Real-Time Scheduling for Internet of Vehicles

车联网实时调度

• 批准号: RGPIN-2017-05578
• 负责人: Lu, Ning
• 金额: $ 1.75万
• 依托单位: Queen's University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=711733
• 关键词: Real; Time; Scheduling; Internet; Vehicles

Internet of Vehicles (IoV) is envisioned to enable next-generation vehicular applications, such as preventive maintenance/diagnostics, feedback-based routing, speed and fuel management, and advanced active safety, among others. As a mission-critical system, IoV is required to guarantee the Quality of Service (QoS) requirements of various services/applications, especially for real-time services with deadline constraints either at packet level or application level. Serving real-time applications is therefore considered as a key component of IoV and many other cyber-physical systems. Despite significant research effort on IoV technology, a mature science to support real-time applications of high-confidence IoV is still missing, and traditional analysis tools/algorithms are unable to cope with the full complexity of IoV or adequately predict system behavior, due to great challenges that arise from the high mobility and intrinsic heterogeneity of such systems. The long-term goal of this research program is to advance the development of efficient and low-complexity scheduling algorithms for delivering heterogeneous services in IoV. The short-term objectives in the next five years are to model and characterize the impact of vehicle mobility on real-time scheduling, to develop a rigorous and systematic framework for design scheduling policies that can achieve optimal performance, and to develop efficient real-time scheduling algorithms considering various engineering costs and constraints. A heterogeneous vehicular connectivity will be considered in this program, where vehicles are capable of connecting to cellular network base stations, Wi-Fi access points, and other vehicles. The proposed research includes three thrusts: (1) Intra-cell scheduling: the development of throughput/utility-optimal scheduling algorithms for enhancing today's cellular network or for next-generation cellular network to serve location-specific IoV services in a real-time manner; (2) Network-wide scheduling: the development of optimal distributed scheduling algorithms for packets with hard deadlines in a vehicular ad hoc network, taking account of both the long-term and short-term guarantees, and flow-level dynamics due to vehicle mobility; (3) Application-level scheduling: the development of optimal application-level scheduling algorithms in favor of cellular traffic steering subject to application delay constraints. It is anticipated that the proposed research program will generate significant scientific, technological, and social impacts in providing the scientific research foundation for supporting real-time applications in IoV. This program will also contribute to the training of highly qualified personnel, providing the trainees with solid knowledge and research background in R&D of IoV, and enabling them to contribute to Canadian high technology industry.

车联网(IoV)旨在实现下一代车辆应用，如预防性维护/诊断、基于反馈的路线选择、速度和燃料管理以及高级主动安全等。作为一个任务关键型系统，IoV需要保证各种服务/应用的服务质量(Quality of Service，简称Qos)要求，尤其是在数据包级和应用级都有截止期限制的实时业务。因此，为实时应用提供服务被视为IoV和许多其他网络物理系统的关键组件。尽管对IoV技术进行了大量研究，但仍然缺乏支持高置信度IoV实时应用的成熟科学，而且由于此类系统的高移动性和内在异构性带来的巨大挑战，传统的分析工具/算法无法应对IoV的全部复杂性或充分预测系统行为。 该研究计划的长期目标是推动高效和低复杂性的调度算法的开发，以便在IoV中交付异类服务。未来五年的短期目标是对车辆机动性对实时调度的影响进行建模和表征，为设计能够达到最优性能的调度策略开发一个严格和系统的框架，并开发考虑各种工程成本和约束的高效实时调度算法。 该计划将考虑不同类型的车辆连接，其中车辆能够连接到蜂窝网络基站、Wi-Fi接入点和其他车辆。拟议的研究包括三个方面： (1)小区内调度：开发吞吐量/效用最优调度算法，以增强今天的蜂窝网络或用于下一代蜂窝网络，以实时方式服务于特定位置的IoV服务； (2)全网调度：在车载自组织网络中，考虑长期和短期保证，以及车辆移动性引起的流级动态，为具有硬截止期限的分组开发最优分布式调度算法； (3)应用级调度：开发最优的应用级调度算法，支持在应用延迟约束下的蜂窝流量调度。 预计拟议的研究计划将在为支持IoV实时应用提供科学研究基础方面产生重大的科学、技术和社会影响。该项目还将有助于培养高素质的人才，为学员提供扎实的IoV研发知识和研究背景，使他们能够为加拿大高科技产业做出贡献。