No abstract

This paper proposes a traffic model and a parameter fitting procedure that are capable of achieving accurate prediction of the queuing behavior for IP traffic exhibiting long-range dependence. The modeling process is a discrete-time batch Markovian arrival process (dBMAP) that jointly characterizes the packet arrival process and the packet size distribution. In the proposed dBMAP, packet arrivals occur according to a discrete-time Markov modulated Poisson process (dMMPP) and each arrival is characterized by a packet size with a general distribution that may depend on the phase of the dMMPP. The fitting procedure is designed to provide a close match of both the autocovariance and the marginal distribution of the packet arrival process, using a dMMPP; a packet size distribution is fitted individually to each state of the dMMPP. A major feature of the procedure is that the number of states of the fitted dBMAP is not fixed a priori; it is determined as part of the procedure itself. In this way, the procedure allows establishing a compromise between the accuracy of the fitting and the number of parameters, while maintaining a low computational complexity.We apply the inference procedure to several traffic traces exhibiting long-range dependence. Very good results were obtained since the fitted dBMAPs match closely the autocovariance, the marginal distribution and the queuing behavior of the measured traces. Our results also show that ignoring the packet size distribution and its correlation with the packet arrival process can lead to large errors in terms of queuing behavior.

Abstract-Vehicular Delay-Tolerant Networks (VDTNs) are an application of the Delay-Tolerant Network (DTN) concept, where the movement of vehicles and their message relaying service is used to enable network connectivity under unreliable conditions. To address the problem of intermittent connectivity, long-term message storage is combined with routing schemes that replicate messages at transfer opportunities. However, these strategies can be inefficient in terms of network resource usage. Therefore, efficient scheduling and dropping policies are necessary to improve the overall network performance. This work presents a performance analysis, based on simulation, of the impact of different scheduling and dropping policies enforced on Epidemic and Spray and Wait routing schemes. This paper evaluates these policies from the perspective of their efficiency in reducing the message's end-to-end delay. In our scenario, it is shown that when these policies are based on the message's lifetime criteria, the message average delay decreases significantly and the overall message delivery probability also increases for both routing protocols. Further simulations show that these results outperform the MaxProp and PRoPHET routing protocols that have their own scheduling and dropping mechanisms.

No abstract

No abstract

No abstract

No abstract

No abstract