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Connected vehicular cloud computing (CVCC) and the VANET can realize real-time monitoring and intelligent adjustment of traffic conditions. With the data collected by vehicles and the guidance provided by cloud computing platforms, the current traffic is facing new opportunities. CVCC is a mobile computing model, which extends the fixed nodes of traditional cloud infrastructure into mobile nodes composed of vehicles. Thus, compared to the traditional cloud infrastructures, CVCC requires a more complex mechanism to ensure the secure and efficient information transmission in both cloud platform-to-vehicle communication and vehicle-to-vehicle communication. Channel capacity, as the key parameter to measure the channel utilization, plays an important role in ensuring the reliability of CVCC service and the integrity of transmission data. In recent decades, the existing calculation methods could not solve the channel capacities problem in multi-participant VANETs. Different from the traditional calculation methods, we propose a novel calculation method in this article, which combines the core concepts of game theory and information theory, to calculate the channel capacities of multiple vehicular networks. The proposed method refreshes the concept of communication, which has potential applications in different services of CVCC. [ABSTRACT FROM AUTHOR]

Online social networks (OSNs) suffer from forged messages. Current studies have typically been focused on the detection of forged messages and do not provide the analysis of the behaviors of message publishers and network strategies to suppress forged messages. This paper carries out the analysis by taking a game theoretic approach, where infinitely repeated games are constructed to capture the interactions between a publisher and a network administrator and suppress forged messages in OSNs. Critical conditions, under which the publisher is disincentivized to publish any forged messages, are identified in the absence and presence of misclassification on genuine messages. Closed-form expressions are established for the maximum number of forged messages that a malicious publisher could publish. Confirmed by the numerical results, the proposed infinitely repeated games reveal that forged messages can be suppressed by improving the payoffs for genuine messages, increasing the cost of bots, and/or reducing the payoffs for forged messages. The increasing detection probability of forged messages or decreasing misclassification probability of genuine messages also has a strong impact on the suppression of forged messages. [ABSTRACT FROM AUTHOR]