首页> 外文期刊>Computer networks >A taxonomy of biologically inspired research in computer networking
【24h】

A taxonomy of biologically inspired research in computer networking

机译:计算机网络中受生物学启发的研究的分类

获取原文
获取原文并翻译 | 示例
           

摘要

The natural world is enormous, dynamic, incredibly diverse, and highly complex. Despite the inherent challenges of surviving in such a world, biological organisms evolve, self-organize, self-repair, navigate, and flourish. Generally, they do so with only local knowledge and without any centralized control. Our computer networks are increasingly facing similar challenges as they grow larger in size, but are yet to be able to achieve the same level of robustness and adaptability. Many research efforts have recognized these parallels, and wondered if there are some lessons to be learned from biological systems. As a result, biologically inspired research in computer networking is a quickly growing field. This article begins by exploring why biology and computer network research are such a natural match. We then present a broad overview of biologically inspired research, grouped by topic, and classified in two ways: by the biological field that inspired each topic, and by the area of networking in which the topic lies. In each case, we elucidate how biological concepts have been most successfully applied. In aggregate, we conclude that research efforts are most successful when they separate biological design from biological implementation - that is to say, when they extract the pertinent principles from the former without imposing the limitations of the latter.
机译:自然世界是巨大的,动态的,令人难以置信的多样且高度复杂。尽管在这样的世界中生存存在固有的挑战,但生物有机体仍在进化,自我组织,自我修复,航行并蓬勃发展。通常,他们这样做仅凭本地知识,而没有任何集中控制。随着计算机网络规模的不断扩大,我们的计算机网络也日益面临类似的挑战,但仍无法达到相同水平的鲁棒性和适应性。许多研究工作已经认识到了这些相似之处,并且想知道是否有一些教训可以从生物系统中学到。结果,在计算机网络中受到生物学启发的研究是一个快速发展的领域。本文首先探讨了为什么生物学和计算机网络研究如此自然地匹配。然后,我们按主题将生物启发性研究进行概述,并按两种方式进行分类:按启发每个主题的生物学领域以及按主题所在的网络领域。在每种情况下,我们都会阐明如何最成功地应用生物学概念。总的来说,我们得出的结论是,当研究工作将生物学设计与生物学实施分开时,即当他们从前者中提取相关原理而不施加后者的局限性时,研究工作才是最成功的。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号