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Energy-Efficient Routing and Rate Allocation for Delay Tolerant Networks

机译:延迟容忍网络的节能路由和速率分配

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摘要

Routing for Delay Tolerant Networks (DTNs) are challengeable for the continuously varied network environment. Most of existing DTN routing algorithms mainly focus on metrics such as delay, hop count and bandwidth, etc. Green communication is a new focus with the goal of saving energy by optimizing network performance and ultimately protecting the natural climate. In this paper, we present an Energy-efficient Routing and Rate Allocation (ERRA) scheme based on Q-learning that can optimize the energy efficiency with the constraints of congestion, buffer and delay. ERRA solves the routing and rate allocation together with reinforce leaning, and then make decisions on relay selection and rate schedule. ERRA explores the possible strategies, and then exploits the knowledge obtained to adapt its relay and schedule strategies. ERRA achieves the desired overall objective by considering the stochastic non-cooperative game under on-line multi-commodity routing situations. The simulation results show that ERRA achieves good energy efficiency and delivery ratio within the delay bound.
机译:对于持续变化的网络环境,延迟容忍网络(DTN)的路由面临挑战。现有的大多数DTN路由算法主要关注延迟,跳数和带宽等指标。绿色通信是新的关注点,其目标是通过优化网络性能并最终保护自然气候来节省能源。在本文中,我们提出了一种基于Q学习的节能路由和费率分配(ERRA)方案,该方案可以在拥塞,缓冲和延迟的约束下优化能效。 ERRA解决路由和速率分配问题,同时增强倾斜度,然后对中继选择和速率计划做出决策。 ERRA探索了可能的策略,然后利用所获得的知识来调整其中继和调度策略。 ERRA通过考虑在线多商品路由情况下的随机非合作博弈来实现预期的总体目标。仿真结果表明,ERRA在延迟范围内具有良好的能效和输送比。

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