Mobile Data Collection in Smart City Applications: The Impact of Precedence-based Route Planning on Data Latency

Abstract

Data collection is one of the key building blocks of smart city applications. Sheer number of sensors deployed across the city generate huge amount of data continuously. Due to their limited transmission range, sensors form a sensor network with a base station. The base station acts as a gateway between the network and the remote user and the generated data is collected by the base station. However, due to sensor locations and the transmission range the network may consist of several partitions. A typical solution is employing one or more mobile element(s) to collect data from partitions periodically. Mobile data collection enables intermittent connectivity between sensors and the base station. The major drawback of mobile data collection is increased data latency depending on the velocity of the mobiles. Another challenge is specifying importance for individual sensors in a smart city application. This study evaluates the impact of precedence-based routing of mobiles on data latency in a realistic manner through employing spatial data obtained from a geographic information system. Precedence levels for sensors are determined based on the amenity type of the building they monitor. Mobility of the mobiles is restricted with the drivable road network. The impact of the precedence-based routing according to total path length, maximum data collection delay, and the maximum data latency is evaluated. Obtained results indicate an increase in total path length up to 14% when precedence-based routing is applied. The results also suggest that precedence-based routing increases maximum data collection delay unless the amenity type has fewer points of interest to monitor.