A Data Forwarding Approach for Opportunistic Mobile Sensor Networks in Fire-Rescue Scenario

Abstract

The opportunistic mobile sensor network has been extensively used in various public safety applications such as the fire-rescue scenario, since it can provide a surveillance range with an inexpensive cost and avoid the dangers of staying in the risk zones to humans. However, the sensor nodes thrown by firefighters in the fire-rescue scenario are easy to move away from current positions due to many environmental factors such as the building structure damages, airflow push or even some explosions. Consequently, the contacts between nodes become scarce and momentary, thereby making the gathered data packets difficult to be forwarded along stable communication paths. Firstly, the mobility patterns of nodes in the fire-rescue scenario are classified into three types: small-range mobile nodes, large-range mobile nodes and firefighter nodes. Then, the optimal proportions of different types of nodes in the data holders are specially investigated mathematically to maximize the delivery ratio. Thus, a data forwarding approach for fire-rescue scenario (DFAFR) is proposed. In DFAFR, each data holder forwards the held data packets to neighbouring nodes independently, and the optimal proportions of data holders are maintained approximatively. Finally, the performance of DFAFR is analyzed through simulation experiments that produce preferable results in the fire-rescue scenario, indicating that DFAFR can improve the delivery ratio and shorten the delivery delay, so that the fire behavior can be reported and processed timely.