Wireless communication technologies have now greatly impact our daily lives. From indoor wireless LANs to outdoor cellular mobile networks, wireless technologies have benefited billions of users around the globe. The era of vehicular ad hoc networks (VANETs) is now evolving, gaining attention and momentum. Researchers and developers have built VANET simulation software to allow the study and evaluation of various media access, routing, and emergency warning protocols. VANET simulation is fundamentally different from MANETs (mobile ad hoc networks) simulation because in VANETs, vehicular environment imposes new issues and requirements, such as constrained road topology, multi-path fading and roadside obstacles, traffic flow models, trip models, varying vehicular speed and mobility, traffic lights, traffic congestion, drivers' behavior, etc. Currently, there are VANET mobility generators, network simulators, and VANET simulators. This paper presents a comprehensive study and comparisons of the various publicly available VANET simulation software and their components. In particular, we contrast their software characteristics, graphical user interface (GUI), popularity, ease of use, input requirements, output visualization capability, accuracy of simulation, etc. Finally, while each of the studied simulators provides a good simulation environment for VANETs, refinements and further contributions are needed before they can be widely used by the research community.

Detecting and controlling the diffusion of infectious diseases such as COVID-19 is crucial to managing epidemics. One common measure taken to contain or reduce diffusion is to detect infected individuals and trace their prior contacts so as to then selectively isolate any individuals likely to have been infected. These prior contacts can be traced using mobile devices such as smartphones or smartwatches, which can continuously collect the location and contacts of their owners by using their embedded localisation and communications technologies, such as GPS, Cellular networks, Wi-Fi, and Bluetooth. This paper evaluates the effectiveness of these technologies and determines the impact of contact tracing precision on the spread and control of infectious diseases. To this end, we have created an epidemic model that we used to evaluate the efficiency and cost (number of people quarantined) of the measures to be taken, depending on the smartphone contact tracing technologies used. Our results show that in order to be effective for the COVID-19 disease, the contact tracing technology must be precise, contacts must be traced quickly, and a significant percentage of the population must use the smartphone contact tracing application. These strict requirements make smartphone-based contact tracing rather ineffective at containing the spread of the infection during the first outbreak of the virus. However, considering a second wave, where a portion of the population will have gained immunity, or in combination with some other more lenient measures, smartphone-based contact tracing could be extremely useful.

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