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Delay sensitive and power-aware SMDP-based connection admission control mechanism in cognitive radio sensor networks

机译:认知无线电传感器网络中基于时延敏感和基于功率感知的基于SMDP的连接允许控制机制

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Due to the opportunistically resource usage of users in cognitive radio sensor networks (CRSNs), the availability of network resources is highly variable. Therefore, admission control is an essential mechanism to manage the traffic of cognitive radio users in order to satisfy the quality of service (QoS) requirements of applications. In this study, a connection admission control (CAC) mechanism is introduced to satisfy the requirements of delay sensitivity and power consumption awareness. This proposed mechanism is modeled through a semi Markov decision process (SMDP) and a linear programming problem is derived with the aim of obtaining the optimal policy to control the traffic of CRSNs and achieving maximum reward. The number of required channels at each network state is estimated through a graph coloring approach. An end to end delay constraint is defined for the optimization problem which is inspired from Klein rock independence approximation. Furthermore, a power-aware weighting method is proposed for this mechanism. We conduct different simulation-based scenarios to investigate the performance of the proposed mechanism. The experimental results demonstrate the efficiency of this SMDP-based mechanism in comparison to the last CAC mechanism in CRSNs. (C) 2017 Elsevier B.V. All rights reserved.
机译:由于认知无线电传感器网络(CRSN)中用户的机会性资源使用,网络资源的可用性变化很大。因此,准入控制是管理认知无线电用户流量的基本机制,以满足应用程序的服务质量(QoS)要求。在这项研究中,引入了一种连接准入控制(CAC)机制来满足延迟敏感性和功耗意识的要求。通过半马尔可夫决策过程(SMDP)对这种提出的机制进行建模,并得出线性规划问题,旨在获得控制CRSN流量的最佳策略并获得最大回报。通过图形着色方法可以估算每个网络状态下所需通道的数量。从Klein岩石独立性近似启发了优化问题的端到端延迟约束。此外,针对该机制提出了一种功率感知加权方法。我们进行不同的基于模拟的方案来研究所提出机制的性能。实验结果证明,与基于CRSN的最后一个CAC机制相比,这种基于SMDP的机制效率高。 (C)2017 Elsevier B.V.保留所有权利。

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