Systems and Open-Source Software   

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Systems   [top

ARA: Wireless Living Lab for Smart and Connected Rural Communities
Iowa State University, University of California - Irvine, Ohio State University, International Computer Science Institute

ARA is an at-scale platform for advanced wireless research to be deployed across the Iowa State University (ISU) campus, City of Ames (where ISU resides), and surrounding research and producer farms as well as rural communities in central Iowa, spanning a rural area with diameter over 60km. It serves as a wireless living lab for smart and connected rural communities, enabling the research and development of rural-focused wireless technologies that provide affordable, high-capacity connectivity to rural communities and industries such as agriculture.

CyNet: End-to-End Software-Defined Cyberinfrastructure for Smart Agriculture and Transportation
Iowa State University, Ames, Iowa

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 are establishing 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.


At-Scale, High-Fidelity Emulation System and Collaborative, Open Innovation Platforms for Vehicular Sensing and Control Networking and Applications

Wayne State University, Ford Research, Georgia Institute of Technology, University of Michigan - Dearborn

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.



GENI WiMAX Research Network in Metro Detroit

Wayne State University, Ford Research, Intel Labs, Community Telecommunications Network

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.


KanseiGenie: Federated WSN Experimental Infrastructure  

Ohio State University, Wayne State University, USA             

KanseiGenie is a federated wireless sensor network (WSN) infrastructure for at-scale experimentation with heterogeneous wireless and sensing platforms. It currently includes WSN infrastructures from Ohio State University, Wayne State University, and Oklahoma State University, and it is expected to incorporate WSN infrastructures from other countries such as India and China too. The system is developed as a part of our NSF GENI project KanseiGenie.


NetEye: Networked Embedded Sensing Testbed

Wayne State University, Detroit, Michigan, USA                                                     

NetEye consists of 130 TelosB motes (with IEEE 802.15.4 radios), 15 Dell Vostro laptops (with IEEE 802.11 b/g radios), and one compute server which are deployed in State Hall --- the Computer Science building at Wayne State University. In addition to providing a local facility for supporting research and educational activities, NetEye is being connected to Kansei as a part of the Kansei consortium; Kansei consortium is initiated to enable experimentation across shared, widely distributed sensornet testbeds at organizations such as Wayne State University, The Ohio State University, Los Alamos National Laboratory, and ETRI, Korea. NetEye and the Kansei consortium are designed and implemented to be interoperable with NSF GENI (i.e., Global Environment for Network Innovations), and, through funding from the NSF GENI program, are being incorporated into the national GENI facility. NetEye also provides live sensing data (e.g., environmental noise, temperature, and humidity) that can be used to drive experimentations and to provide useful information about occupational health in urban universities.

Additional informationKanseiGenie 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 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 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.



Kansei: Sensor Network Testbed for At-Scale Experiments

Consisting of 210 Extreme Scale Motes (XSM) and 210 Extreme Scale Stargates (XSS), Kansei provides a testbed infrastructure to conduct experiments with both IEEE 802.11 and mote networks.

Ohio State University, Columbus, Ohio

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.).


ExScal: Extreme Scaling in Wireless Sensor Networks    
DARPA Networked Embedded Systems Technology (NEST) field demonstration
Avon Park, Florida, December 14, 2004.
(Media: The Lanter news report, 2004.)          

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).


A Line in the Sand
DARPA Networked Embedded Systems Technology (NEST) field demonstration
MacDill Air Force base, Florida, August 20, 2003.
(Media: News report from CBS and ONN, Sept. 8, 2003; The cover story of News in Engineering, The Ohio State University, Autumn 2003.)

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.