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Image processing- and other
sensor-based understanding of plant behavior are becoming key to the
new discoveries in plant genotypes leading to a more productive and
environment-friendly farming. Similarly, connectivity and autonomy
are two main drivers of a safe, efficient, and sustainable
transportation vision, and real-world study of connected and
automated vehicles (CAVs) is a key tool towards realizing that
vision. Existing research and education in agriculture and
transportation systems are constrained by the lack of connectivity
between field-deployed equipment and cloud infrastructures. To
fulfill this gap, we will establish the CyNet cyberinfrastructure at
Iowa State University (ISU). CyNet features advanced, field-deployed
wireless networks with open-source hardware and software platforms,
10Gbps software-defined optical networks, and high-performance cloud
computing infrastructures, and it will be connected to national
infrastructures such as GENI and NSFCloud. To transform the CyNet
hardware platforms into a software-defined, shared-use
infrastructure, we will develop and deploy the following systems: 1)
Predictable,
Reliable, Real-time, and high-Throughput (PRRT) wireless
networking solutions from PI Zhang's research group; 2)
Infrastructure virtualization system that partitions CyNet into
programmable, isolated slices; and 3) Infrastructure management
system that performs admission and access control and that decides
specific resource allocation policies. CyNet is expected to stimulate research and field deployment of PRRT wireless networks (e.g., those considered in 5G and beyond). CyNet is also expected to enable transformative plant science studies and farming practice which promise to move agriculture into a new era in which inputs are optimized, farmer profitability is increased, production levels are less variable from year to year, and the ecological foot-print of agriculture is minimized. CyNet will also enable transformative research in connected and automated transportation, which is key to transportation safety, efficiency, and sustainability. CyNet will enable exciting interdisciplinary education activities in networking, computing, agriculture, and transportation, and it will help engage under-represented students in STEM education. Images:
CyNet Wireless
Tower
PhieldCam Phenotyping Cameras
Deployment at
Research Park Headquarter Building
Connected-and-Automated Transportation Research
News & Reports:
Publications (Selected):
Broader Impacts (Selected):
Project Team: PI: Hongwei
Zhang
Co-PIs: Ahmed Kamal, Arun Somani, Patrick Schnable, Anuj Sharma Postdoc: Matthias Sander-Frigau, Stefan Hey Students: Tianyi Zhang, Chen-Ye Lim, Zhibo Meng, Duo Zhang Acknowledgment: The CyNet project is supported in
part by the following programs/organizations:
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