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提出了一种性能可以调节的组播树生成算法 .这种算法提供了一个调节参数κ ,即每次随机选择的端节点的个数 .通过改变参数κ ,可在组播树的费用和运行时间之间进行权衡选择 ,以适应不同应用场合的需要 .为了仿真 ,还提出了一种使节点平均点度非常精确的随机网络产生方法 .分析和仿真结果表明 ,只用较小的κ值就可得到较为理想的组播树费用 ,同时算法能保持较高的计算效率 .与算法SCTF (SelectiveClosestTerminalFirst)相比 ,在计算效率相同时 ,本算法费用值更低 .
A performance-adjustable multicast tree generation algorithm is proposed, which provides an adjustment parameter κ, which is the number of end nodes randomly selected each time. By changing the parameter κ, the cost and operation of the multicast tree Time to choose between trade-offs to meet the needs of different applications.In order to simulate, a method of random network generation is proposed to make the average point degree of the nodes very accurate.The analysis and simulation results show that with only small κ The cost of the multicast tree can be better, while the algorithm can maintain a higher computational efficiency.Compared with the algorithm of SCTF (SelectiveClosestTerminalFirst), the algorithm cost is lower when the computational efficiency is the same.