Query Processing Algorithm Based on Neighbor Information in Delay Tolerant Network

Dameng Wu; Jiangbo Qian; Yefang Chen; Yihong Dong

doi:10.3969/j.issn.1000-0801.2014.04.015

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Query Processing Algorithm Based on Neighbor Information in Delay Tolerant Network

Research And Development | 更新时间：2024-06-05

- Query Processing Algorithm Based on Neighbor Information in Delay Tolerant Network
- Telecommunications Science Vol. 30, Issue 4, Pages: 100-108(2014)
- 作者机构：
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- DOI：10.3969/j.issn.1000-0801.2014.04.015
  CLC：
- Published Online：2014-04，
  
  Published：20 April 2014
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Dameng Wu, Jiangbo Qian, Yefang Chen, et al. Query Processing Algorithm Based on Neighbor Information in Delay Tolerant Network[J]. Telecommunications science, 2014, 30(4): 100-108.
DOI：

Dameng Wu, Jiangbo Qian, Yefang Chen, et al. Query Processing Algorithm Based on Neighbor Information in Delay Tolerant Network[J]. Telecommunications science, 2014, 30(4): 100-108. DOI： 10.3969/j.issn.1000-0801.2014.04.015.

摘要

与传统网络不同，延迟容忍网络（DTN）具有节点移动性、网络间歇连通性，并且能够容忍适当的延迟。随着移动设备的普及，如何在延迟容忍网络中充分利用这些移动设备进行数据查询及信息分享成为值得研究的问题。一般网络可以采用泛洪的方法进行信息的查询，然而这类方法会消耗较多的网络通信资源及移动设备电池能量。针对这一问题，模仿社会网络中人的自然行为特点，充分利用信息精确度（IA）机制提高网络查询成功率。实验结果表明，基于IA的方法具有高效性和稳定性。

Abstract

Different from conventional networks

DTN has several unique characteristics

such as node mobility

loose connectivity

and delay tolerability

etc. As mobile devices have become indispensable in daily life

there emerges a new interesting problem

which is how to take advantage of the portable and powerful facilities to share resources and information. The prevailing approach to process those queries is to use flooding methods because of their quick response and easy maintenance. However

this kind of approaches wastes a huge amount of communication bandwidth and battery power of mobile devices. To tackle this problem

an intelligence accuracy（IA） scheme was introduced to improve network query success rate. The IA scheme mimics natural behavior of human social networking features to promote efficiency of information collection. Experimental results show that the efficiency and effectiveness of the IA approach are as well as its scalability in a volatile environment.

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