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A novel dynamic confidence interval based secure channel prediction approach for stream-based multichannel wireless sensor networks

机译:基于流基于流的多通道无线传感器网络的新型动态置信区间的安全信道预测方法

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Considering both channel quality and stability may enhance the likelihood of optimum channel decision for stream-based communication. Good quality stable channels may maintain a particular quality level during data stream transmission and thereby minimize channel switching overheads such as switching delay, energy consumption, and the associated data loss. Among the published multichannel MAC protocols for WSNs, only a few consider channel quality before assigning wireless channels. Whereas to the best of our knowledge, only few contemplates both channel quality and stability during stream-based communication, however, not very suitable for varying (noisy) environment. To bridge this gap, this work proposes a novel dynamic Multichannel Adaptive approach for Grading Immediate Channels (MAGIC). The MAGIC protocol may predict and classify the available channels under channel quality and stability assessment methodology and determines Local Preferred Channels (LPCs) in a noisy environment. Afterwards, the best among those channels may be selected (under some QoS criteria) for stream-based communication in WSNs. The proposed MAGIC algorithm minimizes channel processing overheads by considering only non-blacklisted channels during a communication session. Simulation results show that the MAGIC algorithm achieves better performance than the counterparts in terms of channel switching delay, energy consumption, and the associated throughput loss. (C) 2020 Elsevier B.V. All rights reserved.
机译:考虑到频道质量和稳定性,可以提高基于流的通信的最佳信道决策的可能性。良好的质量稳定通道可以在数据流传输期间维持特定的质量水平,从而最小化诸如切换延迟,能耗和相关数据丢失的信道切换开销。在用于WSN的已发布的多声道MAC协议中,仅在分配无线通道之前仅考虑信道质量。据我们所知,只有很少有少数人在基于流的通信中考虑信道质量和稳定性,但不太适合不同(嘈杂)的环境。为了弥合这一差距,这项工作提出了一种新的动态多声道自适应方法,用于直系立即通道(魔术)。 Magic协议可以预测和分类信道质量和稳定性评估方法下的可用频道,并在嘈杂的环境中确定本地优选信道(LPC)。之后,可以选择这些信道中的最佳(在一些QoS标准下)用于WSN中的基于流的通信。所提出的魔法算法通过在通信会话期间仅考虑非黑名单信道来最小化信道处理开销。仿真结果表明,在信道切换延迟,能耗和相关的吞吐量损失方面,魔术算法比对应物更好的性能。 (c)2020 Elsevier B.v.保留所有权利。

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