Strategic integration of Wireless Sensor Networks (WSNs) and IoT (Internet of Things) into VANET infrastructure is crucial for ensuring vehicular safety, mobility management, and vehicular applications. The integration collects information on traffic and road conditions without relying on traditional internet connectivity. It also addresses applications such as early warnings in areas with limited coverage, safety and health emergency messages in highly congested zones, and air monitoring without depending on traditional TCP/IP internet connectivity. This article provides a comprehensive view of network technologies, data acquisition devices, clustering techniques, and energy-efficient routing protocols to optimize Vehicle-to-Everything (V2X) communications in VANETs. This study also addresses how to leverage the frequency channels of the 802.11p protocol and expands the possibilities for developing numerous applications dedicated to remote ambient, traffic and safety monitoring without compromising network performance. Moreover, the recent developments of clustering algorithms and energy-efficient schemes for these VANET applications are analyzed from a novel perspective.

In the last few years, we witnessed numerous episodes of terrorist attacks and menaces in public crowded places. The necessity of better surveillance in these places pushed the development of new automated solutions to spot and notify possible menaces as fast as possible. In this work, we propose a novel approach to create a decentralized architecture to manage patrolling drones and cameras exploiting lightweight protocols used in the internet of things (IoT) domain. Through the adoption of the mist computing paradigm it is possible to give to all the object of the smart ecosystem a cognitive intelligence to speed up the recognition and analysis tasks. Distributing the intelligence among all the objects of the surveillance ecosystem allows a faster recognition and reaction to possible warning situations. The recognition of unusual objects in certain areas, e.g., airports, train stations and bus stations, has been made using computer vision algorithms. The adoption of the IoT protocols in a hierarchical architecture provides high scalability allowing an easy and painless join of other smart objects. Also a study on the soft real-time feasibility has been conducted and is herein presented.

Nowadays, interest in mobile communications is growing rapidly due to the high level of device development, which permits the achievement of good objectives in terms of quality of service (QoS) for user satisfaction during active data flows. The increasing mobile client populations use different mobile devices to access the wireless medium and many applications are being developed to satisfy eager client requirements. Independently on the considered architecture (WLAN, UMTS, LTE, etc.), mobility represents a great advantage for user comfort, but it needs to be managed in an adequate manner in order to avoid service disruptions or unacceptable degradation of the perceived quality. In this paper, the concept of cell-mobility prediction is considered and we show how the analysis of user behavior, in terms of mobility, can be exploited to enhance QoS levels in current communications among mobile hosts and base stations (coverage cells, in general). This paper surveys different unconventional approaches and protocols, showing how it is possible to consider in-advance bandwidth reservations to achieve service continuity, avoiding call droppings during active sessions. First, we present the importance of in-advance reserving in wireless cellular networks, then we discuss the existing protocols and approaches for determining the most suitable future cells.

In wireless networking, the main desire of end-users is to take advantage of satisfactory services, in terms of QoS, especially when they pay for a required need. Many efforts have been made to investigate how the continuity of services can be guaranteed in QoS networks, where users can move from one cell to another one. The introduction of a prediction scheme with passive reservations is the only way to face this issue; however, the deployment of in-advance bandwidth leads the system to waste resources. This work consists of two main integrated contributions: a new pattern prediction scheme based on a distributed set of Markov chains, in order to handle passive reservations, and a statistical bandwidth management algorithm for the reduction of bandwidth wastage. The result of the integration is the Distributed Prediction with Bandwidth Management Algorithm (DPBMA) that is independent from the considered technology and the vehicular environment. Several simulation campaigns were conducted in order to evaluate the effectiveness of the proposed idea. It was also compared with other prediction schemes, in terms of system utilization, accuracy, call dropping, and call blocking probabilities.

As demands on the network continue to grow, it is increasingly important to upgrade the existing infrastructure in order to offer higher bandwidth and service level guarantees to users. Next generation networks (NGNs) represent a fully IP-based architecture that is able to support different technologies. In this context, the satellite networks are considered a fundamental part for future hybrid architectures. In this scenario, knowing satellite channel propagation characteristics in order to be able to design a communication system to respond to new user needs is of fundamental importance. Many papers in the literature show channel models in different satellite scenarios both for fixed and mobile applications; however, to the best of our knowledge, nobody presents an overview on different satellite models based on Markov chains. This paper wants to present a comprehensive review of the most recent developments in satellite channel communications related to mobile services and, in particular, for the land mobile satellite systems. The work presents all different types of Markov models, from single-state to multi-state models, that have been proposed in the literature from the early 1980s.

In this paper, a quality-of-service (QoS) multicast routing protocol, i.e., the core-based tree based on heuristic genetic algorithms (GAs), has been implemented and applied over a high-altitude platform (HAP)-satellite platform. The proposed multicast routing algorithm is called the constrained cost-bandwidth-delay GA (CCBD-GA). To achieve a better optimization of the multicast tree cost, a new algorithm called HULK-GA, which is based on the GA and on a proposed broadcast metric, has been developed. Finally, an algorithm called hybrid cost-bandwidth-delay GA has been proposed, taking into account both CCDB-GA and HULK-GA characteristics to obtain an overall algorithm that can consider QoS routing constraints and minimize the overall cost per link of the considered multicast tree. The joint bandwidth-delay metrics can be very useful in hybrid platforms such as the platform considered, because it is possible to take advantage of the single characteristics of the satellite and HAP segments. The HAP segment offers low propagation delay, permitting QoS constraints based on maximum end-to-end delay to be met. The satellite segment, instead, offers a larger footprint but higher propagation delay. The joint bandwidth-delay metric permits the traffic load to be balanced, respecting both QoS constraints.