Efficient Indexing in Moving Object Trajectories

Publish Year: 1395
نوع سند: مقاله کنفرانسی
زبان: English
View: 719

This Paper With 8 Page And PDF Format Ready To Download

  • Certificate
  • من نویسنده این مقاله هستم

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این Paper:

شناسه ملی سند علمی:

ICSEE01_007

تاریخ نمایه سازی: 19 خرداد 1396

Abstract:

In the last decade, there has been an explosive growth in the number of location-aware systems. Accordingly, large amounts of spatio-temporal data are accumulated. Efficient indexing and querying techniques to manage these large volumes of trajectory data sets are necessary. In this paper we propose ETB-tree (Extended TB-tree), an efficient and scalable indexing to respond the moving object trajectories related queries. Reducing the search space is the main purpose of ETB-tree to decrease the response-time of queries. In the proposed method, each trajectory is separately indexed using a distinct TB-tree. The roots of these trees participate in constructing a particular sorted link list. Every node in this linked list contains constraining information related to its associative tree in order to restrict the overall search space. According to presented results in this paper, the new indexing approach achieves much better performance than TB-tree. Finally, we will show that this indexing method is suitable to the several important categories of queries such as range queries, time slice queries, window queries, k-nearest neighbor queries, closest pair queries, or trajectory queries

Authors

Mohammad Reza Abbasifard

MODB Lab., School of Computer Engineering, Iran University of Science and Technology,Tehran, Iran & Adiban Institute of Higher Education,Garmsar, Iran

Hassan Naderi

MODB Lab., School of Computer Engineering, Iran University of Science and Technology,Tehran, Iran

Hamideh Abbasiforoud

Adiban Institute of Higher Education,Garmsar, Iran

مراجع و منابع این Paper:

لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :
  • J. Birnbaum, H.-C. Meng, J.-H. Hwang, and C. Lawson, _ ...
  • Y. Zheng and X. Zhou. (2011). Computing with Spatial Trajectories ...
  • D. Pfoser, C. S. Jensen, and Y. Theodoridis, "Novel Approaches ...
  • _ F. Mokbel, T. M. Ghanem, and W. G. Aref, ...
  • L.-V. Nguyen-Dinh, W. G. Aref, and M. F. Mokbel, _ ...
  • Y. Manolopoulos, A. Nanopoulos, A. N. Papadopoulos, and Y. Theodoridis. ...
  • Y. Gao, B. Zheng, G. Chen, and Q. Li, "Algorithms ...
  • X. Xu, J. Han, and W. Lu, "RT-tree: An improved ...
  • M. A. Nascimento and J. R. O. Silva, "Towards historical ...
  • Y. _ and D. Papadias, "Efficient Historical R-Trees, " in ...
  • Y. Theodoridis, M. Vazirgiannis, and T. Sellis, _ Spatio -temporal ...
  • Y. Tao and D. Papadias, "MV3R-Tre. A Spatio -Temporal Access ...
  • نمایش کامل مراجع