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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 NSF 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 the GENI cloud computing infrastructure 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 will help 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 platform 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 demo in the Plenary VIP Demo session of the 22nd NSF GENI Engineering Conference on March 25, 2015 in Washington, DC
Testimonial from the Chief of Police, Wayne State University
Our work won the Best Demo Award at the 21st NSF GENI Engineering Conference and the Best Demo First Runner-up Award at the 20th NSF GENI Engineering Conference.
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, we are deploying 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. We are also developing and deploying 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.
Additional information: A Paper on NetEye | Kansei Genie Wiki
ExoGENI: Network-Agile Multi-Provisioned Infrastructure for GENI
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 ˇ°racksˇ± 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 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 intend 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.
Our contributions to Kansei were 1) designing the 210-node 802.11 network such that link and network properties in Kansei mimic those outdoor, 2) designing the experiment scheduler to enable flexible and dependable experimentation, and 3) setting up the hardware and software platforms for Kansei. To facilitate high-fidelity wireless network experimentation, in particular, we have studied both indoor and outdoor wireless link properties, and have co-designed the network system (such as signal attenuators and small form-factor omni-directional antennae) to enable high-fidelity experimentation with reconfigurable network setup (e.g., node distribution density, wireless link reliability, etc.).
Our contributions to the project were twofold. First, to provide real-time and reliable data transport over the IEEE 802.11b mesh network of the ~210 Stargates, we studied the IEEE 802.11b link properties (e.g., MAC transmission time and reliability) in the presence of bursty event traffic, and accordingly we designed and implemented a beacon-free routing protocol Learn On The Fly (LOF). Instead of using beacon packets, LOF estimates link properties based on data traffic itself. Since it models the network state in the presence of data traffic, LOF chooses routes that incur shorter delay and less energy consumption than those chosen by beacon-based protocols (e.g., those using beacon-based ETX metric). Second, to reduce channel contention and to balance load at the XSM mote network, we assisted in designing the routing protocol Logical Grid Routing (LGR).
Our major contribution to the project was designing and implementing mechanisms to transport, reliably and in real-time, large bursts of data packets from different network locations to a base station (one major technical challenge of the project). With existing messaging services, only 50% data were successfully delivered and packet delivery was also significantly delayed, which was insufficient for supporting application logic. To tackle this challenge, we studied the limitations of existing transport control techniques, and we designed a new protocol Reliable Bursty Convergecast (RBC): to alleviate retransmission-incurred channel contention, we introduced differentiated contention control; to improve channel utilization and to reduce ack-loss, we designed a window-less block acknowledgment scheme that guarantees continuous packet forwarding (regardless of packet as well as ack loss) and replicates the acknowledgment for a packet. Moreover, we designed mechanisms to handle varying ack-delay and to reduce delay in timer-based retransmissions. With RBC, 96% data were successfully delivered in real-time such that the network goodput was close to optimal.
Open-Source Software [top]
TinyOS code for the PRK-Based Scheduling (PRKS) Protocol
TinyOS-2.x code for the PRKS protocol. A paper about the PRKS protocol is also available here.
TinyOS code for the Multi-Timescale-Adaptation (MTA) Real-Time Routing Protocol
TinyOS-2.x code for the MTA protocol. A paper about the MTA protocol is also available here.
TinyOS code for the Reliable-Bursty-Convergecast (RBC) protocol
TinyOS-1.x code for the RBC protocol. A paper about the RBC protocol is also available here.
Reliably fetching MAC feedback for IEEE 802.11 devices in Linux
We enhanced the Linux kernel and hostap driver to reliably expose MAC layer feedbak for each frame transmission.
TinyOS code for different data-driven link estimation & routing protocols in wireless sensor networks
TinyOS-1.x code for the L-* protocols. A paper comparing different data-driven link estimation methods is also available here.
TinyOS code for Delay-Constrained Packet Packing in Wireless Sensor Networks
TinyOS-2.x code for tPack protocol. A paper presenting tPack is also available here.