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Ant-Based Topology Convergence Algorithms for Resource Management in VANETs

机译:VANET中用于资源管理的基于蚂蚁的拓扑收敛算法

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摘要

Frequent changes caused by IP-connectivity and user-oriented services in Inter-Vehicular Communication Networks (VCNs) set great challenges to construct reliable, secure and fast converged topology formed by trusted mobile nodes and links. In this paper, based on a new metric for network performance called topology convergence and a new Object-Oriented Management Information Base - active MIB (O:MIB), we propose an ant-based topology convergence algorithm that applies the swarm intelligence metaphor to find the near-optimal converged topology in VCNs which maximizes system performance and guarantee a further sustainable and maintainable system topology to achieve Quality of Service (QoS) and system throughput. This algorithm is essentially a distributed approach in that each node collects information from local neighbor nodes by invoking the methods from each localized O:MIB, through the sending and receiving of ant packets from each active node, to find the appropriate nodes to construct a routing path. Simulation results show this approach can lead to a fast converged topology with regards to multiple optimization objectives, as well as scale to network sizes and service demands.
机译:车辆间通信网络(VCN)中IP连接性和面向用户的服务引起的频繁变化为构建由受信移动节点和链路形成的可靠,安全和快速融合的拓扑结构提出了巨大挑战。在本文中,基于一种称为拓扑收敛的网络性能新指标和一个新的面向对象的管理信息库-主动MIB(O:MIB),我们提出了一种基于蚁群的拓扑收敛算法,该算法应用了群体智能隐喻来查找VCN中接近最佳的融合拓扑,可最大化系统性能并保证进一步的可持续性和可维护性的系统拓扑,以实现服务质量(QoS)和系统吞吐量。该算法本质上是一种分布式方法,其中每个节点通过从每个活动节点发送和接收蚂蚁数据包,从每个本地化的O:MIB调用方法来从本地邻居节点收集信息,以找到合适的节点来构建路由路径。仿真结果表明,该方法可以针对多个优化目标以及网络规模和服务需求的规模实现快速收敛的拓扑。

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