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An energy efficient adaptive HELLO algorithm for mobile ad hoc networks

机译:一种适用于移动自组网的节能高效HELLO算法

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摘要

HELLO protocol or neighborhood discovery is essential in wireless ad hoc networks. It makes the rules for nodes to claim their existence/aliveness. In the presence of node mobility, no fix optimal HELLO frequency and optimal transmission range exist to maintain accurate neighborhood tables while reducing the energy consumption and bandwidth occupation. Thus a Turnover based Frequency and transmission Power Adaptation algorithm (TFPA) is presented in this paper. The method enables nodes in mobile networks to dynamically adjust both their HELLO frequency and transmission range depending on the relative speed. In TFPA, each node monitors its neighborhood table to count new neighbors and calculate the turnover ratio. The relationship between relative speed and turnover ratio is formulated and optimal transmission range is derived according to battery consumption model to minimize the overall transmission energy. By taking advantage of the theoretical analysis, the HELLO frequency is adapted dynamically in conjunction with the transmission range to maintain accurate neighborhood table and to allow important energy savings. The algorithm is simulated and compared to other state-of-the-art algorithms. The experimental results demonstrate that the TFPA algorithm obtains high neighborhood accuracy with low HELLO frequency (at least 11% average reduction) and with the lowest energy consumption. Besides, the TFPA algorithm does not require any additional GPS-like device to estimate the relative speed for each node, hence the hardware cost is reduced.
机译:HELLO协议或邻居发现在无线ad hoc网络中至关重要。它使节点的规则声明其存在/活动。在存在节点移动性的情况下,不存在固定的最佳HELLO频率和最佳传输范围来维护准确的邻域表,同时减少能耗和带宽占用。因此,本文提出了一种基于周转的频率和发射功率自适应算法(TFPA)。该方法使移动网络中的节点能够根据相对速度动态地调整其HELLO频率和传输范围。在TFPA中,每个节点监视其邻居表以对新邻居进行计数并计算周转率。建立了相对速度与周转率之间的关系,并根据电池消耗模型推导了最佳的传输范围,以最大程度地降低总传输能量。通过利用理论分析,HELLO频率可以与传输范围一起动态调整,以保持准确的邻域表并节省大量能源。模拟了该算法并将其与其他最新算法进行比较。实验结果表明,TFPA算法以较低的HELLO频率(平均降低幅度至少为11%)以及最低的能耗获得了较高的邻域精度。此外,TFPA算法不需要任何额外的类似GPS的设备来估计每个节点的相对速度,因此降低了硬件成本。

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