Towards Green Wireless Networks: Energy-Aware Techniques for Emerging Applications with Evolving Network Architectures

迈向绿色无线网络：采用不断发展的网络架构的新兴应用的能源感知技术

• 批准号: RGPIN-2015-04641
• 负责人: Song, Wei
• 金额: $ 1.82万
• 依托单位: University of New Brunswick
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=761630
• 关键词: Towards; Green; Wireless; Networks; Energy

The past decade has witnessed an explosive growth of tremendous mobile traffic, pervasive smart devices, and assorted new applications. While this growth leads to increasing revenue for the global mobile industry, there are rising concerns on environmental impact and high capital/operating expenditure. Driven by the pressing needs from both economical and ecological perspectives, energy efficiency and greening becomes one of the dominant themes for 5G wireless networks. Although such demands have attracted considerable attentions and efforts from the academia and industry, the evolving network architectures need to be continuously augmented with green networking algorithms to fully harvest the potentials. Meanwhile, new user-driven applications keep emerging and call for efficient solutions to maintain sustainable growth.This research program will contribute to the evolution towards next-generation green wireless networks through exploring energy-aware techniques that leverage evolving network architectures, smarter mobile devices, and diverse characteristics of a plethora of emerging applications. Particularly, we will focus on three thrusts. First, exploiting the intelligence of smart devices, we will develop new algorithms for cooperation cluster grouping, task assignment, and incentive for user participation. Energy-efficient multipath transport protocols with user cooperation will also be studied by balancing throughput performance and energy consumption. Second, taking advantage of multi-tier radio access networks, we will develop traffic-aware sleep schemes for different types of base stations, and service-differentiated scheduling schemes for small cells powered by renewable energy sources. Third, leveraging the evolving mobile core with in-network caching, we will develop smart routing algorithms that can reduce energy consumption by shifting traffic while ensuring user quality-of-experience (QoE).This research is expected to benefit Canadian industry by providing guidelines and references for wireless service providers to expand their service capacity while saving capital/operating expenditures. There will also be significant benefits to Canadian society through energy conservation for environment protection. Highly-qualified personnel will be trained in this program and will contribute to the progress of green wireless networks.

在过去的十年中，移动流量，普遍的智能设备以及各种新应用程序的爆炸性增长。尽管这种增长导致全球移动产业的收入增加，但人们对环境影响和高资本/运营支出的担忧越来越令人担忧。从经济和生态学角度来看，能源效率和绿化成为5G无线网络的主要主题之一。尽管这种需求吸引了学术界和行业的大量关注和努力，但不断发展的网络体系结构需要通过绿色网络算法不断增强，以充分收获潜力。同时，新的以用户驱动的应用程序不断出现，并呼吁有效的解决方案维持可持续增长。该研究计划将通过探索能源感知的技术来促进下一代绿色无线网络的发展，从而利用网络体系结构，智能移动设备以及杂货应用程序的多样性特征。特别是，我们将专注于三个推力。首先，利用智能设备的智能，我们将开发用于合作集群分组，任务分配和用户参与的动机的新算法。通过平衡吞吐量性能和能源消耗，还将研究具有用户合作的节能多径运输协议。其次，利用多层无线电访问网络，我们将针对不同类型的基站开发流量吸引人的睡眠方案，并为由可再生能源提供动力的小单元的服务分化的调度方案。第三，通过网络内的缓存利用不断发展的移动核心，我们将开发智能路由算法，这些算法可以通过移动流量来减少能源消耗，同时确保用户体验质量（QOE）（QOE）。这项研究有望通过提供无线服务提供商的指南和参考来使加拿大行业受益，以增强其服务能力，以便在资本使用ebtapertirss and Servianturs and Sepainite-Operative upercenditures。通过节能环境保护，加拿大社会也将带来重大好处。高度合格的人员将在该计划中接受培训，并将为绿色无线网络的进度做出贡献。