T. Kitani, Masataka Yonedu, N. Funabiki, Tom Nakanishi, K. Okayama, T. Higashino
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引用次数: 5
摘要
波分复用(Wavelength Division Multiplexing, WDM)技术通过在一根光纤上实现不同波长的多个通信通道,提供了一种宽带通信网络。在这种技术中,每个节点(波长路由器)都有有限数量的发射器/接收器处理不同的波长,其中每个波长专门用于特定节点对之间的通信通道。因此,一些传输请求可能需要多个波长在到达目的地之前经过多个节点。因此,在基于wdm的网络中,节点的波长分配对于有效传输至关重要。在常规波长分配拓扑中,双向曼哈顿街网络(BMSN)为基于wdm的网络提供了高性能。本文提出了一种两阶段启发式的BMSN波长分配算法,称为HIWAS (HIerarchical wavelength assignment algorithm for BMSN)。第一阶段分层寻找初始波长分配,既能最大限度地避免局部最小值,又能降低时间复杂度。第二阶段采用模拟退火技术改进波长分配。通过求解两类随机实例验证了HIWAS算法的性能,在这两类随机实例中,HIWAS算法比现有最知名的算法在更短的时间内提供了更好的解决方案。
A two-stage hierarchical algorithm for wavelength assignment in WDM-based Bidirectional Manhattan Street Networks
Wavelength Division Multiplexing (WDM) technology provides a wideband communication networks by realizing multiple communication channels with different wavelengths on a single optical fiber. In this technology, each node (wavelength router) has a finite number of transmitters/receivers dealing with different wavelengths, where each wavelength is exclusively used for the communication channel between a specific pair of nodes. Thus, some transmission request may require multiple wavelengths going through several nodes before reaching its destination. As a result, the wavelength assignment to nodes is very important for efficient transmission in WDM-based networks. Among regular wavelength assignment topologies, Bidirectional Manhattan Street Network (BMSN) gives high performance to WDM-based networks. In this paper, we present a two-stage heuristic algorithm for the wavelength assignment in BMSN, called a HIWAS (HIerarchical Wavelength ASsignment algorithm for BMSN). The first stage of HIWAS finds an initial wavelength assignment hierarchically, not only to avoid a local minimum as best as possible but also to reduce the time complexity. The second stage improves the wavelength assignment by adopting the simulated annealing. The performance of HIWAS is verified through solving two types of random instances, where HIWAS provides a better solution with a shorter time than the bestknown existing algorithm.