In the context of changing travel behaviors and the expanding user base of Geographic Information System (GIS) services, conventional centralized architectures responsible for handling shortest distance queries are facing increasing challenges, such as heightened load pressure and longer response times. To mitigate these concerns, this study is the first to develop an edge computing framework specially tailored for processing distance queries. In conjunction with this innovative system, we have developed a straightforward, yet effective, labeling technique termed Border Labeling. Furthermore, we have devised and implemented a range of query strategies intended to capitalize on the capabilities of the edge computing infrastructure. Our experiments demonstrate that our solution surpasses other methods in terms of both indexing time and query speed across various road network datasets. The empirical evidence from our experiments supports the claim that our edge computing architecture significantly reduces the latency encountered by end-users, thus markedly decreasing their waiting times.

中文翻译：

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探索边缘计算环境中的距离查询处理

在出行行为不断变化和地理信息系统（GIS）服务用户群不断扩大的背景下，负责处理最短距离查询的传统集中式架构面临着越来越大的挑战，例如负载压力增大和响应时间延长等。为了缓解这些担忧，本研究首次开发了专门用于处理距离查询的边缘计算框架。结合这一创新系统，我们开发了一种简单而有效的标签技术，称为“边界标签”。此外，我们设计并实施了一系列查询策略，旨在利用边缘计算基础设施的功能。我们的实验表明，我们的解决方案在各种道路网络数据集的索引时间和查询速度方面都优于其他方法。我们实验的经验证据支持这样的说法：我们的边缘计算架构显着减少了最终用户遇到的延迟，从而显着减少了他们的等待时间。