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A social-aware routing protocol for opportunistic networks

机译:机会网络的社交感知路由协议

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摘要

Understanding nodes mobility is of fundamental importance for data delivery in opportunistic and intermittently connected networks referred to as Delay Tolerant Networks (DTNs). The analysis of such mobility patterns and the understanding of how mobile nodes interact play a critical role when designing new routing protocols for DTNs. The Cultural Greedy Ant (CGrAnt) protocol is a hybrid Swarm Intelligence-based approach designed to address the routing problem in such dynamic and complex environment. CGrAnt is based on: (1) Cultural Algorithms (CA) and Ant Colony Optimization (ACO) and (2) operational metrics that characterize the opportunistic social connectivity between wireless users. The most promising message forwarders are selected via a greedy transition rule based mainly on local information captured from the DTN environment. Whenever global information is available, it can also be used to support decisions. We compare the performance of CGrAnt with Epidemic, PROPHET, and dLife protocols in two different mobility scenarios under varying networking parameters. Results obtained by the ONE simulator show that CGrAnt achieves a higher message delivery and lower message redundancy than the three protocols in both scenarios. The only exception is in one of the scenarios, when messages have a time to live lower than 900 min, where CGrAnt delivers a bit less messages than dLife, although with a lower message redundancy. (C) 2016 Elsevier Ltd. All rights reserved.
机译:了解节点的移动性对于称为延迟容忍网络(DTN)的机会性和间歇性连接的网络中的数据传递至关重要。在为DTN设计新的路由协议时,对这种移动性模式的分析以及对移动节点如何交互的理解至关重要。文化贪婪蚂蚁(CGrAnt)协议是基于混合群智能的方法,旨在解决这种动态和复杂环境中的路由问题。 CGrAnt基于:(1)文化算法(CA)和蚁群优化(ACO)以及(2)表征无线用户之间机会性社会连通性的操作指标。主要基于从DTN环境中捕获的本地信息,通过贪婪过渡规则选择最有前途的消息转发器。只要有全球信息,它也可以用来支持决策。我们在不同的网络参数下,在两种不同的移动方案中比较了CGrAnt与Epidemic,PROPHET和dLife协议的性能。通过ONE模拟器获得的结果表明,与这两种方案相比,CGrAnt均实现了比三种协议更高的消息传递和更低的消息冗余。唯一的例外是在一种情况下,当消息的生存时间少于900分钟时,尽管消息冗余性较低,但CGrAnt传递的消息少于dLife。 (C)2016 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Expert Systems with Application》 |2016年第7期|351-363|共13页
  • 作者单位

    Fed Univ Technol Parana UTFPR, Grad Program Appl Comp PPGCA, Av Sete Setembro 3165, BR-80230901 Curitiba, Parana, Brazil|Fed Univ Technol Parana UTFPR, Grad Program Elect & Comp Engn CPGEI, Av Sete Setembro 3165, BR-80230901 Curitiba, Parana, Brazil;

    Fed Univ Technol Parana UTFPR, Grad Program Appl Comp PPGCA, Av Sete Setembro 3165, BR-80230901 Curitiba, Parana, Brazil|Fed Univ Technol Parana UTFPR, Grad Program Elect & Comp Engn CPGEI, Av Sete Setembro 3165, BR-80230901 Curitiba, Parana, Brazil;

    Fed Univ Technol Parana UTFPR, Grad Program Appl Comp PPGCA, Av Sete Setembro 3165, BR-80230901 Curitiba, Parana, Brazil|Fed Univ Technol Parana UTFPR, Grad Program Elect & Comp Engn CPGEI, Av Sete Setembro 3165, BR-80230901 Curitiba, Parana, Brazil;

    Fed Univ Technol Parana UTFPR, Grad Program Appl Comp PPGCA, Av Sete Setembro 3165, BR-80230901 Curitiba, Parana, Brazil|Fed Univ Technol Parana UTFPR, Grad Program Elect & Comp Engn CPGEI, Av Sete Setembro 3165, BR-80230901 Curitiba, Parana, Brazil;

    Inst Natl Rech Informat & Automat INRIA Saclay Il, 4 Rue Jacques Monod, F-91893 Orsay, France;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Cultural algorithms; Ant colony optimization; Social analysis; Routing protocol; Intermittently connected networks;

    机译:文化算法;蚁群优化;社会分析;路由协议;间歇性连接网络;

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