Remote and Rural Connectivity: Infrastructure and Resource Sharing Principles

Thembelihle Dlamini, S. Vilakati
{"title":"Remote and Rural Connectivity: Infrastructure and Resource Sharing Principles","authors":"Thembelihle Dlamini, S. Vilakati","doi":"10.1155/2021/6065119","DOIUrl":null,"url":null,"abstract":"As mobile networks (MNs) are advancing towards meeting mobile user requirements, the rural-urban divide still remains a major challenge. While areas within the urban space (metropolitan mobile space) are being developed, i.e., small Base Stations (BSs) empowered with computing capabilities are deployed to improve the delivery of user requirements, rural areas are left behind. Due to challenges of low population density, low income, difficult terrain, nonexistent infrastructure, and lack of power grid, remote areas have low digital penetration. This situation makes remote areas less attractive towards investments and to operate connectivity networks, thus failing to achieve universal access to the Internet. In addressing this issue, this paper proposes a new BS deployment and resource management method for remote and rural areas. Here, two MN operators share their resources towards the procurement and deployment of green energy-powered BSs equipped with computing capabilities. Then, the network infrastructure is shared between the mobile operators, with the main goal of enabling energy-efficient infrastructure sharing, i.e., BS and its colocated computing platform. Using this resource management strategy in rural communication sites guarantees a quality of service (QoS) comparable to that of urban communication sites. The performance evaluation conducted through simulations validates our analysis as the prediction variations observed show greater accuracy between the harvested energy and the traffic load. Also, the energy savings decrease as the number of mobile users (50 users in our case) connected to the remote site increases. Lastly, the proposed algorithm achieves 51% energy savings when compared with the 43% obtained by our benchmark algorithm. The proposed method demonstrates superior performance over the benchmark algorithm as it uses foresighted optimization where the harvested energy and the expected load are predicted over a given short-term horizon.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"6 1","pages":"6065119:1-6065119:12"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Wirel. Commun. Mob. Comput.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2021/6065119","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

As mobile networks (MNs) are advancing towards meeting mobile user requirements, the rural-urban divide still remains a major challenge. While areas within the urban space (metropolitan mobile space) are being developed, i.e., small Base Stations (BSs) empowered with computing capabilities are deployed to improve the delivery of user requirements, rural areas are left behind. Due to challenges of low population density, low income, difficult terrain, nonexistent infrastructure, and lack of power grid, remote areas have low digital penetration. This situation makes remote areas less attractive towards investments and to operate connectivity networks, thus failing to achieve universal access to the Internet. In addressing this issue, this paper proposes a new BS deployment and resource management method for remote and rural areas. Here, two MN operators share their resources towards the procurement and deployment of green energy-powered BSs equipped with computing capabilities. Then, the network infrastructure is shared between the mobile operators, with the main goal of enabling energy-efficient infrastructure sharing, i.e., BS and its colocated computing platform. Using this resource management strategy in rural communication sites guarantees a quality of service (QoS) comparable to that of urban communication sites. The performance evaluation conducted through simulations validates our analysis as the prediction variations observed show greater accuracy between the harvested energy and the traffic load. Also, the energy savings decrease as the number of mobile users (50 users in our case) connected to the remote site increases. Lastly, the proposed algorithm achieves 51% energy savings when compared with the 43% obtained by our benchmark algorithm. The proposed method demonstrates superior performance over the benchmark algorithm as it uses foresighted optimization where the harvested energy and the expected load are predicted over a given short-term horizon.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
偏远和农村互联互通:基础设施和资源共享原则
随着移动网络(MNs)朝着满足移动用户需求的方向发展,城乡鸿沟仍然是一个重大挑战。虽然正在开发城市空间内的区域(都市流动空间),即部署具有计算能力的小型基站,以改善用户需求的提供,但农村地区却落在后面。由于人口密度低、收入低、地形复杂、基础设施不存在、电网缺乏等挑战,偏远地区数字普及率较低。这种情况使偏远地区对投资和运营连接网络的吸引力降低,从而无法实现普遍接入互联网。针对这一问题,本文提出了一种针对偏远农村地区的BS部署和资源管理新方法。在这里,两家移动网络运营商共享资源,采购和部署配备了计算能力的绿色能源移动电话。然后,网络基础设施在移动运营商之间共享,主要目标是实现节能基础设施共享,即BS及其托管计算平台。在农村通信站点中使用这种资源管理策略可以保证与城市通信站点相当的服务质量(QoS)。通过模拟进行的性能评估验证了我们的分析,因为观察到的预测变化在收获的能量和交通负载之间显示出更高的准确性。此外,随着连接到远程站点的移动用户数量(在我们的示例中为50个用户)的增加,节省的能源也会减少。最后,与基准算法的43%节能相比,本文算法实现了51%的节能。所提出的方法表现出优于基准算法的性能,因为它使用了前瞻优化,其中在给定的短期范围内预测收获的能量和预期负荷。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
AI-Empowered Propagation Prediction and Optimization for Reconfigurable Wireless Networks C SVM Classification and KNN Techniques for Cyber Crime Detection A Secure and Efficient Energy Trading Model Using Blockchain for a 5G-Deployed Smart Community Fusion Deep Learning and Machine Learning for Heterogeneous Military Entity Recognition Influence of Embedded Microprocessor Wireless Communication and Computer Vision in Wushu Competition Referees' Decision Support
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1