# Evaluation of the Use of Compressed Sensing in Data Harvesting for Vehicular Sensor Networks
## 3 Related Works  
As commented at the beginning of the paper, our principal interest is the definition of an efficient strategy to harvest the information of a determined urban region of interest (RoI) using the vehicles' sensing equipment. Regarding this task, a survey of urban vehicular sensing platforms is provided by [PERSON] et al. [12], where they analyze protocols such as Mobeyes [13], FleaNet [14] and Vehicular Information Transport Protocol (VITP) [15]. They are described in the following paragraph, highlighting the reason they do not meet the specific requirements of the VSNs. Mobeyes is a proactive urban monitoring strategy where every node that performs a measurement sends a packet with a summary of its recently sampled information to its neighbors. In addition to the sensor readings, these summaries include relevant information like the timestamp and its location. In conventional sensor networks, this information is dispatched to the nodes responsible for analyzing the sampled data. However, in VSNs, this mechanism is not practical due to the vast amount of generated data. Besides, Mobeyes also allows an on-demand harvesting strategy (Mobeyes-ODH) that works as follows. First of all, the fusion center issues a query request which is broadcast in a region of interest. The receiving nodes immediately answer to this query with its data. So, such a scheme has the issue of transmitting a lot of packets that overload the network. In FleaNet query dissemination protocol, queries are advertised only to 1-hop neighbors. After receiving the query, neighbors store the query without any further forwarding. This way, queries are only spread by means of vehicle motion. FleaNet also provides a mechanism to deliver data using multihop communications, but as in Mobeyes, the early response of the nodes receiving the request message overloads the network. VITP, on its side, allows nodes to aggregate information and report summarized results to the requester. This aggregation consists of piggybacking partial results, so although they reduce the number of packets, they still increase their size with each new partial result added to the packet. Another interesting solution is proposed by [PERSON] et al. [16], called Delay-Bounded Vehicular Data Gathering (DB-VDG). This protocol follows the same strategy as we propose in this paper with two variants (Speed-Based Strategy Selection method) SBSS and Distance-Based Strategy Selection method (DBSS). Data harvesting is divided into two stages. In the first stage, the FC node broadcasts a query message in a specific urban region. In the second one, nodes equipped with sensors that receive this query send back the sensed information taking into account the lifetime of the received query. Depending on the selection method, intermediate nodes decide to forward the messages or being themselves ferries for the data. SBSS takes into account the velocity of the node in order to make this decision, while DBSS simply selects the strategy based on the distance to the FC. In both cases, when forwarding is applied intermediate nodes append multiple samples into the same packet preventing the overhead to excessively increase by flooding a large number of (smaller) packets in the network. All in all, the above proposed protocols do not use data compression, a key aspect that we consider pretty important. They only take advantage of traversing packets to append new information as they encounter a new intermediate node. Therefore the size of these packets depends on the number of intermediate nodes forwarding the packet or the areas of the region of interest that the packet must traverse to reach the destination. Nevertheless, with an efficient gathering method, and compression technique we can benefit from this circumstance to, firstly, optimize the number of packets traversing the network, and secondly compress the payload of the packets, with the consequent reduction in the network overload.