基于基址重定位的快速域名压缩算法
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

基金项目:

国家自然科学基金(61303242)


Fast Domain Name Compression Algorithm Based on Base Relocation
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 增强出版
  • |
  • 文章评论
    摘要:

    为了提高DNS服务器的性能,提出了基于M/M/c排队系统的分析模型.利用该模型分析了DNS服务器的响应时间百分比,确定了其性能瓶颈在于域名压缩速率.目前传统压缩算法由于规则的限制只能在查询应答时进行实时的域名压缩,在高访问量场景存在性能问题.为了提高压缩速率,从DNS数据特征方面对域名压缩的原理进行了剖析,并在此基础上结合重定位技术,提出一种新的域名压缩算法.新的设计改变了传统的DNS数据处理流程,通过压缩前置,降低了应答的实时消耗.实验结果表明,该算法在压缩比损失很小的条件下提升了系统资源利用率,达到了优化响应时间百分比的目的.

    Abstract:

    In order to improve the performance of the DNS server, a mathematical model based on M/M/c queue theory was proposed. The probability distribution function of response time was analyzed according to this model, which identifies domain name compression rate as the performance bottleneck. Due to the rule of traditional domain name compression algorithm, DNS servers can only perform real-time domain name compression when the query is answered, which causes a performance problem in the high-traffic scenario. To improve the domain name compression rate, the principle of domain name compression was analyzed from the aspects of DNS data characteristics. Based on this, combing with base relocation technology, a new domain name compression algorithm was proposed. The new design changes the traditional DNS data process, which reduces the real-time consumption during response by pre-compressing. Experimental results show that the algorithm improves the system resource utilization under the condition of small compression loss and achieves the goal of optimizing the percentile response time.

    参考文献
    相似文献
    引证文献
引用本文

闫夏莉,王骞,吕万波,张海阔,岳巧丽,曹爽.基于基址重定位的快速域名压缩算法.计算机系统应用,2020,29(1):151-157

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2019-06-11
  • 最后修改日期:2019-07-12
  • 录用日期:
  • 在线发布日期: 2019-12-30
  • 出版日期: 2020-01-15
您是第位访问者
版权所有:中国科学院软件研究所 京ICP备05046678号-3
地址:北京海淀区中关村南四街4号 中科院软件园区 7号楼305房间,邮政编码:100190
电话:010-62661041 传真: Email:csa (a) iscas.ac.cn
技术支持:北京勤云科技发展有限公司

京公网安备 11040202500063号