Since the beginning of the COVID-19 pandemic, instructors and students worldwide have been faced with the challenges of shifting from face-to-face to remote education. Due to universities short notice closure, synchronous online instruction through videoconferencing platforms has been the favoured choice for most instructors. In this paper, we report on our experience teaching an online course using Zoom videoconferencing platform. We conduct a two-fold analysis of online synchronous teaching: 1) We first compare the engagement and feedback features offered by Zoom with traditional classroom interactions. We show that some features are challenging to transpose to traditional face-to-face classroom setting while others may require additional hardware and software. 2) We analyze Zoom's attention tracker tool and evaluate the effectiveness of the attentiveness score as an effective grading metric. Our results show no apparent relationship between the students' attention as measured by Zoom and their performance. We also show that the use of recordings increases while attention decline during live classes.

With over 300 billion vehicle trips made in the United States and 64 billion in France per year, network operators have the opportunity to utilize the existing road and highway network as an alternative data network to offload large amounts of delay-tolerant traffic. To enable the road network as a large-capacity transmission system, we exploit the existing mobility of vehicles equipped with wireless and storage capacities together with a collection of offloading spots. An offloading spot is a data storage equipment located where vehicles usually park. Data is transloaded from a conventional data network to the closest offloading spot and then shipped by vehicles along their line of travel. The subsequent offloading spots act as data relay boxes where vehicles can drop off data for later pick-up by other vehicles, depending on their direction of travel. The main challenges of this offloading system are how to compute the road path matching the performance requirements of a data transfer and how to configure the sequence of offloading spots involved in the transfer. We propose a scalable and adaptive centralized architecture built on software-defined networking that maximizes the utilization of the flow of vehicles connecting consecutive offloading spots. We simulate the performance of our system using real roads traffic counts for France. Results show that the centralized controlled offloading architecture can achieve an efficient and fair allocation of concurrent data transfers between major cities in France.

Offloading is a promising technique for alleviating the ever-growing traffic load from infrastructure-based networks such as the Internet. Offloading consists of using alternative methods of transmission as a cost-effective solution for network operators to extend their transport capacity. In this paper, we advocate the use of conventional vehicles equipped with storage devices as data carriers whilst being driven for daily routine journeys. The road network can be turned into a large-capacity transmission system to offload bulk transfers of delay-tolerant data from the Internet. One of the challenges we address is assigning data to flows of vehicles while coping with the complexity of the road network. We propose an embedding algorithm that computes an offloading overlay where each logical link spans over multiple stretches of road from the underlying road infrastructure. We then formulate the data transfer assignment problem as a novel linear programming model we solve to determine the optimal logical paths matching the performance requirements of a data transfer. We evaluate our road traffic allocation scheme using actual road traffic counts in France. The numerical results show that 20% of vehicles in circulation in France equipped with only one Terabyte of storage can offload Petabyte transfers in a week.

We advocate the use of a data shuttle service model to offload bulk transfers of delay-tolerant data from the Internet onto standard vehicles equipped with data storage capabilities. We first propose an embedding algorithm that computes an offloading overlay on top of the road infrastructure. The goal is to simplify the representation of the road infrastructure as raw maps are too complex to handle. In this overlay, each logical link maps multiple stretches of road from the underlying road infrastructure. We formulate then the data transfer assignment problem as a novel linear programming model that determines the most appropriate logical paths in the offloading overlay for a data transfer request. We evaluate our proposal using actual road traffic counts in France. Numerical results show that we can satisfy weekly aggregate requests in the petabyte range while achieving cumulative bandwidth above 10 Gbps with a market share of 20% and only one terabyte of storage per vehicle.

The future of Vehicular Ad-Hoc Networks (VANET) will rely mainly on the support of efficient information dissemination protocols, whether we talk about safety applications that warn the driver of an imminent collision, a simple update on traffic conditions, or road-side advertisements. One of the greatest challenges when designing such protocols is how to deliver packets efficiently in a highly mobile environments under intermittent connectivity. Surprisingly, this problem has been under-investigated in the literature. In this paper, we propose, design, and evaluate SERVUS1, a robust dissemination protocol that guarantees packet propagation with high delivery ratio and low overhead. SERVUS includes a new broadcast management mechanism that takes advantage of the inherent behavioral properties of the VANET environment. In particular, the proposed protocol can update isolated nodes (or clusters) with missing information while ensuring homogeneous information dispersal at low overhead. Through a number of analyses, we show that SERVUS is highly efficient with regard to the tradeoff between reliability and cost, and overcomes important issues like the broadcast storm problem and the topological temporal fragility.