IEEE Access (Jan 2019)
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 vehicles' 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 to analyze and to store 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. Finally, our scheme is evaluated using extensive simulations where we show that (i) approximately 12% - 40% higher successful service delivery can be achieved by our routing algorithm at the expense of acceptable delay loss compared to other three routing protocols; (ii) our trust-aware traffic allocation algorithm can gain 10% - 20% higher effective network utility and better fairness than that of the baseline solution; and (iii) the integrated scheme significantly improves both effective utility ratio and the path-usage proportion by comparing it with only routing scheme and only traffic allocation scheme.
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