物联网的创新。为此,需要对网络架构进行一些修改。本章将讨论云计算中心在5G网络中的作用,以及如何在文献中实现这种集成。云/5G集成的好处也将得到解释。此外,还将演示与集成相关的一些挑战。
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引用次数: 1
Tactile Internet and the Remote Surgeon 触觉互联网和远程外科医生
Pub Date : 1900-01-01 DOI: 10.4018/978-1-7998-1851-9.ch015
M. I. Majid, Tahniyat Aslam, Ahmed Mujtaba Hashmi, Danyal Subzwari, Babar Siddiqui
The delivery of healthcare in remote rural areas is a global phenomenon. Using digital governance, a discretized cluster of node relaying time-sensitive, and reliable data, life-critical health services can be ensured. Here tactile internet-based internet of things (IoT) and its variant internet of medical things (IoMT), as well as tactile internet, is introduced. Its relationship with 5G is explored. A model for e-health implementation using unmanned autonomous vehicles (UAVs) in the backhaul is presented. The link is analyzed over fiber optics, satellite, and 5G network in terms of latency and reliability: the crucial metrics for robotic surgery. It is also shown that 5G implemented in Italy, Zimbabwe, and Cooks Island have supported mobile hospitals in rural regions. Hence, induction of 5G networks is a feasible approach. Finally, a critical review of expected future technologies including telematics is presented. Hence, tactile internet-based robotic surgery can reduce the digital divide.
在偏远农村地区提供保健服务是一种全球现象。使用数字治理,一个离散的节点集群中继时间敏感和可靠的数据,可以确保生命攸关的健康服务。本文介绍了基于触觉互联网的物联网(IoT)及其变体医疗物联网(IoMT)以及触觉互联网。探讨了其与5G的关系。提出了一种在回程中使用无人驾驶飞行器(uav)实现电子医疗的模型。通过光纤、卫星和5G网络分析链路的延迟和可靠性:这是机器人手术的关键指标。研究还表明,在意大利、津巴布韦和库克岛实施的5G支持了农村地区的移动医院。因此,引入5G网络是一种可行的方法。最后,对包括远程信息处理在内的未来技术进行了评述。因此,基于互联网的触觉机器人手术可以减少数字鸿沟。
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引用次数: 2
Game Theory for Co-Tiered Interference Mitigation in 5G Small-Cell Networks 5G小蜂窝网络中协同层干扰抑制的博弈论
Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-1712-2.CH007
Ducheng Wu, Qi-hui Wu, Yuhua Xu
Small-cell technologies are seen as one of the most promising solutions for the rapid growth of wireless data services and 5G requirements. However, because most SBSs are deployed with minimum intervention from the end users and the service providers, it is hard to mitigate co-tiered interference. It is significant to study the self-organized distributed co-tiered interference mitigation and resource allocation. Game theory is an effective distributed approach towards handling the distributed co-tiered interference mitigation problem without a central controller. This chapter is to address the application of game theory and distributed learning solutions for distributed co-tiered interference mitigation. Two potential game models for static and dynamic co-tiered interference mitigation are presented and discussed for small-cell networks with fixed loads and dynamic loads separately. In addition, two distributed learning algorithms are presented and results are discussed. Finally, some future research directions are given.
小蜂窝技术被视为无线数据服务和5G需求快速增长的最有前途的解决方案之一。然而,由于大多数SBSs的部署很少受到最终用户和服务提供商的干预,因此很难减轻共层干扰。研究自组织分布式共层干扰抑制和资源分配具有重要意义。博弈论是一种有效的分布式方法,可以在没有中央控制器的情况下处理分布式共层干扰缓解问题。本章将讨论博弈论和分布式学习解决方案在分布式共层干扰缓解中的应用。针对固定负载和动态负载的小蜂窝网络,分别提出和讨论了静态和动态共层干扰抑制的两种潜在博弈模型。此外,还提出了两种分布式学习算法,并对结果进行了讨论。最后,对今后的研究方向进行了展望。
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引用次数: 0
Managing 5G Converged Core With Access Traffic Steering, Switching, and Splitting 管理5G融合核心接入流量转向、交换、分裂
Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-7570-2.CH008
Toktam Mahmoodi, Stephen H. Johnson, M. Condoluci, Vicknesan Ayadurai, M. Cuevas, M. Dohler
This chapter discusses the ongoing work around hybrid access and network convergence, with particular emphasis on recent works on ATSSS in 3GPP. Three main aspects are analyzed: policy enforcement, integration with 5G QoS framework, interaction with underlying multi-path transport protocol. The chapter also provides some preliminary testbed results showing the benefits of ATSSS in the management of multiple accesses analyzing some primary performance indicators such as achievable data rates, link utilization for aggregated traffic, and session setup latency. The chapter also provides some results by considering two examples of realization of ATSSS policies to avoid inefficiency in link utilization and to allow the fulfillment of data rate requirements.
本章讨论了围绕混合接入和网络融合正在进行的工作,特别强调了3GPP中ATSSS的最新工作。主要分析了三个方面:策略实施、与5G QoS框架的集成、与底层多路径传输协议的交互。本章还提供了一些初步的测试结果,显示了ATSSS在多访问管理中的好处,分析了一些主要性能指标,如可实现的数据速率、聚合流量的链路利用率和会话建立延迟。本章还通过考虑ATSSS策略实现的两个示例提供了一些结果,以避免链路利用率低效率并允许实现数据速率要求。
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引用次数: 2
期刊
Research Anthology on Developing and Optimizing 5G Networks and the Impact on Society
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