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Safe Cooperating Cyber-Physical Systems using Wireless Communication

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Optimal Rate-Adaptive Data Dissemination in Vehicular Platoons
Publication . Li, Kai; Ni, Wei; Tovar, Eduardo; Guizani, Mohsen
In intelligent transportation systems, wireless connected vehicles moving in platoons can improve roads’ throughput. For managing driving status of the platoon, a lead vehicle transmits driving information to following autonomous vehicles by using multi-hop data dissemination. We study a novel data dissemination protocol which investigates a chain-based transmit rate control to reduce data dissemination latency. The optimal resource allocation algorithm is formulated to minimize the total dissemination latency of the platoon under guaranteed bit error rates, and can be judiciously reformulated and solved using standard optimization techniques. A novel dynamic programming algorithm is presented to solve the platooning resource allocation optimization, which uses backward induction to significantly reduce the resource allocation complexity. In addition, we interpret the vehicular platoon as one-dimensional Markov chain, and derive a closed form of dissemination latency. Simulations are carried out to evaluate the performance of the proposed dynamic programming algorithm. The numerical results show that our algorithm achieves optimal solutions with cutting off the complexity by orders of magnitude, while improving dissemination rate in the vehicular platoon.
Design and Implementation of Secret Key Agreement for Platoon-based Vehicular Cyber-physical Systems
Publication . Li, Kai; Ni, Wei; Emami, Yousef; Shen, Yiran; Severino, Ricardo; Pereira, David; Tovar, Eduardo
In a platoon-based vehicular cyber-physical system (PVCPS), a lead vehicle that is responsible for managing the platoon’s moving directions and velocity periodically disseminates control messages to the vehicles that follow. Securing wireless transmissions of the messages between the vehicles is critical for privacy and confidentiality of the platoon’s driving pattern. However, due to the broadcast nature of radio channels, the transmissions are vulnerable to eavesdropping. In this article, we propose a cooperative secret key agreement (CoopKey) scheme for encrypting/decrypting the control messages, where the vehicles in PVCPS generate a unified secret key based on the quantized fading channel randomness. Channel quantization intervals are optimized by dynamic programming to minimize the mismatch of keys. A platooning testbed is built with autonomous robotic vehicles, where a TelosB wireless node is used for onboard data processing and multihop dissemination. Extensive real-world experiments demonstrate that CoopKey achieves significantly low secret bit mismatch rate in a variety of settings. Moreover, the standard NIST test suite is employed to verify randomness of the generated keys, where the p-values of our CoopKey pass all the randomness tests. We also evaluate CoopKey with an extended platoon size via simulations to investigate the effect of system scalability on performance.
DynaMO—Dynamic Multisuperframe Tuning for Adaptive IEEE 802.15.4e DSME Networks
Publication . Kurunathan, Harrison; Severino, Ricardo; Koubaa, Anis; Tovar, Eduardo
Recent advancements in the IoT domain have been pushing for stronger demands of Qualityof-Service (QoS) and in particular for improved determinism for time-critical wireless communications under power constraints. The IEEE 802.15.4e standard protocol introduced several new MAC behaviors that provide enhanced time-critical and reliable communications. The Deterministic Synchronous Multichannel Extension (DSME) is one of its prominent MAC behaviors that combines contention-based and contentionfree communication, guaranteeing bounded delays and improved reliability and scalability by leveraging multi-channel access and CAP reduction. However, DSME has a multi-superframe structure, which is statically defined at the beginning of the network. As the network evolves dynamically by changing its traffic characteristics, these static settings can affect the overall throughput and increase the network delay because of improper allocation of bandwidth. In this paper, we address this problem, and we present a dynamic multi-superframe tuning technique that dynamically adapts the multi-superframe structure based on the size of the network. This technique improves the QoS by providing 15-30% increase in throughput and 15-35% decrease in delay when compared to static DSME networks

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European Commission

Funding programme

H2020

Funding Award Number

692529

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