测绘通报 ›› 2017, Vol. 0 ›› Issue (9): 46-50.doi: 10.13474/j.cnki.11-2246.2017.0285

• 学术研究 • 上一篇    下一篇

对等网络遥感影像瓦片资源遗传选择算法

范兆炜1,2, 李子扬1, 周增光1, 李传荣1   

  1. 1. 中国科学院光电研究院中国科学院定量遥感信息技术重点实验室, 北京 100094;
    2. 中国科学院大学, 北京 100049
  • 收稿日期:2017-01-16 修回日期:2017-03-27 出版日期:2017-09-25 发布日期:2017-10-12
  • 通讯作者: 李传荣.E-mail:crli@aoe.ac.cn E-mail:crli@aoe.ac.cn
  • 作者简介:范兆炜(1991-),男,硕士生,主要研究方向为计算机应用技术.E-mail:18401698369@163.com
  • 基金资助:
    国家863计划(2013AA122904)。

Tile Resource Selection Algorithm for Remote Sensing Image Based on Peer-to-Peer Network

FAN Zhaowei1,2, LI Ziyang1, ZHOU Zengguang1, LI Chuanrong1   

  1. 1. Key Laboratory of Quantitative Remote Sensing Information Technology, Academy of Opto-Electronics, Chinese Academy of Sciences, Beijing 100094, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2017-01-16 Revised:2017-03-27 Online:2017-09-25 Published:2017-10-12

摘要: 对等网络技术的快速发展,为遥感影像数据的高效共享开辟了新的途径。对等节点终端间互相进行数据传输的方式,有效地降低了数据共享对服务器的依赖程度,极大地提高了数据分发传输的效率。由于对等网络中各终端可能存储不同区域的影像数据,因此当需要共享某个影像数据时,选择从哪些终端传输哪些瓦片以提高传输效率,是一个需要解决的重要问题。本文研究对等终端间瓦片数据集的高效共享途径,提出了一种基于遗传算法的瓦片资源选择方法,可以有效地解决对等网瓦片资源选择问题。

关键词: 遥感影像, 瓦片, 对等网, 数据传输, 组合优化, 遗传算法

Abstract: The rapid development of peer-to-peer network technology opens up a new way for the efficient sharing of remote sensing image data. The way of data transmission between peer nodes can effectively reduce the dependence of data sharing on the server, and greatly improve the efficiency of data distribution and transmission. As each terminal in the peer-to-peer network may store image data in different areas, therefore, when you need to share a certain image data, how to choose from which terminals to transmit which tiles to improve the transmission efficiency, is an important problem needed to be solved. This paper studies the efficient way to share the tile data sets between peer-to-peer terminals, and proposes a tile resource selection method based on genetic algorithm, which can effectively solve the problem of tile resource selection in the peer-to-peer network.

Key words: remote sensing image, tiles, P2P, data transmission, combinatorial optimization, genetic algorithm

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