Opportunistic Mobile Sensor Data Collection with SCAR

Sensors are now embedded in all sorts of devices (such as phones and PDAs) and attached to many moving things such as robots, vehicles and animals. The collection of data from these mobile sensors presents challenges related to the variability of the topology of the sensor network and the need to limit communication (for energy or bandwidth saving). Fortunately, the data collected, despite considerable, is often delay tolerant and its delivery to the sinks is, in most cases, not time critical. We have devised SCAR, a context aware opportunistic routing protocol which allows efficient routing of sensor data to sinks, through selection of best paths by prediction over movement patterns and current battery level of nodes. In this paper we present the implementation of the protocol in Contiki and validate the approach through the use of the COOJA simulator with mobility traces provided by the ZebraNet Project. We compare the performance with respect to random choice based dissemination.