Trajectory Optimization of Packet Ferries in Opportunistic Social-Based Machine-to-Machine Networks

Machine-to-machine (M2M) communication is an emerging paradigm to connect a large number of devices through wireless technologies. In recent application scenarios, devices are normally carried by people in social contexts. Like the behavior of people, the moving activity of devices always happens in a specific area, which corresponds to some specific communities. How to guarantee the higher packet delivery ratio while reducing forwarding delay in such M2M networks is a challenging issue and has not been well addressed yet. In this paper, we put some special mobile devices (called postmen) in the opportunistic social-based M2M networks and their main responsibility is to carry packets for normal devices which belong to specific communities. Our work focuses on the optimization of the moving trajectory by considering the minimum transmission delay. We formulate the optimal issue into semi-Markov Decision Process model. The decision process includes two parts: packets-choosing strategy and trajectory of packet-ferrying determination strategy. By maximizing the individual reward of a postman, its optimal trajectory will be found. Furthermore, the proposed solution guarantees the packet delivery ratio and delay for isolated communities. Simulation results show that the proposed packet-ferrying solution outperforms the two existing ferrying solutions in terms of packet delivery ratio. © 2013 Xin Guan.