A huge amount of data, generated by Internet of Things (IoT), is growing up exponentially based on nonstop operational states. Those IoT devices are generating an avalanche of information that is disruptive for predictable data processing and analytics functionality, which is perfectly handled by the cloud before explosion growth of IoT. Fog computing structure confronts those disruptions, with powerful complement functionality of cloud framework, based on deployment of micro clouds (fog nodes) at proximity edge of data sources. Particularly big IoT data analytics by fog computing structure is on emerging phase and requires extensive research to produce more proficient knowledge and smart decisions. This survey summarizes the fog challenges and opportunities in the context of big IoT data analytics on fog networking. In addition, it emphasizes that the key characteristics in some proposed research works make the fog computing a suitable platform for new proliferating IoT devices, services, and applications. Most significant fog applications (e.g., health care monitoring, smart cities, connected vehicles, and smart grid) will be discussed here to create a well-organized green computing paradigm to support the next generation of IoT applications.

A new integration of wireless communication technologies into the automobile industry has instigated a momentous research interest in the field of Vehicular Ad Hoc Network (VANET) security. Intelligent Transportation Systems (ITS) are set up, aiming to offer promising applications for efficient and safe communication for future automotive technology. Vehicular networks are unique in terms of characteristics, challenges, architecture, and applications. Consequently, security requirements related to vehicular networks are more complex as compared to mobile networks and conventional wireless networks. This article presents a survey about developments in vehicular networks from the perspective of lightweight cryptographic protocols and privacy preserving algorithms. Unique characteristics of vehicular networks are presented which make the embedded security applications computationally hard as well as memory constrained. The current study also deals with the fundamental security requirements, essential for vehicular communication. Furthermore, awareness of security threats and their cryptographic solutions in terms of future automotive industry are discussed. In addition, asymmetric, symmetric, and lightweight cryptographic solutions are summarized. These strategies can be enhanced or incorporated all in all to meet the security perquisites of future cars security.

Topic-level social influence analysis has been playing an important role in the online social networks like microblogs. Previous works usually use the cumulative number of links, such as the number of followers, to measure users' topic-level influence in a static network. However, they ignore the dynamics of influence and the methods they proposed can not be applied to social streams. To address the limitations of prior works, we firstly propose a novel topic-level influence over time (TIT) model integrating the text, links and time to analyze the topic-level temporal influence of each user. We then design an influence decay based approach to measure users' topic-level influence from the learned temporal influence. In order to track the influencers in data streams, we combine TIT and the influence decay method into a united online model (named oTIT), which is applicable to dynamic scenario. Through extensive experiments, we demonstrate the superiority of our approach, compared with the baseline and the state-of-the-art method. Moreover, we discover influence exhibits significantly different variation patterns over different topics, which verifies our viewpoint and gives us a new angle to understand its dynamic nature.

The Vehicular Ad Hoc Network (VANET) plays a vital role in the development of smart cities, especially in ensuring vehicles' safety on roads. However, VANET wireless-based networks face some challenges such as security, stability, communication, and reliability. To resolve these issues, we propose a fuzzy cluster head selection scheme in Cognitive Radio (CR) VANET, which uses the CR technology for the spectrum sensing algorithm. In this technology, the free spectrums of the primary user are utilized by secondary users without any correlation. Moreover, we have considered some input parameters such as vehicles' average velocity, distance, network connectivity level, lane weight and trustworthiness for the fuzzy system based CR VANET in this research. The selected cluster head provides stability and reliability to the cluster compared to the state of art techniques. Extensive experiments were conducted in order to evaluate the effectiveness of the proposed approach. However, simulation results authenticate more stable and secure cluster formation using the proposed fuzzy logic based CR VANET.