A theoretical analysis of buffer occupancy for Intermittently-Connected Networks.

Network congestion is a well-known problem that may heavily affect the overall network performance. Congestion control approaches in Intermittently-Connected Networks (ICNs) differ from those used in classical networks, since the assumptions of “universal connectivity” of the nodes and “global information” about the network do not hold. In this paper, an analytical framework is proposed to investigate node buffer occupancy in ICNs through bulk-arrivals/bulk-services queuing models. A relation in the z-domain between the discrete probability densities of the buffer state occupancies and of the sizes of the arriving bulks is exploited to analyze two classes of forwarding strategies for ICNs. The infinite- and finite-buffer cases are investigated, simulated, and compared in terms of the concept of stochastic order, which is also used to compare models obtained for different parameter choices. The results can be exploited for buffer dimensioning and for deriving estimates of performance metrics such as average buffer occupancy, average delivery delay, and buffer overflow probability. The theoretical analysis is complemented by numerical outcomes from a network simulator and from real mobility traces.