Internet of Vehicles and Real-Time Optimization Algorithms: Concepts for Vehicle Networking in Smart Cities

Achieving sustainable freight transport and citizens’ mobility operations in modern cities are becoming critical issues for many governments. By analyzing big data streams generated through IoT devices, city planners now have the possibility to optimize traffic and mobility patterns. IoT combined with innovative transport concepts as well as emerging mobility modes (e.g., ridesharing and carsharing) constitute a new paradigm in sustainable and optimized traffic operations in smart cities. Still, these are highly dynamic scenarios, which are also subject to a high uncertainty degree. Hence, factors such as real-time optimization and re-optimization of routes, stochastic travel times, and evolving customers’ requirements and traffic status also have to be considered. This paper discusses the main challenges associated with Internet of Vehicles (IoV) and vehicle networking scenarios, identifies the underlying optimization problems that need to be solved in real time, and proposes an approach to combine the use of IoV with parallelization approaches. To this aim, agile optimization and distributed machine learning are envisaged as the best candidate algorithms to develop efficient transport and mobility systems

A comprehensive survey on cooperative intersection management for heterogeneous connected vehicles

Nowadays, with the advancement of technology, world is trending toward high mobility and dynamics. In this context, intersection management (IM) as one of the most crucial elements of the transportation sector demands high attention. Today, road entities including infrastructures, vulnerable road users (VRUs) such as motorcycles, moped, scooters, pedestrians, bicycles, and other types of vehicles such as trucks, buses, cars, emergency vehicles, and railway vehicles like trains or trams are able to communicate cooperatively using vehicle-to-everything (V2X) communications and provide traffic safety, efficiency, infotainment and ecological improvements. In this paper, we take into account different types of intersections in terms of signalized, semi-autonomous (hybrid) and autonomous intersections and conduct a comprehensive survey on various intersection management methods for heterogeneous connected vehicles (CVs). We consider heterogeneous classes of vehicles such as road and rail vehicles as well as VRUs including bicycles, scooters and motorcycles. All kinds of intersection goals, modeling, coordination architectures, scheduling policies are thoroughly discussed. Signalized and semi-autonomous intersections are assessed with respect to these parameters. We especially focus on autonomous intersection management (AIM) and categorize this section based on four major goals involving safety, efficiency, infotainment and environment. Each intersection goal provides an in-depth investigation on the corresponding literature from the aforementioned perspectives. Moreover, robustness and resiliency of IM are explored from diverse points of view encompassing sensors, information management and sharing, planning universal scheme, heterogeneous collaboration, vehicle classification, quality measurement, external factors, intersection types, localization faults, communication anomalies and channel optimization, synchronization, vehicle dynamics and model mismatch, model uncertainties, recovery, security and privacy

Foggy clouds and cloudy fogs: a real need for coordinated management of fog-to-cloud computing systems

The recent advances in cloud services technology are fueling a plethora of information technology innovation, including networking, storage, and computing. Today, various flavors have evolved of IoT, cloud computing, and so-called fog computing, a concept referring to capabilities of edge devices and users' clients to compute, store, and exchange data among each other and with the cloud. Although the rapid pace of this evolution was not easily foreseeable, today each piece of it facilitates and enables the deployment of what we commonly refer to as a smart scenario, including smart cities, smart transportation, and smart homes. As most current cloud, fog, and network services run simultaneously in each scenario, we observe that we are at the dawn of what may be the next big step in the cloud computing and networking evolution, whereby services might be executed at the network edge, both in parallel and in a coordinated fashion, as well as supported by the unstoppable technology evolution. As edge devices become richer in functionality and smarter, embedding capacities such as storage or processing, as well as new functionalities, such as decision making, data collection, forwarding, and sharing, a real need is emerging for coordinated management of fog-to-cloud (F2C) computing systems. This article introduces a layered F2C architecture, its benefits and strengths, as well as the arising open and research challenges, making the case for the real need for their coordinated management. Our architecture, the illustrative use case presented, and a comparative performance analysis, albeit conceptual, all clearly show the way forward toward a new IoT scenario with a set of existing and unforeseen services provided on highly distributed and dynamic compute, storage, and networking resources, bringing together heterogeneous and commodity edge devices, emerging fogs, as well as conventional clouds.Peer ReviewedPostprint (author's final draft

Analyzing the Effect of Deceiving Agents in a System of Self-Driving Cars at an intersection - a computational model

The creation of protocols for autonomous intersection management is an active research topic with the potential of increasing the capacity of intersections addressing the increasing demand on roads. Most of the proposed protocols assume that all the vehicles involved will behave pro-socially, that is, in a way that improves the outcome of the system over their individual gain. We simulated three different autonomous intersection protocols, two centralized and one decentralized, introducing some egoistic agents that we call deceiving vehicles. Deceiving vehicles may decide to transmit false information while using a protocol if they detect that doing so can result in a lower delay in the intersection. Our simulations show that in two of the protocols, it is possible for a deceiving vehicle to experience lower delay times compared to its non-deceiving counterparts. Additionally, as more deceiving vehicles enter the system the overall capacity of an intersection can be reduced, increasing delays for non-deceiving vehicles which creates an incentive for more vehicles to deceive. We pose that, given that vehicles have an incentive to deceive, autonomous intersection protocol's authors need to consider deceiving vehicles in their design and include measures to prevent them, thus avoiding the performance degradation they produce.La creación de protocolos de manejo autónomo de intersecciones es un tema de investigación activo que tiene el potencial de aumentar la capacidad de las intersecciones aportando a la solución del problema del creciente aumento en la demanda en las vías. La mayoría de los protocolos propuestos asumen que todos los vehículos se comportan de manera prosocial, es decir, que actúan de una manera que beneficia al sistema sobre su propio beneficio. Nosotros simulamos tres protocolos de intersección autónomos, dos centralizados y uno descentralizado, introduciendo algunos agentes egoístas que llamamos vehículos engañosos. Los vehículos engañosos pueden decidir transmitir información falsa cuando usan un protocolo si detectan que hacerlo puede resultar una demora menor en la intersección. Nuestras simulaciones muestran que, en dos de los protocolos, es posible que los vehículos engañosos experimenten demoras menores frente a sus contrapartes no-engañosos. Asimismo, conforme más vehículos engañosos son introducidos en el sistema, la capacidad total de la intersección se ve reducida, aumentando las demoras para los vehículos que no son engañosos lo que genera un incentivo para que más vehículos sean engañosos. Proponemos que, dado que los vehículos tienen incentivos para engañar, los autores de protocolos de intersecciones autónomas deben considerar los vehículos engañosos en su diseño e incluir medida para prevenirlos, evitando así la degradación en rendimiento que producen.MaestríaSistemas Inteligente

Hybrid Hierarchical Approach For Addressing Service Discovery Issues In MANETS.

Management of Mobile Ad-hoc Net works (MANETs) is very difficult, because the movement of nodes is unpredictable, frequently changing the topology of the network Consequently, Service Discovery (SD) in the network a perquisite for efficient usage of network resources, is a complex problem

Lessons Learned from a Decade of Sudden Oak Death in California: Evaluating Local Management

Sudden Oak Death has been impacting California’s coastal forests for more than a decade. In that time, and in the absence of a centrally organized and coordinated set of mandatory management actions for this disease in California’s wildlands and open spaces, many local communities have initiated their own management programs. We present five case studies to explore how local-level management has attempted to control this disease. From these case studies, we glean three lessons: connections count, scale matters, and building capacity is crucial. These lessons may help management, research, and education planning for future pest and disease outbreaks

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

Effective Handover Technique in Cluster Based MANET Using Cooperative Communication

Mobile ad hoc networks (MANETs) are becoming increasingly common now a days and typical network loads considered for MANETs are increasing as applications evolve. This increases the importance of bandwidth efficiency and requirements on energy consumption delay and jitter. Coordinated channel access protocols have been shown to be well suited for MANETs under uniform load distributions. However, these protocols are not well suited for non-uniform load distributions as uncoordinated channel access protocols due to the lack of on-demand dynamic channel allocation mechanisms that exist in infrastructure based coordinated protocols. We have considered a lightweight dynamic channel allocation algorithm and a cooperative load balancing strategy that are helpful for the cluster based MANETs and an effective handover technique to improve the increased packet transmission mechanism. This helps in reduce jitter, packet delay and packet transfer speed, we use a novel handover algorithm to address this problem We present protocols that utilize these mechanisms to improve performance in terms of throughput, energy consumption and inter-packet delay variation (IPDV)