Reliable Multiservice Delivery in Fog-enabled VANETs: Integrated Misbehavior Detection and Tolerance
Abstract:
Vehicular ad hoc networks (VANETs) in which vehicles act as the mobile nodes provide a wide variety of services, such as audio and video surveillance. However, such networks suffer from an important problem of service delivery reliability as the network performance degrades significantly in the presence of misbehaving vehicles. Most of the existing works either assume that vehiclesβ misbehaviors are constant or ignore heterogeneous traffic for multiservice (a mix of video, voice and data traffic). In this paper, we investigate the problem of trust-based multiservice delivery via integrated misbehavior detection and tolerance for fault-aware VANETs. To model the effects of time-varying misbehaviors, modern fog computing could help analyzing and storing related data in VANETs while evaluating the dynamic trust weights based on attribute parameters of each vehicle. Then we incorporate these weights into our service delivery framework that integrates trustworthy vehicle selection for misbehavior detection and uses differential resource allocation to achieve misbehavior tolerance. We present a multi-path selection criterion based on the trust evaluation and design a trust-aware heterogeneous traffic allocation algorithm over multiple routing paths.
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