计算机应用 ›› 2010, Vol. 30 ›› Issue (07): 1711-1713.

• 网络与通信 •    下一篇

面向稳定性的基于权值的车辆自组网分簇算法——SWBCA

林磊1,肖晓强2,徐明2,魏李琦3   

  1. 1. 国防科学技术大学
    2. 国防科学技术大学计算机学院
    3.
  • 收稿日期:2010-01-21 修回日期:2010-03-09 发布日期:2010-07-01 出版日期:2010-07-01
  • 通讯作者: 林磊
  • 基金资助:
    国家自然科学基金资助项目

SWBCA: Stability-oriented weight-based clustering algorithm for VANETs

  • Received:2010-01-21 Revised:2010-03-09 Online:2010-07-01 Published:2010-07-01
  • Contact: Lei Lin

摘要: 分簇技术是提高无线自组网性能的关键技术之一,增强分簇算法的稳定性即减少簇结构的变化可以有效降低其维护开销。针对车辆自组网的特点,提出了一种面向稳定性的基于权值的车辆自组网分簇算法——SWBCA。该算法使用车辆节点的度数与理想度数的差值以及车辆节点相对于邻居节点的移动性两个指标计算车辆节点的综合权值进而选举簇头,并使用蒙特卡洛思想对簇的维护过程进行优化来提高稳定性。通过NS2模拟实验表明,SWBCA算法较其他算法具有较强的稳定性,并能有效改善车辆自组网的广播性能。

关键词: 车辆自组网, 稳定性, 基于权值的分簇算法, 蒙特卡洛优化

Abstract: Clustering is one of the key technologies in improving network performance in Ad Hoc networks. Enhancing the stability of a clustering algorithm can reduce the maintenance overhead. According to the characteristics of vehicular Ad Hoc networks (VANETs), a stabilityoriented weightbased clustering algorithm (SWBCA) was proposed in this paper. SWBCA firstly took account of the relative mobility of nodes and the difference between the degree of each node and the ideal degree value for clusterhead election. Then the clusters maintenance of the algorithm was improved with Monte Carlo optimization. Through simulation with NS2, the SWBCA is proved to be more stable than other algorithms and can help improve broadcast performance.

Key words: Vehicle Ad-Hoc Network (VANET), stability, weight-based clustering algorithm, Monte Carlo optimization