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Generic Neighbor Discovery Accelerations in Mobile Applications

机译：移动应用程序中的通用邻居发现加速

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摘要

As a supporting primitive of many mobile applications, neighbor discovery identifies nearby devices so that they can exchange information and collaborate in a peer-to-peer manner. To date, discovery schemes trade a long latency for energy efficiency and require a collaborative duty cycle pattern, and thus they are not suitable for interactive mobile applications where a user is unable to configure others' devices. In this article, we propose Acc, which serves as an on-demand generic discovery accelerating middleware for many deterministic neighbor discovery schemes. Acc leverages the discovery capabilities of neighbor devices, supporting both direct and indirect neighbor discoveries. Further, we present a proactive online rendezvous maintenance mechanism, which is used to reduce delays for the detection of leaving of neighbors. Our evaluations show that Acc-assisted discovery schemes reduce latency by up to 51.8% compared to schemes consuming the same amount of energy. More importantly, to prove the real-world value of Acc, we further present and evaluate a Crowd-Alert application where Acc is employed by taxi drivers to accelerate selection of a direction with fewer competing taxis and more potential passengers, based on a 280GB dataset of more than 14,000 taxis in Shenzhen, the most crowded city in China.
机译：作为许多移动应用程序的支持原语，邻居发现可以识别附近的设备，以便它们可以交换信息并以对等方式进行协作。迄今为止，发现方案在能量效率方面需要较长的等待时间，并且需要协作的占空比模式，因此，它们不适用于用户无法配置其他设备的交互式移动应用程序。在本文中，我们提出了Acc，它是许多确定性邻居发现方案的按需通用发现加速中间件。 Acc利用邻居设备的发现功能，支持直接和间接邻居发现。此外，我们提出了一种主动的在线会合维护机制，该机制可用于减少检测邻居离开的延迟。我们的评估表明，与消耗相同能量的方案相比，加速辅助发现方案最多可将等待时间减少51.8％。更重要的是，为了证明Acc的真实价值，我们进一步展示并评估了Crowd-Alert应用程序，其中出租车司机使用Acc来加速选择方向，而基于280GB数据集的竞争性出租车更少而潜在乘客更多深圳是中国最拥挤的城市，共计有14,000多辆出租车。

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