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首页> 外文期刊>IEEE Journal on Selected Areas in Communications >Adaptive energy conserving algorithms for neighbor discovery in opportunistic Bluetooth networks
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Adaptive energy conserving algorithms for neighbor discovery in opportunistic Bluetooth networks

机译：机会性蓝牙网络中用于邻居发现的自适应节能算法

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摘要

In this paper, we introduce and evaluate novel adaptive schemes for neighbor discovery in Bluetooth-enabled ad-hoc networks. In an ad-hoc peer-to-peer setting, neighbor search is a continuous, hence battery draining process. In order to save energy when the device is unlikely to encounter a neighbor, we adaptively choose parameter settings depending on a mobility context to decrease the expected power consumption of Bluetooth-enabled devices. For this purpose, we first determine the mean discovery time and power consumption values for In different Bluetooth parameter settings through a comprehensive exploration of the parameter space by means of simulation validated by experiments on real devices. The fastest average discovery time obtained is 0.2 s, while at an average discovery time of I s the power consumption is just 1.5 times that of the idle mode on our devices. We then introduce two adaptive algorithms for dynamically adjusting the Bluetooth parameters based on past perceived activity in the ad-hoc network. Both adaptive schemes for selecting the discovery mode are based only on locally-available information. We evaluate these algorithms in a node mobility simulation. Our adaptive algorithms reduce energy consumption by 50% and have up to 8% better performance over a static power-con serving scheme
机译：在本文中，我们介绍并评估了用于蓝牙自组织网络中邻居发现的新型自适应方案。在临时对等设置中，邻居搜索是一个连续的过程，因此会消耗电池电量。为了在设备不太可能遇到邻居时节省能量，我们根据移动性上下文自适应地选择参数设置，以降低启用蓝牙的设备的预期功耗。为此，我们首先通过在真实设备上进行的实验验证的模拟，通过对参数空间的全面探索，确定在不同蓝牙参数设置中的平均发现时间和功耗值。最快的平均发现时间为0.2 s，而平均发现时间为s时，功耗仅为我们设备上空闲模式的1.5倍。然后，我们介绍了两种自适应算法，用于根据ad-hoc网络中过去的感知活动动态调整蓝牙参数。用于选择发现模式的两种自适应方案都仅基于本地可用信息。我们在节点移动性仿真中评估这些算法。我们的自适应算法可将能耗降低50％，并且性能比静态功率节省方案高出8％。

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