A V2I and V2V Collaboration Framework to Support Emergency Communications in ABS-Aided Internet of Vehicles

He, Yixin; Wang, Dawei; Huang, Fanghui; Zhang, Ruonan; Gu, Xin; Pan, Jianping

doi:10.1109/tgcn.2023.3245098

Cited by 32 publications

(20 citation statements)

References 38 publications

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“…The simulations can be further divided into the following two categories: one with a set of fixed CPU requirement parameters and one where the simulated processing time is based on information contained by the CPMs. resp = d UL + t process + d DL (1) Sensors 2023, 23, x FOR PEER REVIEW 19 of 2 consequence, the processing time of the incoming CPMs, so the imagined edge-side C service's response time was modeled using the built-in method calculateProcessingTime assuming a fair sharing model for the resource distribution among applications. We defin the total response time shown below in the graphs and Table 3 as seen in Equation ( 1), i.e the UL delay for sending the CPM to the MEC host, the processing time of the CPM, an the DL delay of the response message.…”

Section: Simulation Scenarios Parameters and Initial Resultsmentioning

confidence: 99%

Implementation of MEC-Assisted Collective Perception in an Integrated Artery/Simu5G Simulation Framework

Kovács,

Bokor

2023

Sensors

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Advanced vehicle-to-everything (V2X) safety applications must operate with ultra-low latency and be highly reliable. Therefore, they require sophisticated supporting technologies. This is especially true for cooperative applications, such as Collective Perception (CP), where a large amount of data constantly flows among vehicles and between vehicles and a network intelligence server. Both low and high-level support is needed for such an operation, meaning that various access technologies and other architectural elements also need to incorporate features enabling the effective use of V2X applications with strict requirements. The new 5G core architecture promises even more supporting technologies, like Multi-access Edge Computing (MEC). To test the performance of these technologies, an integrated framework for V2X simulations with 5G network elements is proposed in the form of combining Simu5G, a standalone 5G implementation, with the go-to V2X-simulator, Artery. As a first step toward a fully functional MEC-assisted CP Service, an extension to Simu5G’s edge implementation is introduced. The edge application is responsible for dispatching the Collective Perception Messages generated by the vehicles via the 5G connectivity so that a MEC server provided by the network can process incoming data. Simulation results prove the operability of the proposed integrated system and edge computing’s potential in assisting V2X scenarios.

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Section: Simulation Scenarios Parameters and Initial Resultsmentioning

confidence: 99%

Implementation of MEC-Assisted Collective Perception in an Integrated Artery/Simu5G Simulation Framework

Kovács,

Bokor

2023

Sensors

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“…Terrestrial robots equipped with GPS and other navigation systems can be used to collect data and provide situational awareness to emergency responders. Internet of Vehicles (IoV) can be employed to support emergency communication [92]. For example, in 2018, the Los Angeles Fire Department deployed a robotic vehicle to help fight a wildfire in California.…”

Section: Terrestrial Robotsmentioning

confidence: 99%

From Sensors to Safety: Internet of Emergency Services (IoES) for Emergency Response and Disaster Management

Damaševičius

Bačanin

Misra

2023

JSAN

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The advancement in technology has led to the integration of internet-connected devices and systems into emergency management and response, known as the Internet of Emergency Services (IoES). This integration has the potential to revolutionize the way in which emergency services are provided, by allowing for real-time data collection and analysis, and improving coordination among various agencies involved in emergency response. This paper aims to explore the use of IoES in emergency response and disaster management, with an emphasis on the role of sensors and IoT devices in providing real-time information to emergency responders. We will also examine the challenges and opportunities associated with the implementation of IoES, and discuss the potential impact of this technology on public safety and crisis management. The integration of IoES into emergency management holds great promise for improving the speed and efficiency of emergency response, as well as enhancing the overall safety and well-being of citizens in emergency situations. However, it is important to understand the possible limitations and potential risks associated with this technology, in order to ensure its effective and responsible use. This paper aims to provide a comprehensive understanding of the Internet of Emergency Services and its implications for emergency response and disaster management.

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“…In [38], a survey on D2D Communication for 5 GB/6G Networks about concept, applications, challenges, and future directions have been discussed. In [39], the authors provide a V2I and V2V collaboration framework to support emergency communications in the ABS-aided internet of vehicles. Up to now, several works have been proposed to study the resource allocation for D2D communication in hybrid VLC/RF systems.…”

Section: Related Workmentioning

confidence: 99%

Joint Resource Allocation and Drones Relay Selection for Large-Scale D2D Communication Underlaying Hybrid VLC/RF IoT Systems

Liu,

Huang,

Zhang

et al. 2023

Drones

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Relay-aided Device-to-Device (D2D) communication combining visible light communication (VLC) with radio frequency (RF) is a promising paradigm in the internet of things (IoT). Static relay limits the flexibility and maintaining connectivity of relays in Hybrid VLC/RF IoT systems. By using a drone as a relay station, it is possible to avoid obstacles such as buildings and to communicate in a line-of-sight (LoS) environment, which naturally aligns with the requirement of VLC Systems. To further support the application of VLC in the IoT, subject to the challenges imposed by the constrained coverage, the lack of flexibility, poor reliability, and connectivity, drone relay-aided D2D communication appears on the horizon and can be cost-effectively deployed for the large-scale IoT. This paper proposes a joint resource allocation and drones relay selection scheme, aiming to maximize the D2D system sum rate while ensuring the quality of service (QoS) requirements for cellular users (CUs) and D2D users (DUs). First, we construct a two-phase coalitional game to tackle the resource allocation problem, which exploits the combination of VLC and RF, as well as incorporates a greedy strategy. After that, a distributed cooperative multi-agent reinforcement learning (MARL) algorithm, called WoLF policy hill-climbing (WoLF-PHC), is proposed to address the drones relay selection problem. Moreover, to further reduce the computational complexity, we propose a lightweight neighbor–agent-based WoLF-PHC algorithm, which only utilizes historical information of neighboring DUs. Finally, we provide an in-depth theoretical analysis of the proposed schemes in terms of complexity and signaling overhead. Simulation results illustrate that the proposed schemes can effectively improve the system performance in terms of the sum rate and outage probability with respect to other outstanding algorithms.

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A V2I and V2V Collaboration Framework to Support Emergency Communications in ABS-Aided Internet of Vehicles

Cited by 32 publications

References 38 publications

Implementation of MEC-Assisted Collective Perception in an Integrated Artery/Simu5G Simulation Framework

Implementation of MEC-Assisted Collective Perception in an Integrated Artery/Simu5G Simulation Framework

From Sensors to Safety: Internet of Emergency Services (IoES) for Emergency Response and Disaster Management

Joint Resource Allocation and Drones Relay Selection for Large-Scale D2D Communication Underlaying Hybrid VLC/RF IoT Systems

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