Data Dissemination for Vehicles in Temporary Cellular Network Dead Spots

Data Dissemination for Vehicles in Temporary Cellular Network Dead Spots

Ergys Puka, Peter Herrmann
Copyright: © 2019 |Pages: 18
DOI: 10.4018/IJCPS.2019070103
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The cellular network coverage in sparsely populated and mountainous areas is often patchy. That can be a significant impediment for services based on connections between vehicles and their environment. This article presents a method to reduce the waiting time occurring when a vehicle intends to send a message via a cellular network but is currently in a dead spot, i.e., an area without sufficient coverage. The authors introduce a data dissemination protocol that allows vehicles to connect through an ad-hoc network. The ad-hoc network peers can then find out which one will most likely leave the dead spot first. The selected vehicle stores then the messages of all connected vehicles and forwards them to the remote infrastructure as soon as it regains cellular network access. This research also discusses message flows in larger dead spots in which a vehicle may consecutively form several ad-hoc connections. Further, the authors describe an initial implementation of the protocol using the technology Wi-Fi Direct that is realized on most modern mobile phones.
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1. Introduction

In the automotive sector, networked applications connecting vehicles with each other and with the infrastructure have gotten popular. Such programs realize helpful services assisting drivers in various ways. For instance, by retrieving the current vehicle and road conditions, the transport safety can be improved. Furthermore, informing about the current traffic density leads to more efficient and environmentally beneficial driving (Papadimitratos, de La Fortelle, Evenssen, Brignolo, & Cosenza, 2009).

Vehicle-to-infrastructure (V2I) connections between moving vehicles and remote servers are predominantly realized using cellular networks (Siegel, Erb, & Sarma, 2017). Thus, applications based on V2I rely on a continuous cellular network coverage which, however, is not always given in practice. This applies particularly to rural and sparsely inhabited areas and minor roads since the cell tower infrastructure is mostly oriented on the number of people sojourning in an area (Mecklenbräuker et al., 2011), (Puka, Herrmann, Levin, & Skjetne, 2018). Also, mountainous terrain can lead to temporary inaccessibility since the presence of hills tends to cause echoes of signals deteriorating the radio reception (Driesen, 2000). On the other hand, long distance travelling through sparsely populated and often mountainous areas profits most from many of the automotive applications (e.g., breakdown support, warning system about icy conditions or rocks on the roads). An extreme case is the Australian Outback where cellular network coverage can only be found around the relatively few settlements. For instance, on the 315 km long way between Uluru and Kings Canyon in the Northern Territories, that is quite popular with tourists, there is just the settlement Yulara with mobile network coverage as well as two parking lots provided with Wi-Fi access.

A straightforward way to guarantee connectivity in the absence of cellular network coverage is the usage of other networking technologies like satellite communication which, however, is quite expensive (Guerra, Ferreira, Costa, Nodar-López, & Agelet, 2018). Therefore, we suggest a novel data dissemination protocol that can reduce the delivery time of messages sent from vehicles in a dead spot to the external infrastructure. In this way, reports about break downs as well as important sensor data indicating the road condition can be sped up. Our protocol capitalizes on certain spatiotemporal properties of the vehicles in an area. It utilizes mostly ephemeral ad-hoc networks between vehicles through which messages can be forwarded. The current positions of the vehicles in such an ad-hoc network are considered to find out which one will regain cellular network access first. To achieve that, we see two variants:

  • As described in Section 2, there is a large interest in the industry to create so-called connectivity maps (United States Patentnr. 2015/028,190, 2015). Here, vehicles constantly monitor their cellular network connectivity. Periodically, the vehicles forward their measurements to a central server that generates the connectivity maps by aggregating the input data from many vehicles. The connectivity maps are then sent back to the vehicles which can align their communication accordingly. In our context, the connectivity maps may help vehicles in a dead spot to make accurate predictions about the points in time, they will regain cellular connectivity. This approach is introduced in (Meyer, Puka, & Herrmann, 2019).

  • Assuming that, on rural side roads and in mountainous terrain, the different vehicles tend to have similar speeds, they are for roughly the same amount of time in a dead spot. Now, we simply need to compare the points of time, the vehicles connected via an ad-hoc network entered the dead spot and presume that the one reaching the dead spot first will likely be also the one leaving it first. This approach tends to be a little more imprecise than the one mentioned above but avoiding the creation and maintenance of connectivity maps makes it more simple and easier to realize. It will be discussed in this paper.

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