A Prototype Study on Hybrid Sensor-Vehicular Networks Extended

In this paper we present a concept where we combine two forms of networks that both attracted a lot of research efforts recently. Both Vehicular Ad-hoc Networks (VANETs) and Wireless Sensor Networks (WSNs) are subject of ongoing research activities. However, the characteristics of VANETs and WSNs are very different. Nodes in sensor networks are highly miniaturized, mostly static, very resource and energy constrained, and usually have good sensing capabilities. In contrast, VANETs have very dynamic topologies and the vehicles do not suffer from significant energy constraints. The vehicles could be equipped with sensors themselves. However, the sensor coverage cannot be guaranteed, as vehicles are not present everywhere and at all times and some kinds of events cannot be reliabily detected by moving entities. We introduce the new concept of Hybrid Sensor-Vehicular Networks so that both network types can benefit from the strengths of each other while compensating the weaknesses. We use a Wireless Sensor Network deployed in or near roads as a sensor grid with constant availability and dense coverage in contrast to the vehicle-to-vehicle network which might have only sparse coverage. The sensor network constantly communicates its sensor data to the vehicles driving on the road, delivering them with accurate and up-to-date sensor information. Vehicles communicate to disseminate this information to over comparatively long distances. There, the vehicles deliver this data back the sensor network where it is stored for future retrieval by other vehicles. This relieves the sensor network from the energy-consuming task to transfer the data hop-by-hop inside the WSN itself. Such Hybrid Sensor-Vehicular Networks are suited for all applications where a stationary WSN collects sensor data that is disseminated only on a small scale within the WSN, then delivered to vehicles which transfer it to other regions by multi-hop routing or vehicle movement and either hand it off to interested vehicles or to remote WSN nodes that store the data and deliver it to approaching cars on certain conditions. We use an example for further explaining this concept. Assume we have a road segment as shown in Figure 1. The application implements a dangerous road condition warning, where drivers are warned about potentially dangerous road conditions like e.g. icy road. First, a WSN node detects ice on the road and shares this information with neighboring motes ( 1 ©) inside a small region. When a vehicle A enters this region, the WSN triggers a vehicle-present event and the information is transmitted to the car ( 2 ©). This way, the driver of vehicle A would receive a short-term warning and can react accordingly. Vehicle A forwards the information via the long-range VANET to vehicle B ( 3 ©). A relevance function determines that vehicle B is in a good position to feed the information back to the WSN for further availability. As the road splits at position B, the icy road information would otherwise become unavailable to vehicles approaching from the lower road. So B transfers the information back to the WSN ( 4 ©) and the nodes distribute it in a small neighbourship for redundancy purposes ( 5 ©). A and B leave this road segment ( 6 ©) and are out of communication range, when vehicle C approaches the intersection and still receives the warning information from the WSN ( 7 ©). The vehicle displays a warning to the driver who has plenty of time to adapt his driving style to the approaching danger. There are two important observations here: