Making Smart Vehicles Cognitive

Vehicle networks play an increasingly important role in promoting mobile applications, driving safety, network economy, and daily life. It is predicted there will be more than 50 million self-driving cars on the road by 2035; the sheer number and density of vehicles mean non-negligible resources for computing and communication in vehicular environments.

 

It is important to develop a better understanding of the fundamental properties of connected vehicle networks and to create better models and protocols for optimal network performance.

Equipped with a $221,797 NSF grant, Min Song is collaborating with Wenye Wang of North Carolina State University on “The Ontology of Inter-Vehicle Networking with Spatial-Temporal Correlation and Spectrum Cognition.” The pair are investigating the fundamental understanding and challenges of inter-vehicle networking, including foundation and constraints in practice that enable networks to achieve performance limits.

Vehicular communications are driven by the demands and enforcement of intelligent transportation system and standardization activities on DSRC and IEEE 802.11p/WAVE. Many applications, either time-sensitive or delay-tolerant, have been proposed and explored, including cooperative traffic monitoring and control, and recently extended for blind crossing, collision prevention, real-time detour routes computation, and many others. With the popularity of smart mobile devices, there is also an explosion of mobile applications in terrestrial navigation, mobile games, and social networking through Apple’s App Store, Google Play, and Windows.

A systematic investigation of connected vehicles will be done to gain scientific understanding and engineering guidelines critical to achieving optimal performance and desirable services. The merit of the project centers on the development of theoretical and practical foundations for services using inter-vehicle networks. The project starts from the formation of cognitive communication networks and moves on to the coverage of messages. The project further studies how resilient a network is under network dynamics, including vehicular movements, message dissemination, and
routing schemes.

The impact of the research is timely yet long-term, from fully realistic setting of channel modeling, to much-needed applications in vehicular environments, and to transforming performance analysis and protocol design for distributed, dynamic, and mobile systems. The outcome will advance knowledge and understanding not only in the field of vehicular networks, but also mobile ad-hoc networks, cognitive radio networks, wireless sensor networks, and future 5G networks.

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High-Performance Wireless Mesh Networks

A wireless mesh network is a network topology in which each wireless node cooperatively relays data for the network. Song’s CAREER Award project developed distributed interference-aware broadcasting protocols for wireless mesh networks to achieve 100 percent reliability, low broadcasting latency, and high throughput. The problem of network wide broadcasting is a fundamental operation in ad-hoc mesh networks. Many broadcasting protocols have been developed for wireless ad-hoc networks with different focuses. However, these protocols assume a single-radio, single-channel, and single-rate network model and/or a generalized physical model and do not take into account the impact of interference. This project focuses on the design, analysis, and implementation of distributed broadcasting protocols for multi-radio, multi-channel, and multi-rate ad-hoc mesh networks.

Song’s work advances knowledge and understanding in the areas of wireless mesh networks, network optimization, information dissemination, and network performance analysis. Research findings allow the research community and network service providers to better understand the technical implications of heterogeneous networking technologies and cross-layer protocol support, and to create new technology needed for building future wireless mesh networks. The techniques developed in this project will have a broad impact on a spectrum of applications, including homeland security, military network deployment, information dissemination, and daily life. A deep understanding of interference and broadcasting will foster the deployment of more wireless mesh networks, and the development of better network protocols and network architecture. The problems studied are pragmatically and intellectually important and the solutions are critical to several areas such as modeling of wireless communication links, system performance analysis, and algorithms.