Distributed Stream Processing of RNN Query in Mobile Computing

DOI

10.2991/icecee-15.2015.106How to use a DOI?

Keywords

Reverse Nearest Neighbor; Big Data; MapReduce; Cloud Computing

Abstract

Reverse Nearest Neighbor (RNN) queries are a pipeline of complimentary problems, and have aroused a vast concern in the world in the past few years, such as location based services, profile based marketing, resource allocation and traffic monitoring system etc. Now the one of the most important disadvantages for the RNN is that it has inherent sequential nature and using for memory algorithm, which limits its use in data processing of large scale spatial data queries. Scalable algorithms for Reverse Nearest Neighbor queries in distributed environment are the key problem in this paper. First of all, we investigate the SRNN initialization query method based on the inverted grid index. Then, Eager-SRNN has effective treatment on the problem of the scalable Multi-dimensional RNN. Eager-SRNN tries to prune spatial objects step by step as soon as they are accessed. Beyond that, SRNN algorithm is the first attempt for the exact scalable RNN algorithms in a distributed environment on multi-dimensional datasets. An evaluation which we proved through a lot of experiments has been widely applied on the new method of the synthetic data scalability and the performance.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Siqi Xu
AU  - Changqing Ji
AU  - Yanran Zhuang
AU  - Sunying Gao
AU  - Nianpeng Yang
AU  - Jingguo Yan
AU  - Xin Zhang
PY  - 2015/06
DA  - 2015/06
TI  - Distributed Stream Processing of RNN Query in Mobile Computing
BT  - Proceedings of the 2015 International Conference on Electrical, Computer Engineering and Electronics
PB  - Atlantis Press
SP  - 511
EP  - 516
SN  - 2352-538X
UR  - https://doi.org/10.2991/icecee-15.2015.106
DO  - 10.2991/icecee-15.2015.106
ID  - Xu2015/06
ER  -