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首页> 外文期刊>Pervasive and Mobile Computing >Stochastic backlog and delay bounds of generic rate-based AIMD congestion control scheme in cognitive radio sensor networks
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Stochastic backlog and delay bounds of generic rate-based AIMD congestion control scheme in cognitive radio sensor networks

机译:认知无线电传感器网络中基于速率的通用AIMD拥塞控制方案的随机积压和延迟边界

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Performance guarantees for congestion control schemes in cognitive radio sensor networks (CRSNs) can be helpful in order to satisfy the quality of service (QoS) in different applications. Because of the high dynamicity of available bandwidth and network resources in CRSNs, it is more effective to use the stochastic guarantees. In this paper, the stochastic backlog and delay bounds of generic rate-based additive increase and multiplicative decrease (AIMD) congestion control scheme are modeled based on stochastic network calculus (SNC). Particularly, the probabilistic bounds are modeled through moment generating function (MGF)-based SNC with regard to the sending rate distribution of CR source sensors. The proposed stochastic bounds are verified through NS2-based simulations. (C) 2015 Elsevier B.V. All rights reserved.
机译:认知无线电传感器网络(CRSN)中的拥塞控制方案的性能保证可能有助于满足不同应用中的服务质量(QoS)。由于CRSN中可用带宽和网络资源的高度动态性,因此使用随机保证更为有效。本文基于随机网络演算(SNC),对基于速率的通用加性和乘性减少(AIMD)拥塞控制方案进行了随机积压和延迟边界的建模。特别地,关于CR源传感器的发送速率分布,通过基于矩量生成函数(MGF)的SNC对概率边界进行建模。通过基于NS2的仿真验证了所提出的随机界限。 (C)2015 Elsevier B.V.保留所有权利。

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