Abstract-Recently, location-oriented services in Vehicular Cyber-Physical System (VCPS) have witnessed significant attention due to their potentiality to address traffic related issues towards on-road safety and efficiency. The multichannel communication aids these services by tuning their overall performance in vehicular environments. The literature on multichannel communication is based on interference as channel quality measure. However, uncertain mobility and density of vehicles significantly affect channel quality apart from interference. The static quantification of channel quality is not suitable due to the dynamic characteristics of the channel quality parameters. In this context, this paper proposes Fuzzy-based Channel Selection framework for location-oriented services in Multichannel VCPS environments (F-CSMV). Specifically, a system model is presented for deriving channel access delay using Markov chain model. The channel quality is estimated using channel access delay (CAD) and signal-to-interference ratio (SIR). The fuzzy logic based channel selection framework is developed focusing on fuzzification and defuzzification of CAD and SIR. The comparative performance evaluation attests the benefit of the framework as compared to the state-of-the-art techniques considering channel and network performance-related metrics in VCPS environments.

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Abstract:The efficiency and scalability of geographical routing depend on the accuracy of location information of vehicles. Each vehicle determines its location using Global Positioning System (GPS) or other positioning systems. Related literature in geographical routing implicitly assumes accurate location information. However, this assumption is unrealistic considering the accuracy limitation of GPS and obstruction of signals by road side environments. The inaccurate location information results in performance degradation of geographical routing protocols in vehicular environments. In this context, this paper proposes a location error resilient geographical routing (LER-GR) protocol. Rayleigh distribution based error calculation technique is utilized for assessing error in the location of neighbouring vehicles. Kalman filter based location prediction and correction technique is developed to predict the location of the neighbouring vehicles. The next forwarding vehicle (NFV) is selected based on the least error in location information. Simulations are carried out to evaluate the performance of LER-GR in realistic environments, considering junction-based as well as real map-based road networks. The comparative performance evaluation attests the location error resilient capability of LER-GR in a vehicular environment.

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