دانلود رایگان مقاله ارزیابی تحلیلی عملکرد تماس بر اساس برنامه های پیام رسانی

Abstract

Communications in mobile opportunistic networks, instead of using the Internet infrastructure, take place upon the establishment of ephemeral contacts among mobile nodes using direct communication. In this paper, we analytically model the performance of mobile opportunistic networks for contact-based messaging applications in city squares or gathering points, a key challenging topic that is required for the effective design of novel services. We take into account several social aspects such as: the density of people, the dynamic of people arriving and leaving a place, the size of the messages and the duration of the contacts. We base our models on Population Processes, an approach commonly used to represent the dynamics of biological populations. We study their stable equilibrium points and obtain analytical expressions for their resolution. The evaluations performed show that these models can reproduce the dynamics of message diffusion applications. We demonstrate that when the density of people increases, the effectiveness of the diffusion is improved. Regarding the arrival and departure of people, their impact is more relevant when the density of people is low. Finally, we prove that for large message sizes the effectiveness of the epidemic diffusion is reduced, and novel diffusion protocols should be considered.

5. Conclusions

In this paper, we analytically modelled the performance of mobile opportunistic networks for contact-based messaging applications in city squares or gathering points, a key topic necessary for the effective design of novel services. In our study we took into account several social aspects such as: the density of people, the dynamics of people arriving and leaving a place, the size of the messages and the duration of the contacts. We first introduced a dynamical model that takes into account that nodes can arrive and leave the area. For this model we studied the stability of the fixed points and obtained analytical expressions for its resolution. We proved that when the system reaches equilibrium, the arrival and exit rates are the same, so the total number of nodes in the area remains constant, but this renewal rate implies that not all nodes receive the message. We extended this model taking into account the communication time for transmitting the message. This model describes a system that is also stable when the arrival rate equals the exit rate. For this model, we also obtained analytical expressions for its fixed points and the number of nodes that get the message. The evaluations performed showed that the models can reproduce the dynamics and stable states of message diffusion.