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Now a days Vehicular Ad hoc Network is an emerging technology. Mobility management is one of the most challenging research issues for Vehicular Ad hoc Network to support variety of intelligent transportation system applications. Vehicular…
Modeling multivariate time series has long been a subject that has attracted researchers from a diverse range of fields including economics, finance, and traffic. A basic assumption behind multivariate time series forecasting is that its…
Vehicular Ad Hoc Networks (VANETs) play a crucial role in Intelligent Transportation Systems (ITS) by facilitating communication between vehicles and infrastructure. This communication aims to enhance road safety, improve traffic…
Automated equipment health monitoring from streaming multisensor time-series data can be used to enable condition-based maintenance, avoid sudden catastrophic failures, and ensure high operational availability. We note that most complex…
The ever increasing adoption of mobile technologies and ubiquitous services allows to sense human behavior at unprecedented levels of details and scale. Wearable sensors are opening up a new window on human mobility and proximity at the…
Modern vehicles have multiple electronic control units (ECUs) that are connected together as part of a complex distributed cyber-physical system (CPS). The ever-increasing communication between ECUs and external electronic systems has made…
Networks are widely used to model real-world systems and uncover their topological features. Network properties such as the degree distribution and shortest path length have been computed in numerous real-world networks, and most of them…
Today, with the development of intercity and metropolitan roadways and with various cars moving in various directions, there is a greater need than ever for a network to coordinate commutes. Nowadays, people spend a lot of time in their…
Vehicular adhoc network or VANET is special types of adhoc network consists of moving cars referred to as nodes; provide a way to exchange any information between cars without depending on fixed infrastructure. For efficient communication…
Link prediction in unmanned aerial vehicle (UAV) ad hoc networks (UANETs) aims to predict the potential formation of future links between UAVs. In adversarial environments where the route information of UAVs is unavailable, predicting…
Vehicle Ad-hoc Networks (VANETs) act as the core of vehicular communications and provide the fundamental wireless communication architecture to support both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication.…
Now-a-days vehicles are one of the most important parts of our life. We need them to cross distances in our everyday life. In this paper we discuss Vehicular AdHoc Network (VANET) technology that can ensure the maintenance of traffic rules…
Deep graph clustering has recently received significant attention due to its ability to enhance the representation learning capabilities of models in unsupervised scenarios. Nevertheless, deep clustering for temporal graphs, which could…
In this paper, we focus on two-dimensional connectivity in sparse vehicular ad hoc networks (VANETs). In this respect, we find thresholds for the arrival rates of vehicles at entrances of a block of streets such that the connectivity is…
Predicting future locations of agents in the scene is an important problem in self-driving. In recent years, there has been a significant progress in representing the scene and the agents in it. The interactions of agents with the scene and…
In the last few years, the Vehicular Ad-hoc Network (VANET) has come to be an important area of research. Significant research has been conducted to improve the performance of VANETS. One output of further research conducted on VANET is the…
Graph neural networks (GNN) have shown significant capabilities in handling structured data, yet their application to dynamic, temporal data remains limited. This paper presents a new type of graph attention network, called TempoKGAT, which…
Intelligent Transportation Systems (ITSs) is the backbone of transportation services in smart cities. ITSs produce better-informed decisions using real-time data gathered from connected vehicles. In ITSs, Vehicular Ad hoc Network (VANET) is…
Inductive representation learning on temporal graphs is an important step toward salable machine learning on real-world dynamic networks. The evolving nature of temporal dynamic graphs requires handling new nodes as well as capturing…
Edge-enabled Vehicular Ad Hoc Network (VANET) introduces real-time services and storage, computation, and communication facilities to the vehicles through Roadside Units (RSUs). Nevertheless, RSUs are often easy targets for security…