Double talk : “Can Edge Computing fulfill the requirements of automated vehicular services using 5G network?” & “Can Vehicular Cloud Replace Edge Computing?”

Abstract 1: Communication and computation services support-
ing Connected and Automated Vehicles (CAVs) are characterized
by stringent requirements, in terms of response time and reliability.

Fulfilling these requirements is crucial for ensuring road
safety and traffic optimization. The conceptually simple solution
of hosting these services in the vehicles increases their cost
(mainly due to the installation and maintenance of computation
infrastructure) and may drain their battery excessively. Such
disadvantages can be tackled via Multi-Access Edge Computing
(MEC), consisting in deploying computation capability in network

nodes deployed close to the devices (vehicles in this case),
such as to satisfy the stringent CAV requirements.
However, it is not yet clear under which conditions MEC can
support CAV requirements and for which services. To shed light
on this question, we conduct a simulation campaign using well-
known open-source simulation tools, namely OMNeT++, Simu5G,
Veins, INET, and SUMO. We are thus able to provide a reality
check on MEC for CAV, pinpointing what are the computation
capacities that must be installed in the MEC, to support the
different services, and the amount of vehicles that a single MEC
node can support. We find that such parameters must vary a
lot, depending on the service considered. This study can serve
as a preliminary basis for network operators to plan future
deployment of MEC to support CAV.

Abstract 2: Edge computing (EC) consists of deploying com-
putation resources close to the users, thus enabling low-latency
applications, such as augmented reality and online gaming.
However, large-scale deployment of edge nodes can be highly
impractical and expensive. Besides EC, there is a rising concept
known as Vehicular Cloud Computing (VCC). VCC is a com-
puting paradigm that amplifies the capabilities of vehicles by
exploiting part of their computational resources, enabling them
to participate in services similar to those provided by the EC.
The advantage of VCC is that it can opportunistically exploit
part of the computation resources already present on vehicles,
thus relieving a network operator from the deployment and
maintenance cost of EC nodes. However, it is still unknown under
which circumstances VCC can enable low-latency applications
without EC. In this work, we show that VCC has the potential to
effectively supplant EC in urban areas, especially given the higher
density of vehicles in such environments. The goal of this paper
is to analyze, via simulation, the key parameters determining
the conditions under which this substitution of EC by VCC is
feasible. In addition, we provide a high level cost analysis to
show that VCC is much less costly for a network operator than
adopting EC.