Distributed Hybrid Simulation of the Internet of Things and Smart Territories

This paper deals with the use of hybrid simulation to build and compose heterogeneous simulation scenarios that can be proficiently exploited to model and represent the Internet of Things (IoT). Hybrid simulation is a methodology that combines multiple modalities of modeling/simulation. Complex scenarios are decomposed into simpler ones, each one being simulated through a specific simulation strategy. All these simulation building blocks are then synchronized and coordinated. This simulation methodology is an ideal one to represent IoT setups, which are usually very demanding, due to the heterogeneity of possible scenarios arising from the massive deployment of an enormous amount of sensors and devices. We present a use case concerned with the distributed simulation of smart territories, a novel view of decentralized geographical spaces that, thanks to the use of IoT, builds ICT services to manage resources in a way that is sustainable and not harmful to the environment. Three different simulation models are combined together, namely, an adaptive agent-based parallel and distributed simulator, an OMNeT++ based discrete event simulator and a script-language simulator based on MATLAB. Results from a performance analysis confirm the viability of using hybrid simulation to model complex IoT scenarios.Comment: arXiv admin note: substantial text overlap with arXiv:1605.0487

Modeling the Internet of Things: a simulation perspective

This paper deals with the problem of properly simulating the Internet of Things (IoT). Simulating an IoT allows evaluating strategies that can be employed to deploy smart services over different kinds of territories. However, the heterogeneity of scenarios seriously complicates this task. This imposes the use of sophisticated modeling and simulation techniques. We discuss novel approaches for the provision of scalable simulation scenarios, that enable the real-time execution of massively populated IoT environments. Attention is given to novel hybrid and multi-level simulation techniques that, when combined with agent-based, adaptive Parallel and Distributed Simulation (PADS) approaches, can provide means to perform highly detailed simulations on demand. To support this claim, we detail a use case concerned with the simulation of vehicular transportation systems.Comment: Proceedings of the IEEE 2017 International Conference on High Performance Computing and Simulation (HPCS 2017

Edge computing and iot analytics for agile optimization in intelligent transportation systems

[EN] With the emergence of fog and edge computing, new possibilities arise regarding the data-driven management of citizens' mobility in smart cities. Internet of Things (IoT) analytics refers to the use of these technologies, data, and analytical models to describe the current status of the city traffic, to predict its evolution over the coming hours, and to make decisions that increase the efficiency of the transportation system. It involves many challenges such as how to deal and manage real and huge amounts of data, and improving security, privacy, scalability, reliability, and quality of services in the cloud and vehicular network. In this paper, we review the state of the art of IoT in intelligent transportation systems (ITS), identify challenges posed by cloud, fog, and edge computing in ITS, and develop a methodology based on agile optimization algorithms for solving a dynamic ride-sharing problem (DRSP) in the context of edge/fog computing. These algorithms allow us to process, in real time, the data gathered from IoT systems in order to optimize automatic decisions in the city transportation system, including: optimizing the vehicle routing, recommending customized transportation modes to the citizens, generating efficient ride-sharing and car-sharing strategies, create optimal charging station for electric vehicles and different services within urban and interurban areas. A numerical example considering a DRSP is provided, in which the potential of employing edge/fog computing, open data, and agile algorithms is illustrated.This work was partially supported by the Spanish Ministry of Science (PID2019111100RB-C21/AEI/10.13039/501100011033, RED2018-102642-T), and the Erasmus+ program (2019I-ES01-KA103-062602).Peyman, M.; Copado, PJ.; Tordecilla, RD.; Do C. Martins, L.; Xhafa, F.; Juan-Pérez, ÁA. (2021). Edge computing and iot analytics for agile optimization in intelligent transportation systems. Energies. 14(19):1-26. https://doi.org/10.3390/en14196309126141

Using Distributed Ledger Technologies in VANETs to Achieve Trusted Intelligent Transportation Systems

With the recent advancements in the networking realm of computers as well as achieving real-time communication between devices over the Internet, IoT (Internet of Things) devices have been on the rise; collecting, sharing, and exchanging data with other connected devices or databases online, enabling all sorts of communications and operations without the need for human intervention, oversight, or control. This has caused more computer-based systems to get integrated into the physical world, inching us closer towards developing smart cities. The automotive industry, alongside other software developers and technology companies have been at the forefront of this advancement towards achieving smart cities. Currently, transportation networks need to be revamped to utilize the massive amounts of data being generated by the public’s vehicle’s on-board devices, as well as other integrated sensors on public transit systems, local roads, and highways. This will create an interconnected ecosystem that can be leveraged to improve traffic efficiency and reliability. Currently, Vehicular Ad-hoc Networks (VANETs) such as vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-grid (V2G) communications, all play a major role in supporting road safety, traffic efficiency, and energy savings. To protect these devices and the networks they form from being targets of cyber-related attacks, this paper presents ideas on how to leverage distributed ledger technologies (DLT) to establish secure communication between vehicles that is decentralized, trustless, and immutable. Incorporating IOTA’s protocols, as well as utilizing Ethereum’s smart contracts functionality and application concepts with VANETs, all interoperating with Hyperledger’s Fabric framework, several novel ideas can be implemented to improve traffic safety and efficiency. Such a modular design also opens up the possibility to further investigate use cases of the blockchain and distributed ledger technologies in creating a decentralized intelligent transportation system (ITS)

Applications of Federated Learning in Smart Cities: Recent Advances, Taxonomy, and Open Challenges

Federated learning plays an important role in the process of smart cities. With the development of big data and artificial intelligence, there is a problem of data privacy protection in this process. Federated learning is capable of solving this problem. This paper starts with the current developments of federated learning and its applications in various fields. We conduct a comprehensive investigation. This paper summarize the latest research on the application of federated learning in various fields of smart cities. In-depth understanding of the current development of federated learning from the Internet of Things, transportation, communications, finance, medical and other fields. Before that, we introduce the background, definition and key technologies of federated learning. Further more, we review the key technologies and the latest results. Finally, we discuss the future applications and research directions of federated learning in smart cities

Emergency message dissemination schemes based on congestion avoidance in VANET and vehicular FoG computing

With the rapid growth in connected vehicles, FoG-assisted vehicular ad hoc network (VANET) is an emerging and novel field of research. For information sharing, a number of messages are exchanged in various applications, including traffic monitoring and area-specific live weather and social aspects monitoring. It is quite challenging where vehicles' speed, direction, and density of neighbors on the move are not consistent. In this scenario, congestion avoidance is also quite challenging to avoid communication loss during busy hours or in emergency cases. This paper presents emergency message dissemination schemes that are based on congestion avoidance scenario in VANET and vehicular FoG computing. In the similar vein, FoG-assisted VANET architecture is explored that can efficiently manage the message congestion scenarios. We present a taxonomy of schemes that address message congestion avoidance. Next, we have included a discussion about comparison of congestion avoidance schemes to highlight the strengths and weaknesses. We have also identified that FoG servers help to reduce the accessibility delays and congestion as compared to directly approaching cloud for all requests in linkage with big data repositories. For the dependable applicability of FoG in VANET, we have identified a number of open research challenges. © 2013 IEEE