Efficient algorithms for delay-bounded minimum cost path problem in communication networks

G. Kumar, Nishit Narang, C. Ravikumar
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引用次数: 9

Abstract

As the amount of data transmitted over a network increases and high bandwidth applications requiring point to multipoint communications like videoconferencing, distributed database management or cooperative work become widespread, it becomes very important to optimize network resources. One such optimization is multicast tree generation. The problem of generating a minimum cost multicast tree given the network topology and costs associated with the connecting links can be modelled as a Steiner tree problem which is NP-complete. Much work has been done in the direction of obtaining near-optimal multicast trees when the objective is only to minimize the cost. However, many real time applications such as videoconferencing require that data be sent within prespecified delay limits in order to avoid problems such as anachronism and lack of synchronization. We deal with the delay-bounded cost-optimal multicast tree (DBCPAT) generation problem. Specifically, we discuss a closely related problem which is to find a delay-bounded cost-optimal path (DBCP) between a specified source and destination node. Such a path can be used as a starting point to solve the DBCMT. We present an exact solution to the DBCP which is based on the branch-and-bound paradigm. We also propose a heuristic technique to solve the DBCP using the principle of evolutionary computing. The results obtained using the two techniques are compared for several large networks.
通信网络延迟有界最小代价路径问题的有效算法
随着通过网络传输的数据量的增加和需要点对多点通信的高带宽应用(如视频会议、分布式数据库管理或协同工作)的普及,优化网络资源变得非常重要。其中一种优化是组播树生成。在给定网络拓扑和连接链路相关代价的情况下,生成最小代价组播树的问题可以建模为np完全的斯坦纳树问题。当目标只是最小化成本时,在获得接近最优组播树的方向上已经做了很多工作。然而,许多实时应用程序(如视频会议)要求在预先指定的延迟限制内发送数据,以避免诸如时间错误和缺乏同步等问题。研究了延迟有界成本最优组播树(DBCPAT)的生成问题。具体来说,我们讨论了一个密切相关的问题,即在指定的源节点和目标节点之间找到延迟有界的成本最优路径(DBCP)。这样的路径可以作为求解DBCMT的起点。我们提出了一个基于分支定界范式的DBCP的精确解。我们还提出了一种利用进化计算原理求解DBCP的启发式技术。在几个大型网络中比较了两种方法的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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