# Fog-Based Two-Phase Event Monitoring and Data Gathering in Vehicular Sensor Networks
## 2 Related Work
### Event Monitoring and Data Gathering  
[PERSON] et al. (2015) proposed the MobEyes system for proactive urban monitoring. The system exploits the vehicle mobility to opportunistically diffuse concise summaries of the sensed data, and it harvests these summaries and builds a low-cost distributed index of the stored data to support various applications. [PERSON] et al. (2016) proposed a data management system called CarTelfor querying and collecting data from mobile vehicles, which enables the application development with the data collected. [PERSON] et al. (2017) proposed a delay-bounded vehicular data-gathering approach, which exploits the time interval to harvest data from the region of interest satisfying specified time constraints and properly alternates the data muling and multi-hop forwarding strategies. Yet, the solution has to be integrated with a time-stable geocast protocol for the query propagation and result collection. They depend on multi-hop in-network communications and \"store-carry-forward\" opportunistic communications, which encounter larger delay and communication cost. Besides minimizing the delay from source to destination, event-monitoring and data-gathering protocols also try to minimize the consumed resources while ensuring that the collected information meets certain maximum delay requirements. [PERSON] et al. (2018) proposed a pull-based data-gathering strategy called GeoVanet. It adopts a distributed hash table based model to identify a fixed geographical location where a mailbox is dedicated to the query, so users are able to send queries to a set of cars and find the desired information in a bounded time. [PERSON] (2019) introduced a method of selective data collection for traffic control applications. The underlying idea is to detect the necessity of data transfers on the basis of the uncertainty determination of the traffic control decisions, and sensor data are transmitted from vehicles to the control node only at selected time moments. [PERSON] et al. (2010) presented the two protocols called D-Greedy and D-MinCost for traffic-monitoring in vehicular networks. They defined two operation modes, multi-hop forwarding (MF) mode and the DTN (Delay Tolerant Network) mode (DM). During MF mode, messages are forwarded using Greedy-DTN through the shortest path to the destination, while in DM mode, messages are only forwarded at intersections to keep them inside the shortest path when the current carrier moves away. As the volume of sensed data might be large, there is also some research on reducing the volume of sensed data and the cost of gathering them. [PERSON] et al. (2017) proposed an event-exchanging and data-gathering scheme based on the Flajolet-Martin sketches in vehicular networks. The sketchescould be exchanged without loss of information and be duplicate insensitive, so it allows manipulating the same physical repository for all vehicles. [PERSON] et al. (2018) proposed a cooperative storage solution in vehicular sensor networks for mobile surveillance. Nodes first capture images from links/streets and then eliminate redundant data by exchanging image tags between vehicles, and it also includes a distributed storage balancing mechanism to offload data from heavy-load nodes to light-load nodes. Recently, the compressive sensing (CS) technique was also used for data-gathering in VANETs. [PERSON] et al. (2018) proposed the CS-based sharing mechanism to enable efficient decentralized context sharing in vehicular networks. It exploits message aggregation and the sparsity of events to reduce the total number of message exchanges. The idea of data aggregation and compressive sensing is orthogonal to the proposed TPEG mechanism, and they could be embedded in our scheme to reduce the cost of message transmissions further. The proposed scheme differs from the above-mentioned schemes in the mode of sensing for event-monitoring. When nodes work in LCS mode, only the sketched data need to be uploaded to the road side unit for event-monitoring.