延迟容忍网络中基于邻居信息精确度的查询算法

吴大猛; 钱江波; 陈叶芳; 董一鸿

doi:10.3969/j.issn.1000-0801.2014.04.015

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延迟容忍网络中基于邻居信息精确度的查询算法

研究与开发 | 更新时间：2024-06-05

- 延迟容忍网络中基于邻居信息精确度的查询算法
- Query Processing Algorithm Based on Neighbor Information in Delay Tolerant Network
- 电信科学 2014年30卷第4期页码：100-108
- 作者机构：
- 作者简介：
  
  [ "吴大猛，男，宁波大学硕士生，主要研究方向为延迟容忍网络查询处理。" ]
  [ "钱江波，男，博士，宁波大学教授，主要研究方向为数据库、数据流、逻辑电路设计。" ]
  [ "陈叶芳，女，宁波大学讲师，主要研究方向为数据流处理。" ]
  [ "董一鸿，男，博士，宁波大学教授，主要研究方向为移动数据库、数据挖掘和人工智能。" ]
- 基金信息：
  
  浙江省自然科学基金资助项目;The Natural Science Foundation of Zhejiang Province(LY13F020040);宁波市自然科学基金资助项目(2012A610065;2013A610063);浙江省“信息与通信工程”重中之重学科开放基金资助项目
- DOI：10.3969/j.issn.1000-0801.2014.04.015
  中图分类号：
- 网络出版日期：2014-04，
  
  纸质出版日期：2014-04-20
- 稿件说明：
移动端阅览
吴大猛, 钱江波, 陈叶芳, 等. 延迟容忍网络中基于邻居信息精确度的查询算法[J]. 电信科学, 2014,30(4):100-108.

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.
吴大猛, 钱江波, 陈叶芳, 等. 延迟容忍网络中基于邻居信息精确度的查询算法[J]. 电信科学, 2014,30(4):100-108. DOI： 10.3969/j.issn.1000-0801.2014.04.015.

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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