基于生物吸引子选择的WDM网状网络流量疏导的自适应意向连接重路由

Yan Li, Jianping Wang, Yun Xu
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引用次数: 7

摘要

在波分复用(WDM)网状网络中,一个波长可以提供的高带宽与单个连接的相对低带宽请求之间的不匹配限制了波长的利用。将多个连接训练到一个波长上的流量疏导是提高资源利用率的理想技术。然而,由于不可预测的流量需求,新到达的请求可能无法使用剩余的资源来容纳。重路由是一种进一步提高网络吞吐量的有效方法,它重新路由现有的连接,以便容纳新到达的请求。本文研究了自适应有意识的连接重路由,它根据网络状态有意识地触发重路由算法,目的是为未来的连接保留最大的资源。在有意重路由方案中有两个重要的问题:何时触发重路由算法和对所容纳的连接进行重路由的规则。问题的答案可以在适当的重路由数量内降低网络阻塞概率。在本文中,我们建议使用生物吸引子选择方法来解决上述问题,以便在适当的时间进行重新路由以适应不可预测的交通需求。该重路由方案具有良好的自适应性,提高了系统的鲁棒性。仿真结果验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive intentional connection rerouting for traffic grooming in WDM mesh networks with biological attractor selection
In wavelength division multiplexing (WDM) mesh networks, wavelength utilization is limited by the mismatch between the high bandwidth that one wavelength can provide and the relatively low bandwidth request of a single connection. Traffic grooming which grooms multiple connections onto one wavelength is a desirable technique to improve resource utilization. However, with unpredictable traffic demand, the newly arrived request may not be accommodated using remaining resources. Rerouting which reroutes existing connections such that the newly arrived request can be accommodated is an effective approach to further improve network throughput. In this paper, we study adaptive intentional connection rerouting which intentionally triggers rerouting algorithm according to network status, with the aim to reserve maximum resources for future connections. There are two important issues in intentional rerouting scheme: when to trigger rerouting algorithm and the rule to reroute the accommodated connections. The answers to the questions can reduce network blocking probability within an appropriate number of rerouting. In this paper, we propose to use biological attractor selection approach to address the above issues so that rerouting can be performed at the right time to accommodate unpredictable traffic demand. The proposed rerouting scheme can also improve system robustness given its adaptability. The simulations demonstrate the effectiveness of our proposed adaptive rerouting approach.
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