Cooperative mobile data collection in smart cities

Abstract

Smart cities are driven by huge amount of data collected from sensors deployed across the city. Sensors typically form a multi-hop network with a base station (BS ) in order to send their data to the command and control center. However, sparse deployment of sensors can leave subsets of the network partitioned from the rest of the network. In such a case, isolated partitions cannot forward their data to the BS . Consequently, network coverage and data fidelity decline. A possible solution to link partitions and provide connectivity is employing mobile data collectors (MDCs). A smart vehicle supporting wireless communication can act as an MDC and carry data between sensors and the BS . Using a single MDC extends the average tour length. To minimize the maximum tour length, multiple MDCs can be employed. To identify sensors to be visited by each MDC, this paper clusters partitions as many as the number of MDCs and assigns an MDC for each cluster. Then two different cooperative data collection schemes are considered based on the availability of inter-MDC data exchange. If MDCs collaborate in data delivery, they meet at certain meeting points for data exchange. Such a cooperation avoids the requirement of visiting the BS for some MDCs and reduces tour lengths. On the other hand, MDCs closer to the BS can experience data loss due to buffer overflow given the higher volume of the accumulated data. Presented approaches are evaluated in terms of maximum tour length, data latency, and data loss. The smart city application is simulated with deployment of sensors on certain amenity types. Geographic data is obtained from a volunteered geographic information system and MDC mobility is restricted with the road network. Obtained results indicate that MDC cooperation decreases maximum tour length at the expense of increased rate of data loss and data latency.