Energy-, Latency and Resilience-aware Networking

能源、延迟和弹性感知网络

• 批准号: 315036956
• 负责人: Professor Dr.-Ing. Thorsten Herfet
• 金额: --
• 依托单位: Lehrstuhl für Informatik 4: Verteilte Systeme und Betriebssysteme
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 财政年份: 2016
• 资助国家: 德国
• 起止时间: 2015-12-31 至 2021-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/315036956?language=en
• 关键词: Energy; Latency; Resilience; aware; Networking

Explicitly increasing the predictability of the network behavior by bringing latency- and resilience-awareness to the entire cyber-physical network stack has been the major achievement of the project LARN and a significant contribution to the priority program "Cyber-Physical Networking".The continuation project will -- in collaboration within the priority program but also with a sister proposal under the US National Science Foundation's Cyber-Physical Systems program -- extend these results into two important directions:First, energy demand will be addressed. As well for the wired backbone (due to the sheer amount of data) as for wireless nodes (due to the restrictions of battery powered devices) energy-awareness and the optimization of the networks stack towards the reduction of its energy demand becomes inevitable. We will extend the awareness of the overall CPN to besides latency and resilience include energy.Second, we will exploit the predictability to optimally serve cyber-physical systems and the quality of control in those systems. Other than making control algorithms robust against random losses and random delays, we will enable statistical shaping of the network behavior to optimize the coaction of CPNs (networks) and CPSs (systems). For this we will exploit input from control systems researchers within the priority program but also with US colleagues from Wayne State University, Michigan, USA.Hence, we will continue to unite the disciplines "Operating Systems/Real-Time Processing" and "Telecommunications/Information Theory" and complement this through the inclusion of an explicit collaboration with "Control Systems". Two application scenarios (distributed, networked power microgrids and autonomous vehicles) will be addressed and demonstrated by means of a) the provision of RNAs (Reliable Network Atoms) and b) the validation in a real-world wide area network testbed. Both, the RNAs and the testbed will remain to be available to other partners of the SPP and to collaborating projects and researchers from the NSF's CPS program.

LARN项目的主要成就是通过为整个网络物理网络堆栈带来延迟和连续性意识来显着提高网络行为的可预测性，这也是对优先计划“网络物理网络”的重大贡献。该延续项目将与优先计划以及美国国家科学基金会网络计划下的姐妹计划合作，物理系统计划-扩展这些结果到两个重要的方向：第一，能源需求将得到解决。对于有线骨干网（由于数据量巨大）以及无线节点（由于电池供电设备的限制），能量感知和网络堆栈的优化以减少其能量需求变得不可避免。我们将扩展整个CPN的意识，除了延迟和弹性，还包括能量。第二，我们将利用可预测性，以最佳方式服务于网络物理系统和这些系统的控制质量。除了使控制算法对随机损失和随机延迟具有鲁棒性之外，我们还将对网络行为进行统计整形，以优化CPN（网络）和CPS（系统）的共同作用。为此，我们将利用优先计划内的控制系统研究人员的投入，同时也与美国密歇根州韦恩州立大学的美国同事合作。因此，我们将继续联合“操作系统/实时处理”和“电信/信息理论”这两个学科，并通过与“控制系统”的明确合作来补充这一点。两个应用场景（分布式，网络化的电力微电网和自动驾驶汽车）将通过a）提供RNA（可靠的网络原子）和B）在真实世界广域网测试平台中的验证来解决和演示。RNA和测试平台将继续提供给SPP的其他合作伙伴以及NSF CPS计划的合作项目和研究人员。