Towards an efficient routing web processing service through capturing real-time road conditions from big data

M. Bakillah, A. Mobasheri, S. Liang, A. Zipf
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引用次数: 16

Abstract

The rapidly growing number of crowdsourcing platforms generates huge volumes of volunteered geographic information (VGI), which requires analysis to reveal their potential. The huge volumes of data appear as an opportunity to improve various applications, including routing and navigation services. How existing techniques for dealing with Big Data could be useful for the analysis of VGI remains an open question, since VGI differs from traditional data. In this paper, we focus on examining the latest developments and issues associated with big data from the perspective of the analysis of VGI. This paper notably presents our new architecture for exploiting Big VGI in event service processing in support to optimization of routing service. In addition, our study highlights the opportunities that are created by the emergence of Big VGI and crowdsourced data on improving routing and navigation services, as well as the challenges that remain to be addressed to make this a reality. Finally, avenues for future research on the next generation of collaborative routing and navigation services are presented.
通过大数据获取实时路况,实现高效的路由网络处理服务
快速增长的众包平台产生了大量的志愿地理信息(VGI),需要对其进行分析以揭示其潜力。海量的数据似乎是一个改进各种应用程序的机会,包括路由和导航服务。处理大数据的现有技术如何对VGI分析有用仍然是一个悬而未决的问题,因为VGI不同于传统数据。本文主要从VGI分析的角度探讨大数据的最新发展和相关问题。本文重点介绍了在事件服务处理中利用大VGI支持路由服务优化的新体系结构。此外,我们的研究还强调了大VGI和众包数据的出现为改善路线和导航服务带来的机遇,以及要实现这一目标仍需解决的挑战。最后,提出了下一代协同路由和导航服务的未来研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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