An Effective Routing Algorithm with Chaotic Neurodynamics for Optimizing Communication Networks
An Effective Routing Algorithm with Chaotic Neurodynamics for Optimizing Communication Networks
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DOI：
10.4236/ajor.2012.23042
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发表时间：
2012-09
期刊：
影响因子：
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通讯作者：
T. Kimura;T. Hiraguri;T. Ikeguchi
中科院分区：
文献类型：
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作者：
T. Kimura;T. Hiraguri;T. Ikeguchi
在通信网络中，终端用户之间可靠通信的最大障碍是分组拥塞。已经尝试了许多方法来解决拥塞问题。在这方面，我们提出了一个路由算法与混沌神经动力学。通过利用混沌神经元最重要的不应效应，路由算法表现出比最短路径方法更好的性能。此外，我们还进一步改进了路由算法，结合最短路径和相邻节点的等待时间的信息。我们确认，使用混沌神经动力学的路由算法是最有效的方法，以减轻在通信网络中的数据包拥塞。在以前的工作中，混沌路由算法已被评估为理想的通信网络中，每个节点具有相同的传输能力路由的数据包和相同的缓冲区大小存储的数据包。为了检验混沌路由算法是否实际适用，重要的是在现实条件下评估其性能。2007年，M. Hu等人提出了一种实用的通信网络，其中引入了最大的存储容量和处理能力。New-man等人提出了具有社团结构的无标度网络;这些网络使用最短路径介数有效地从真实的复杂网络中提取社团。此外，无标度网络在真实的复杂网络如协作网络或通信网络中具有共同的结构。因此，在本文中，我们评估的混沌路由算法的通信网络的现实条件。由于有效地缓解了数据包，该路由算法表现出更高的数据包到达率比传统的路由算法。进一步证实了混沌路由算法可以应用于真实的通信网络。
In communication networks, the most significant impediment to reliable communication between end users is the congestion of packets. Many approaches have been tried to resolve the congestion problem. In this regard, we have proposed a routing algorithm with chaotic neurodynamics. By using a refractory effect, which is the most important effect of chaotic neurons, the routing algorithm shows better performance than the shortest path approach. In addition, we have further improved the routing algorithm by combining information of the shortest paths and the waiting times at adjacent nodes. We confirm that the routing algorithm using chaotic neurodynamics is the most effective approach to alleviate congestion of packets in a communication network. In previous works, the chaotic routing algorithm has been evaluated for ideal communication networks in which every node has the same transmission capability for routing the packets and the same buffer size for storing the packets. To check whether the chaotic routing algorithm is practically applicable, it is important to evaluate its performance under realistic conditions. In 2007, M. Hu et al. proposed a practicable communication network in which the largest storage capacity and processing capability were introduced. New-man et al. proposed scale-free networks with community structures; these networks effectively extract communities from the real complex network using the shortest path betweenness. In addition, the scale-free networks have common structures in real complex networks such as collaboration networks or communication networks. Thus, in this paper, we evaluate the chaotic routing algorithm for communication networks to which realistic conditions are introduced. Owing to the effective alleviation of packets, the proposed routing algorithm shows a higher arrival rate of packets than the conventional routing algorithms. Further, we confirmed that the chaotic routing algorithm can possibly be applied to real communication networks.