A hierarchical optimized QoS ant colony algorithm for Ad hoc networks

Zhong Liquan; Meng Lilin; Ke Bing; Shao Ruirui

doi:10.13756/j.gtxyj.2014.04.010

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A hierarchical optimized QoS ant colony algorithm for Ad hoc networks

- A hierarchical optimized QoS ant colony algorithm for Ad hoc networks
- Study on Optical communication Issue 4, Pages: 31-33(2014)
- 作者机构：
  
  1. 西安邮电大学电子工程学院
  2. 中国航天科工集团第二研究院
- 作者简介：
- 基金信息：
- DOI：10.13756/j.gtxyj.2014.04.010
  CLC： TN929.5
- Published：2014，
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[1]钟李全,孟李林,柯冰,邵瑞瑞.基于分级结构的优化QoS路由算法[J].光通信研究,2014(04):31-33+39.

Zhong Liquan, Meng Lilin, Ke Bing, et al. A hierarchical optimized QoS ant colony algorithm for Ad hoc networks. [J]. (4):31-33(2014)
[1]钟李全,孟李林,柯冰,邵瑞瑞.基于分级结构的优化QoS路由算法[J].光通信研究,2014(04):31-33+39. DOI： 10.13756/j.gtxyj.2014.04.010.

Zhong Liquan, Meng Lilin, Ke Bing, et al. A hierarchical optimized QoS ant colony algorithm for Ad hoc networks. [J]. (4):31-33(2014) DOI： 10.13756/j.gtxyj.2014.04.010.

摘要

Ad hoc（自组织）网络中包含延迟、延迟抖动、带宽和丢包率等约束条件在内的QoS（服务质量）路由问题

是一个NP完全问题

传统的平面QoS蚂蚁路由算法难以解决提高算法全局搜索能力和加快收敛速度之间的矛盾。针对以上问题

提出了HQAC（分级QoS蚁群）算法

在分级的基础上对蚁群算法的路由搜寻过程进行了改进

同时对信息素更新公式进行了优化。仿真结果表明

与传统的QoS路由算法相比

HQAC算法在搜索全局最优解

尤其是收敛速度等性能上有了很大的提高。

Abstract

QoS routing problem in Ad hoc networks including such constraints as delay

delay jitter

bandwidth and packet loss is an NP-complete problem.It is difficult for the traditional plane QoS ant routing algorithm to solve the contradiction between improving the global search ability of the algorithm and speeding up the convergence rate.In relation to the above problem

this paper presents a Hierarchical QoS Ant Colony（HQAC）algorithm.On the basis of the hierarchical structure

it improves the routing search process of the algorithm and optimizes the pheromone update formula.Simulation results show that compared with the traditional QoS routing algorithms

this algorithm is remarkably improved in searching the global optimal solution

especially in convergence rate and other performances.

关键词

自组织网络蚁群算法分级QoS蚁群算法信息素

Keywords

Ad hoc networkant colony algorithmHQAC algorithmpheromone

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School of Electrical & Electronic Engineering,North China Electric Power University

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江苏大学计算机科学与通信工程学院江苏镇江　212013

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