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Control superframe for high throughput of cluster-based WBAN with CSMA/CA

机译:控制超帧,可通过CSMA / CA实现基于集群的WBAN的高吞吐量

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Due to rapidly increasing of elderly population all over the world and quickly developing of entertainment devices, wireless body area network (WBAN) attracts attention. For both medical and non-medical applications, a reliability, high energy-efficiency and high throughput of WBAN communication are requested. The well-known cluster-based is proposed to obtain the high energy-efficiency, however the transmission in every cluster is controlled on MAC layer by superframe in order to obtain the high throughput. The performance of original cluster-based, complete control and spatial reuse superframe scenarios is analyzed and compared. The calculation result indicates that the spatial reuse superframe outperforms the original cluster-based when the access probability and/or the total number of sensors are high. Furthermore, there are the optimal number of clusters, the access probabilities and the total number of sensors that achieve the highest throughput. The optimization method of number of spatial reuse superframe (k) is proposed to obtain the highest throughput when another factors change. k increases when another factors of system model increase, excepted the payload. The optimization method of another factors is similar and the proposed method can be applied to not only IEEE802.15.6 WBAN but also another cluster-based wireless sensor networks.
机译:由于全世界老年人口的迅速增加和娱乐设备的迅速发展,无线人体局域网(WBAN)引起了人们的关注。对于医学和非医学应用,都要求WBAN通信的可靠性,高能效和高吞吐量。为了获得高能量效率,提出了基于众所周知的基于簇的方法,但是为了获得高吞吐量,通过超帧在MAC层上控制每个簇中的传输。分析并比较了基于原始群集,完全控制和空间重用的超帧方案的性能。计算结果表明,当访问概率和/或传感器总数较高时,空间复用超帧的性能优于原始的基于聚类的帧。此外,还有达到最高吞吐量的最佳群集数量,访问概率和传感器总数。提出了空间复用超帧数(k)的优化方法,以在其他因素变化时获得最高的吞吐量。当系统模型的其他因素(有效载荷除外)增加时,k就会增加。其他因素的优化方法相似,所提出的方法不仅可以应用于IEEE802.15.6 WBAN,而且可以应用于其他基于集群的无线传感器网络。

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