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A Bayesian Game Based Optimization Strategy Proposal for Routing in Energy Constrained DTNs

机译:基于贝叶斯博弈的能量受限DTN路由优化策略建议

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In this paper, we propose an optimization strategy to be applied to a well-known DTN routing algorithm as PRoPHET and SimBetTS which, by default, don't regard to the issue of energy constraint. Our proposed strategy is based on modeling of the message forwarding as a Bayesian game that aims specifically to capture the dynamic nature of the multi-copy replication decisions, the energy constraint of the nodes and the belief about the energy of other nodes. In addition, we consider factors of evidence aging on accumulated observations used to update the belief that a node has about the energy of the other nodes. The main feature of this belief update system is not to utilize neighborhood watch or acknowledgment mechanism. Moreover, in this paper, we conduct simulation experiments to evaluate the performance of our optimization strategy proposal from a DTN scenario with heterogeneous nodes based on realistic human mobility traces. Simulations results show that our proposed optimization strategy is able to lead the network to remain operational for a longer period of time and, consequently, to achieve a higher final delivery ratio even when compared to a proposal using energy-aware routing.
机译:在本文中,我们提出了一种优化策略,该策略将应用于著名的DTN路由算法PRoPHET和SimBetTS,默认情况下,该算法不考虑能量约束问题。我们提出的策略基于作为贝叶斯博弈的消息转发建模,该博弈专门旨在捕获多副本复制决策的动态特性,节点的能量约束以及对其他节点的能量的信念。此外,我们在累积的观测值中考虑证据老化的因素,这些观测值用于更新一个节点对其他节点的能量的看法。该信念更新系统的主要特征是不利用邻居监视或确认机制。此外,在本文中,我们进行了仿真实验,以基于真实的人类移动轨迹,从具有异构节点的DTN场景评估我们的优化策略建议的性能。仿真结果表明,与使用能量感知路由的提议相比,我们提出的优化策略能够使网络保持更长的运行时间,因此,可以实现更高的最终交付率。

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