For at-scale, high-fidelity evaluation of vehicular sensing and control (VSC) networking and applications research as well as for robust, sustainable operation of the GENI infrastructure, we develop a multidimensional emulation system for networked vehicular sensing and control. The emulation system integrates at-scale simulation of VSC networks in GENI racks with in-field WiMAX and VSC channel measurements as well as high-fidelity sensing of vehicle internal and external state. As a part of the project, we develop a virtualized VSC platform with OpenXC-based sensing of vehicle internal state, camera-based sensing of vehicle external state, and real-time wireless channel measurement. The virtualized VSC platforms have been deployed in Wayne State University campus patrol vehicles and are networked with the GENI backbone infrastructures through the GENI WiMAX network on campus. The emulation system has been validated through experiments with the deployed VSC platforms, the GENI WiMAX network, and the GENI racks.
The virtualized VSC platform and the emulation system are of interest to both researchers and end-users of VSC networks and applications. For instance, the virtualized VSC platform enables non-interfering, simultaneous access to the same platform by multiple users, thus it helps different communities of vehicular sensing and control to synergize their effort and to advance different aspects of the field (e.g., networking, control, human interaction, and applications) in a concerted manner. The virtualized platform also enables incremental deployment of new technologies and applications, since the platform serves as an enabler for non-interfering execution of older and newer applications on the same platform. The long-lived deployment and operation of the VSC platforms on Wayne State University police patrol vehicles also serve as live examples and convincing evidence for other related communities to consider this virtualized platform for their deployments of vehicular sensing and control infrastructures.
A video summarizing our vision for "Platforms and Infrastructures for Collaborative, Open Innovation in Connected and Automated Vehicles"
Our work won the Best Demo Award at the 21st NSF GENI Engineering Conference and the First Runner-up Demo Award at the 20th NSF GENI Engineering Conference.
Transforming the traditional, single-vehicle-oriented fuel economy optimization, networked fuel economy optimization will significantly improve the fuel economy of road vehicles. Based on Cloud-provisioned road and traffic conditions, for instance, optimally controlling the speed, throttle, and gear of 2007 Ford Focus can improve fuel economy by 33-77%; having vehicles sense and share information about traffic flow, road condition, and control actions enables platoon-oriented control which can further improve fuel economy by up to 20%. The great fuel economy will improve the travel ranges of PHEVs and will reduce vehicle ownership cost as well as greenhouse gas emissions. Networked fuel economy and emission control can also be integrated with vehicle operations such as route planning and adaptive cruise control in the short-term, vehicle tethering in the near-term, and autonomous driving in the long-term.
One basis for the above vision of networked fuel economy optimization is for the vehicles, the transportation infrastructures, and the Cloud to exchange real-time sensing and/or control information through vehicular wireless networks. Inheriting the basic designs of WiFi which was not developed for real-time control, however, the existing vehicular wireless networking technology Dedicated Short-Range Communications (DSRC)/IEEE-802.11p cannot ensure predictable, real-time information delivery. Our study has found out that, when the sensing sampling rate and thus the load of information exchange is high, the current DSRC technology may not even be able to ensure an information delivery ratio of 40%. To address the gap between the current practice of wireless networking and the stringent real-time requirements by networked fuel economy control, this project investigates the architectures and protocols for predictable, real-time inter-vehicle wireless communication.
In supporting mission-critical tasks such as those in industrial automation and the next-generation vehicles, message passing in wireless networked sensing and control systems is required to be reliable and in real-time. Nonetheless, the design priorities on reliability and real-time require us to rethink the models and protocols for messaging, we still lack an interference model that is local and accurate for distributed protocol design, and the basic problem of computing probabilistic path delays is NP-hard. Focusing on single-hop transmission scheduling and multi-hop spatiotemporal data flow control, we address these challenges by pursuing the following tasks: 1) Based on our physical-ratio-K (PRK) interference model, we investigate control-theoretic approaches to online model instantiation, and we address the challenges of large interference range as well as anisotropic, asymmetric wireless communication; 2) We propose a lightweight approach to computing probabilistic path delays, and we propose a multi-timescale adaptation framework for real-time messaging. The proposed research makes novel contributions to the models, protocols, and network planning tools for reliable, real-time wireless messaging. For instance, our PRK interference model integrates protocol model's locality with physical model's high-fidelity, thus it bridges the gap between the suitability for distributed implementation and the enabled scheduling performance. By controlling network operations at the same timescale of the corresponding dynamics, our multi-timescale adaptation framework ensures long-term optimality while addressing short-term dynamics at the same time.
Along with the research, we also pursue an integrated, multi-level, multi-component education plan. Our education activities will raise public awareness and will improve student retention and the participation of underrepresented groups in computing.
This project proposes a cross-layer framework in which vehicular wireless networking and platoon control interact with each other to tame cyber-physical uncertainties. Based on the real-time capacity region of wireless networking and the physical process of vehicle movements, platoon control selects its control strategies and the corresponding requirements on the timeliness and throughput of wireless data delivery to optimize control performance. Based on the requirements from platoon control, wireless networking adapts to cyber-physical uncertainties to ensure the timeliness and throughput of single-hop as well as multi-hop broadcast. For proactively addressing the impact of vehicle mobility on wireless broadcast, wireless networking also leverages input from platoon control on vehicle movement prediction. In realizing the cross-layer framework, wireless scheduling ensures agile, predictable interference control in the presence of cyber-physical uncertainties. Networked control with random topology switching and time delay serves as a new framework for platoon control as well as for control theory as a discipline and for stochastic differential equations as a mathematical subject. The mathematical tools serve as a foundation for reasoning about the jointly-optimized wireless networking and platoon control.
This project will enable the development of wireless vehicular CPS towards safe, efficient, and clean transportation. The principles and techniques for taming cyber-physical uncertainties will provide insight into other application domains of wireless networked sensing and control such as unmanned aerial vehicles and smart power grids. This project will also enable integrative research and education in wireless CPS through a multi-level, multi-component education practice.
2013 Project Summary.
WiMAX represents a latest broadband wireless access technology that employees cutting-edge wireless communication techniques such as MIMO and OFDMA, and it serves as a basic platform for evaluating broadband wireless access in real-world settings. WiMAX is expected to play a major role in areas such as smart grid, smart transportation, vehicular infotainment, and community Internet access. Towards building an experimental infrastrcuture for research, education, and application exploration, this project will deploy a multi-sector/cell WiMAX network in Metro Detroit which supports handoff, virtualization, and scientific measurement. The WiMAX network will be connected via VLAN to the GENI backbone network. This project will also develop and deploy a WiMAX mobile station platform that supports scientific measurement as well as application exploration. This GENI WiMAX network is expected to enable research, education, and application exploration in smart transportation, smart grid, wireless networked sensing and control, and community services.
A demo on the project.
ExoGENI is a GENI experimental infrastructure that links GENI to two advances in virtual infrastructure services outside of GENI: open cloud computing (OpenStack) and dynamic circuit fabrics. ExoGENI orchestrates a federation of independent cloud sites located across the US and circuit providers, like NLR and Internet2 through their native IaaS API interfaces, and links them to other GENI tools and resources.
Individual ExoGENI deployments consist of cloud site ¡°racks¡± on host campuses, linked with national research networks through programmable exchange points. The ExoGENI sites and control software are enabled for flexible networking operations using traditional VLAN-based switching and OpenFlow. Using the ORCA (Open Resource Control Architecture) control framework software, ExoGENI offers a powerful unified hosting platform for deeply networked, multi-domain, multi-site cloud applications. We expect that ExoGENI will seed a larger, evolving platform linking other third- party cloud sites, transport networks, and other infrastructure services, and that it will enable real-world deployment of innovative distributed services and new visions of a Future Internet.
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