The deflection self-routing Banyan network: a large-scale ATM switch using the fully adaptive self-routing and its performance analyses
The deflection self-routing Banyan network: a large-scale ATM switch using the fully adaptive self-routing and its performance analyses
复制标题
偏转自路由Banyan网络:采用全自适应自路由的大规模ATM交换机及其性能分析
DOI:
10.1109/90.793032
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发表时间:
1999
期刊:
影响因子:
--
通讯作者:
Heung
中科院分区:
文献类型:
--
作者:
Jae;H. Yoon;Heung
Because the Internet traffic, that will be the major traffic of broadband integrated services digital networks, is bursty when cells are being switched within the multistage switching network, it has a higher possibility that multiple cells arriving simultaneously at a switching element through different incoming links may have to be forwarded along the same outgoing link. We propose a high-performance large-scale ATM switch dealing with such link contention problem. It is a new unbuffered augmented Banyan network using fully adaptive self-routing control: the deflection self-routing Banyan network. To utilize all the links of the network as alternate paths, we employ the deflection-routing algorithm in each switching element, such that cells failing to get selected for the intended link are sent along different links, in the hope that they later return, or detour the contended link and continue their journey to the destination. Cells are never dropped within the switching network, whereas the switch has no multiple cell buffers. The proposed routing is as simple as that of the generic Banyan network, and all the switch elements (SEs) have a uniform structure. To design the proposed network and its self-routing, we use the topological properties that all the SEs of the Banyan network are arranged in a regular pattern topologically. We formulate and prove these properties through an algebraic formalism. We also ran a performance analysis to provide quantitative comparison against the Banyan network and the replicated Banyan networks. As a result, we show that the new network has a far better performance and scalability than the other networks.