Abstract
We propose a new harvesting approach for Vehicular Sensor Networks based on compressed sensing (CS) technology called Compressed Sensing-based Vehicular Data Harvesting (CS-VDH). This compression technology allows for the reduction of the information volume that nodes must send back to the fusion center and also an accurate recovery of the original data, even in absence of several original measurements. Our proposed method, thanks to a proper design of a delay function, orders the transmission of these measurements, being the nodes farther from the fusion center, the ones starting this transmission. This way, intermediate nodes are more likely to introduce their measurements in a packet traversing the network and to apply the CS technology. This way the contribution is twofold, adding different measurements to traversing packets, we reduce the total overload of the network, and also reducing the size of the packets thanks to the applied compression technology. We evaluate our solution by using ns-2 simulations in a realistic vehicular environment generated by SUMO, a well-known traffic simulator tool in the Vehicular Network domain. Our simulations show that CS-VDH outperforms Delay-Bounded Vehicular Data Gathering (DB-VDG), a well-known protocol for data gathering in vehicular sensor networks which considers a specific delay bound. We also evaluated the proper design of our delay function, as well as the accuracy in the reconstruction of the original data. Regarding this latter topic, our experiments proved that our proposed solution can recover sampled data with little error while still reducing the amount of information traveling through the vehicular network.
Highlights
Vehicular ad-hoc networks (VANETs) have drawn the attention of both the industry and research communities due to the number of services and applications they can provide in real life to different entities such as governments, car manufacturers, and communication operators
Considering the specific requirements and conditions of Vehicular Sensor Networks (VSNs), this paper proposes a data gathering solution which comprises two stages: (i) a query dissemination process where the fusion center (FC) broadcasts a message within a determined region of interest, and (ii) the harvesting stage where vehicles send their measurements back to the FC in an efficient way
Our proposed solution comprises the whole process of distributing the query inside an region of interest (RoI) and the transmission of the sensed information from the vehicles inside this region to the FC
Summary
Vehicular ad-hoc networks (VANETs) have drawn the attention of both the industry and research communities due to the number of services and applications they can provide in real life to different entities such as governments, car manufacturers, and communication operators. In the last few years, a new application domain called Vehicular Sensor Networks (VSNs) has emerged. It comes from the integration of wireless sensor networks (WSNs) and VANETs. That is, instead of deploying a high number of sensors in a specific urban area to measure a particular data of interest, cars equipped with sensors can be used as mobile sensing nodes. The Compressed Sensing technology was proposed by Candès and Donoho among others [1,2,3] as an alternative to the traditional sampling methods following the Nyquist–Shannon theorem. The argument posed by CS is that regarding signal information, all the elements of the signal are not always significant.
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