Cloud Computing in VANETs: Architecture, Taxonomy, and Challenges

Cloud Computing in VANETs (CC-V) has been investigated into two major themes of research including Vehicular Cloud Computing (VCC) and Vehicle using Cloud (VuC). VCC is the realization of autonomous cloud among vehicles to share their abundant resources. VuC is the efficient usage of conventional cloud by on-road vehicles via a reliable Internet connection. Recently, number of advancements have been made to address the issues and challenges in VCC and VuC. This paper qualitatively reviews CC-V with the emphasis on layered architecture, network component, taxonomy, and future challenges. Specifically, a four-layered architecture for CC-V is proposed including perception, co-ordination, artificial intelligence and smart application layers. Three network component of CC-V namely, vehicle, connection and computation are explored with their cooperative roles. A taxonomy for CC-V is presented considering major themes of research in the area including design of architecture, data dissemination, security, and applications. Related literature on each theme are critically investigated with comparative assessment of recent advances. Finally, some open research challenges are identified as future issues. The challenges are the outcome of the critical and qualitative assessment of literature on CC-V

CONGESTION CONTROL FOR A ULTRA-WIDEBAND DYNAMIC SENSOR NETWORK USING AUTONOMIC BASED LEARNING

The physical conditions of the area of interest is being collected at the central location using a set of dedicated sensors that forms a network is referred to as Wireless Sensor Network. A dynamic environment is required for a secure multi-hop communication between nodes of the heterogeneous Wireless Sensor Network. One such solution is to employ autonomic based learning in a MAC Layer of the UWB TxRx. Over a time period the autonomic based network learns from the previous experience and adapts to the environment significantly. Exploring the Autonomicity would help us in evading the congestion of about 30% in a typical UWB-WSNs. Simulation results showed an improvement of 5% using Local Automate Collision Avoidance Scheme (LACAS-UWB) compared to LACAS

Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks

This book presents collective works published in the recent Special Issue (SI) entitled "Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks”. These works expose the readership to the latest solutions and techniques for MANETs and VANETs. They cover interesting topics such as power-aware optimization solutions for MANETs, data dissemination in VANETs, adaptive multi-hop broadcast schemes for VANETs, multi-metric routing protocols for VANETs, and incentive mechanisms to encourage the distribution of information in VANETs. The book demonstrates pioneering work in these fields, investigates novel solutions and methods, and discusses future trends in these field

Game Theory for Multi-Access Edge Computing:Survey, Use Cases, and Future Trends

Game theory (GT) has been used with significant success to formulate, and either design or optimize, the operation of many representative communications and networking scenarios. The games in these scenarios involve, as usual, diverse players with conflicting goals. This paper primarily surveys the literature that has applied theoretical games to wireless networks, emphasizing use cases of upcoming multiaccess edge computing (MEC). MEC is relatively new and offers cloud services at the network periphery, aiming to reduce service latency backhaul load, and enhance relevant operational aspects such as quality of experience or security. Our presentation of GT is focused on the major challenges imposed by MEC services over the wireless resources. The survey is divided into classical and evolutionary games. Then, our discussion proceeds to more specific aspects which have a considerable impact on the game's usefulness, namely, rational versus evolving strategies, cooperation among players, available game information, the way the game is played (single turn, repeated), the game's model evaluation, and how the model results can be applied for both optimizing resource-constrained resources and balancing diverse tradeoffs in real edge networking scenarios. Finally, we reflect on lessons learned, highlighting future trends and research directions for applying theoretical model games in upcoming MEC services, considering both network design issues and usage scenarios

A Systematic Literature Review on Blockchain Enabled Federated Learning Framework for Internet of Vehicles

While the convergence of Artificial Intelligence (AI) techniques with improved information technology systems ensured enormous benefits to the Internet of Vehicles (IoVs) systems, it also introduced an increased amount of security and privacy threats. To ensure the security of IoVs data, privacy preservation methodologies have gained significant attention in the literature. However, these strategies also need specific adjustments and modifications to cope with the advances in IoVs design. In the interim, Federated Learning (FL) has been proven as an emerging idea to protect IoVs data privacy and security. On the other hand, Blockchain technology is showing prominent possibilities with secured, dispersed, and auditable data recording and sharing schemes. In this paper, we present a comprehensive survey on the application and implementation of Blockchain-Enabled Federated Learning frameworks for IoVs. Besides, probable issues, challenges, solutions, and future research directions for BC-Enabled FL frameworks for IoVs are also presented. This survey can further be used as the basis for developing modern BC-Enabled FL solutions to resolve different data privacy issues and scenarios of IoVs

A Survey and Future Directions on Clustering: From WSNs to IoT and Modern Networking Paradigms

Many Internet of Things (IoT) networks are created as an overlay over traditional ad-hoc networks such as Zigbee. Moreover, IoT networks can resemble ad-hoc networks over networks that support device-to-device (D2D) communication, e.g., D2D-enabled cellular networks and WiFi-Direct. In these ad-hoc types of IoT networks, efficient topology management is a crucial requirement, and in particular in massive scale deployments. Traditionally, clustering has been recognized as a common approach for topology management in ad-hoc networks, e.g., in Wireless Sensor Networks (WSNs). Topology management in WSNs and ad-hoc IoT networks has many design commonalities as both need to transfer data to the destination hop by hop. Thus, WSN clustering techniques can presumably be applied for topology management in ad-hoc IoT networks. This requires a comprehensive study on WSN clustering techniques and investigating their applicability to ad-hoc IoT networks. In this article, we conduct a survey of this field based on the objectives for clustering, such as reducing energy consumption and load balancing, as well as the network properties relevant for efficient clustering in IoT, such as network heterogeneity and mobility. Beyond that, we investigate the advantages and challenges of clustering when IoT is integrated with modern computing and communication technologies such as Blockchain, Fog/Edge computing, and 5G. This survey provides useful insights into research on IoT clustering, allows broader understanding of its design challenges for IoT networks, and sheds light on its future applications in modern technologies integrated with IoT.acceptedVersio

Game Theory Based Privacy Protection for Context-Aware Services

In the era of context-aware services, users are enjoying remarkable services based on data collected from a multitude of users. To receive services, they are at risk of leaking private information from adversaries possibly eavesdropping on the data and/or the un--trusted service platform selling off its data. Malicious adversaries may use leaked information to violate users\u27 privacy in unpredictable ways. To protect users\u27 privacy, many algorithms are proposed to protect users\u27 sensitive information by adding noise, thus causing context-aware service quality loss. Game theory has been utilized as a powerful tool to balance the tradeoff between privacy protection level and service quality. However, most of the existing schemes fail to depict the mutual relationship between any two parties involved: user, platform, and adversary. There is also an oversight to formulate the interaction occurring between multiple users, as well as the interaction between any two attributes. To solve these issues, this dissertation firstly proposes a three-party game framework to formulate the mutual interaction between three parties and study the optimal privacy protection level for context-aware services, thus optimize the service quality. Next, this dissertation extends the framework to a multi-user scenario and proposes a two-layer three-party game framework. This makes the proposed framework more realistic by further exploring the interaction, not only between different parties, but also between users. Finally, we focus on analyzing the impact of long-term time-serial data and the active actions of the platform and adversary. To achieve this objective, we design a three-party Stackelberg game model to help the user to decide whether to update information and the granularity of updated information

Enabling Cyber-Physical Communication in 5G Cellular Networks: Challenges, Solutions and Applications

Cyber-physical systems (CPS) are expected to revolutionize the world through a myriad of applications in health-care, disaster event applications, environmental management, vehicular networks, industrial automation, and so on. The continuous explosive increase in wireless data traffic, driven by the global rise of smartphones, tablets, video streaming, and online social networking applications along with the anticipated wide massive sensors deployments, will create a set of challenges to network providers, especially that future fifth generation (5G) cellular networks will help facilitate the enabling of CPS communications over current network infrastructure. In this dissertation, we first provide an overview of CPS taxonomy along with its challenges from energy efficiency, security, and reliability. Then we present different tractable analytical solutions through different 5G technologies, such as device-to-device (D2D) communications, cell shrinking and offloading, in order to enable CPS traffic over cellular networks. These technologies also provide CPS with several benefits such as ubiquitous coverage, global connectivity, reliability and security. By tuning specific network parameters, the proposed solutions allow the achievement of balance and fairness in spectral efficiency and minimum achievable throughout among cellular users and CPS devices. To conclude, we present a CPS mobile-health application as a case study where security of the medical health cyber-physical space is discussed in details