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| 1 | BGMM: A Body Gauss-Markov Based Mobility Model for Body Area Networks显示文摘Existing mobility models have limitations in their ability to simulate the movement of Wireless Body Area Network(WBAN) since body nodes do not exactly follow either classic mobility models or human contact distributions. In this paper, we propose a new mobility model called Body Gauss–Markov Mobility(BGMM) model,which is oriented specially to WBAN. First, we present the random Gauss-Markov mobility model as the most suitable theoretical basis for developing our new model, as its movement pattern can reveal real human body movements. Next, we examine the transfer of human movement states and derive a simplified mathematical Human Mobility Model(HMM). We then construct the BGMM model by combining the RGMM and HMM models. Finally,we simulate the traces of the new mobility model. We use four direct metrics in our proposed mobility model to evaluate its performance. The simulation results show that the proposed BGMM model performs with respect to the direct mobility metrics and can effectively represent a general WBAN-nodes movement pattern. | Yi Liu Danpu Liu Guangxin Yue | 2018 | Tsinghua Science and Technology2018，23，3： | 4 |
| 2 | 基于随机博弈机制的物联网安全收敛算法研究显示文摘为解决当前物联网安全收敛算法存在的节点覆盖区域冲突,读写性能不强,难以解决信号干涉等不足,本文提出了基于随机博弈机制的物联网安全收敛算法。首先,采取信号正交调节方式,确定信道发射过程中最佳信噪比性能,且通过随机博弈方式进一步调节节点覆盖半径,降低因节点间频率干涉而导致的覆盖区域冲突及读写性能不强等问题,改善了节点间因工作频段相似而导致频率干涉问题;随后,考虑到单纯通过调节节点覆盖半径方式存在的精确化程度不够的问题,采取调整节点发射过程中时间戳读写的措施,构建时间戳读写规避机制,通过调整物联网节点进行信道发射过程中的时间窗口,实现对发射信号的精确传送,进一步降低了信号干涉发射的概率。仿真实验表明:与当前广泛部署的节点能量感知退避算法(Node Energy Aware Backoff Algorithm,NEAB机制),时间窗口感知调整算法(Time Window Aware Adjustment Algorithm,TW2A机制)相比,本文收敛算法具有更小的网络完全收敛时间与节点读写时间,以及更少的单节点最大收敛次数,具有很强的实际部署价值。 | 廖慧惠 杜秀全 | 2019 | 井冈山大学学报(自然科学版)2019，40，2： | 1 |
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