Electronic Resource
Continuously Monitoring Optimal Routes with Collective Spatial Keywords on Road Networks
| العنوان: | Continuously Monitoring Optimal Routes with Collective Spatial Keywords on Road Networks |
|---|---|
| المؤلفون: | Li, Jiajia, Wang, Zongbo, Zhang, Yifei, Zhao, Liang, Li, Lei, Zong, Chuanyu |
| بيانات النشر: | Institute of Electrical and Electronics Engineers Inc. 2022 |
| نوع الوثيقة: | Electronic Resource |
| مستخلص: | The keyword-aware route planning problem, which returns the best route satisfying all the user-specified keywords, has attracted more and more research attention. However, existing research work mainly focuses on improving the efficiency of snapshot queries, but does not consider continuously monitoring queries. This paper is the first to investigate the continuous Optimal Routes with Collective Spatial Keywords (ORCSK) problem, which continuously returns the optimal route that can collectively cover the required spatial keywords for the given path on which a user is travelling. The direct solution is to perform multiple snapshot queries, which is obviously inefficient and infeasible. Based on the state-of-the-art algorithm DAPrune for answering ORCSK, we Figure out the safe-region for queries based on two proposed theorem, which means that results do not change within this region. Moreover, when the user leaves the safe-region, the result has to be recalculated. To tackle this scenario, we also propose a baseline algorithm and an optimization algorithm based on DAPrune, which can make full use of previously computed useful information to efficiently update the results. Comprehensive experiments with different parameter settings on multiple real-world road networks show that our safe-region based method is superior to the competitors in orders of magnitude. © 2022 IEEE. |
| مصطلحات الفهرس: | Continuous, Keyword-aware route planning, Safe-region, Spatial keywords, Conference paper |
| URL: | |
| الاتاحة: | Open access content. Open access content |
| ملاحظة: | English |
| Other Numbers: | HNK oai:repository.hkust.edu.hk:1783.1-132417 Proceedings - 2022 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Autonomous and Trusted Vehicles, Scalable Computing and Communications, Digital Twin, Privacy Computing, Metaverse, SmartWorld/UIC/ATC/ScalCom/DigitalTwin/PriComp/Metaverse 2022, December 2022, article number 10189471, p. 41-48 1415833433 |
| المصدر المساهم: | HONG KONG UNIV OF SCI & TECH, THE From OAIster®, provided by the OCLC Cooperative. |
| رقم الانضمام: | edsoai.on1415833433 |
| قاعدة البيانات: | OAIster |
| الوصف غير متاح. |