Named Data Networking (NDN), as a specific architecture design of Information-Centric Networking (ICN), has quickly became a promising candidate for future Internet architecture, where communications are driven by data names instead of IP addresses. To realize the NDN architecture in the future Internet, a stateful forwarding plane has been proposed to maintain the pending Interest packets and guide Data packets back to the consumers. However, the operations of stateful forwarding plane are not fully explained in NDN project and the design specifics remain to be filled in. In addition, the overall framework of stateful forwarding plane should be adaptive and responsive to diverse network conditions by taking into account of multiple network metrics. In this paper, we propose a novel adaptive forwarding strategy, also referred to as fwdPRO, to realize intelligent and adaptive Interest packet forwarding in NDN. The basic idea of the fwdPRO is to employ Technique for Order Performance by Similarity to Idea Solution (TOPSIS) to dynamically evaluate outgoing interface alternatives based on multiple network metrics and objectively select an optimal outgoing interface to forward the Interest packet. The TOPSIS is a multi-criteria decision-making (MCDM) model to identify the best alternative that is nearest to the positive ideal solution and farthest from the negative ideal solution. We conduct extensive simulation experiments for performance evaluation and comparison with the existing BestRoute and EPF schemes. The simulation results show that the proposed adaptive forwarding strategy can improve the Interest satisfaction ratio and Interest satisfaction latency as well as reduce the average hop count.

Recent advancements in embedded sensing system, wireless communication technologies, big data, and artificial intelligence have fueled the development of Internet of Vehicles (IoV), where vehicles, road side unit (RSUs), and smart devices seamlessly interact with each other to enable the gathering and sharing of information on vehicles, roads, and their surrounds. As a fundamental component of IoV, vehicular networks (VANETs) are playing a critical role in processing, computing, and sharing travel-related information, which can help vehicles timely be aware of traffic situation and finally improve road safety and travel experience. However, due to the unique characteristics of vehicles, such as high mobility and sparse deployment making neighbor vehicles unacquainted and unknown to each other, VANETs are facing the challenge of evaluating the credibility of road safety messages. In this paper, we propose a blockchain-based trust management system using multi-criteria decision-making model, also referred to as TrustBlockMCDM, in VANETs. In the TrustBlockMCDM, each vehicle evaluates the credibility of received road safety message and generates the trust value of message originator. Due to the limited storage capacity, each vehicle periodically uploads the trust value to a nearby RSU. After receiving various trust values from vehicles, the RSU calculates the reputation value of message originator of road safety message using multi-criteria decision-making model, packs the reputation value into a block, and competes to add the block into blockchain. We evaluate the proposed TrustBlockMCDM approach through simulation experiments using OMNeT++ and compare its performance with prior blockchain-based decentralized trust management approach. The simulation results indicate that the proposed TrustBlockMCDM approach can not only improve fictitious message detection rate and malicious vehicle detection rate, but also can increase the number of dropped fictitious messages.