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On the Optimality of Generic Rate-Based AIMD and AIAD Congestion Control Schemes in Cognitive Radio Sensor Networks

机译:认知无线电传感器网络中基于通用速率的AIMD和AIAD拥塞控制方案的最优性

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Investigating the optimality and the modeling of congestion control schemes is crucial in order to provide quality of service (QoS) for various applications in cognitive radio sensor networks (CRSNs). This paper develops an analytical framework to study the optimality of rate-based generic AIMD and AIAD congestion control schemes. In this way, a congestion model is introduced to describe the congestion behavior of CRSNs. A semi-Markov chain (SMC) is proposed to model the steady-state sending rate distribution of source nodes based on the congestion model. The optimality of generic AIMD and AIAD, based on the proposed models, is analyzed in order to maximize the defined rate-congestion ratio (RCR). The analytical results are verified through various NS2-based simulations in CRSNs.
机译:为了为认知无线电传感器网络(CRSN)中的各种应用提供服务质量(QoS),研究拥塞控制方案的最优性和建模至关重要。本文建立了一个分析框架,以研究基于速率的通用AIMD和AIAD拥塞控制方案的最优性。这样,引入了拥塞模型来描述CRSN的拥塞行为。提出了一种半马尔可夫链(SMC),用于基于拥塞模型对源节点的稳态发送速率分布进行建模。基于提出的模型,对通用AIMD和AIAD的最优性进行了分析,以使定义的速率-拥塞比(RCR)最大化。分析结果通过CRSN中基于NS2的各种模拟进行了验证。

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