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首页> 外文期刊>IEEE/ACM Transactions on Networking >Optimal Forwarding in Delay-Tolerant Networks With Multiple Destinations
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Optimal Forwarding in Delay-Tolerant Networks With Multiple Destinations

机译:具有多个目标的容错网络中的最佳转发

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摘要

We study the tradeoff between delivery delay and energy consumption in a delay-tolerant network in which a message (or a file) has to be delivered to each of several destinations by epidemic relaying. In addition to the destinations, there are several other nodes in the network that can assist in relaying the message. We first assume that, at every instant, all the nodes know the number of relays carrying the message and the number of destinations that have received the message. We formulate the problem as a controlled continuous-time Markov chain and derive the optimal closed-loop control (i.e., forwarding policy). However, in practice, the intermittent connectivity in the network implies that the nodes may not have the required perfect knowledge of the system state. To address this issue, we obtain an ordinary differential equation (ODE) (i.e., a deterministic fluid) approximation for the optimally controlled Markov chain. This fluid approximation also yields an asymptotically optimal open-loop policy. Finally, we evaluate the performance of the deterministic policy over finite networks. Numerical results show that this policy performs close to the optimal closed-loop policy.
机译:我们研究了在时延容忍网络中传递延迟和能耗之间的权衡,在该网络中,必须通过流行病中继将消息(或文件)传递到多个目的地中的每个目的地。除了目的地之外,网络中还有其他几个节点可以帮助中继消息。我们首先假设,在所有时刻,所有节点都知道承载消息的中继的数量以及已接收到消息的目的地的数量。我们将问题表述为受控的连续时间马尔可夫链,并得出最佳的闭环控制(即转发策略)。但是,在实践中,网络中的间歇性连接意味着节点可能不具备所需的系统状态的完整知识。为了解决这个问题,我们获得了最优控制马尔可夫链的常微分方程(ODE)(即确定性流体)近似值。这种流体近似也产生了渐近最优的开环策略。最后,我们评估有限网络上确定性策略的性能。数值结果表明,该策略的性能接近最优闭环策略。

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