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.

过去十年见证了巨大的移动的流量、普及的智能设备和各种新应用的爆炸式增长。虽然这种增长导致全球移动的行业收入增加，但人们对环境影响和高资本/运营支出的担忧日益增加。在经济和生态角度的迫切需求的推动下，能源效率和绿色成为5G无线网络的主导主题之一。尽管这些需求引起了学术界和工业界的广泛关注和努力，但不断发展的网络架构需要通过绿色网络算法不断增强，以充分挖掘潜力。同时，新的用户驱动的应用不断涌现，需要高效的解决方案来保持可持续的增长。本研究计划将通过探索能量感知技术，利用不断发展的网络架构，更智能的移动的设备和大量新兴应用的多样化特征，为下一代绿色无线网络的发展做出贡献。特别是要抓好三个方面。首先，利用智能设备的智能，我们将开发新的算法，用于协作集群分组，任务分配和激励用户参与。通过平衡吞吐量性能和能量消耗，还将研究具有用户协作的节能多路径传输协议。其次，利用多层无线接入网络，我们将为不同类型的基站开发流量感知的睡眠方案，并为可再生能源供电的小型小区开发服务差异化调度方案。第三，利用不断发展的移动的核心与网内缓存，我们将开发智能路由算法，可以减少能源消耗，通过转移流量，同时确保用户体验质量（QoE）。这项研究预计将有利于加拿大的行业提供指导和参考，为无线服务提供商扩大其服务容量，同时节省资本/运营支出。通过节约能源保护环境，也将给加拿大社会带来重大利益。高素质的人员将在这个计划中得到培训，并将有助于绿色无线网络的进步。