Energy-, Latency and Resilience-aware Networking

通过将延迟和弹性意识引入整个网络物理网络堆栈，明确地增加网络行为的可预测性，这是LARN项目的主要成就，也是对“网络物理网络”优先计划的重大贡献。继续项目将在优先项目内合作，同时也与美国国家科学基金会网络物理系统项目的姊妹提案合作，将这些结果扩展到两个重要方向：首先，将解决能源需求问题。对于有线骨干网（由于庞大的数据量）和无线节点（由于电池供电设备的限制）来说，能量意识和优化网络堆栈以减少其能量需求是不可避免的。我们将扩大对整体CPN的认识，除了延迟和弹性，还包括能量。其次，我们将利用可预测性来优化服务于网络物理系统和这些系统中的控制质量。除了使控制算法对随机损失和随机延迟具有鲁棒性外，我们还将使网络行为的统计塑造能够优化cpn（网络）和cps（系统）的合作。为此，我们将利用优先项目内的控制系统研究人员以及来自美国密歇根州韦恩州立大学的美国同事的意见。因此，我们会继续整合“操作系统/实时处理”及“电讯/资讯理论”两门学科，并透过与“控制系统”的明确合作加以补充。两种应用场景（分布式、网络化电力微电网和自动驾驶汽车）将通过a)提供rna（可靠网络原子）和b)在现实世界的广域网测试平台上进行验证来解决和演示。rna和试验台都将继续提供给SPP的其他合作伙伴，以及NSF CPS项目的合作项目和研究人员。

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.