Question

求高手帮我翻译下面一小段外文

6. Conclusions and future work
In this paper we discussed design concepts of CAC for both QoS satisfaction and reward optimization and developed and analyzed elastic threshold-based CAC for serving multiple service classes in mobile wireless networks. We compared the performance of elastic threshold-based CAC with existing CAC algorithms in solution optimality. We presented a greedy search algorithm that determines a near optimal solution for elastic threshold-based CAC. We discovered that partitioning CAC performs poorly among all. Threshold-based and spillover CAC algorithms perform reasonably well when the mobile user population is moderate However, as the user population increases and thus the aggregate traffic increases, they fail to generate a legitimate solution to satisfy QoS constraints of service classes.
不要就拿翻译器翻译一下，外文翻译是毕业设计的一部分，随便一翻过不了关啊，谢谢！

Answer 1

Conclusions and future work In this paper we discussed design concepts of CAC for both QoS satisfaction and reward optimization and developed and analyzed elastic threshold-based CAC for serving multiple service classes in mobile wireless networks.结论和未来的工作，在本文中，我们讨论了两种优化服务质量满意度和奖励的CAC设计概念和发展，分析了服务于移动无线网络的多个服务类的弹性阈值的基础之CAC。 We compared the performance of elastic threshold-based CAC with existing CAC algorithms in solution optimality.我们比较了弹性基于阈值的最优解成飞与成飞现有算法的性能。 We presented a greedy search algorithm that determines a near optimal solution for elastic threshold-based CAC.我们提出一个贪婪搜索算法，该算法确定弹性阈值附近的成飞最优解。 We discovered that partitioning CAC performs poorly among all.我们发现，分割成飞各性能很差。 Threshold-based and spillover CAC algorithms perform reasonably well when the mobile user population is moderate However, as the user population increases and thus the aggregate traffic increases, they fail to generate a legitimate solution to satisfy QoS constraints of service classes.基于阈值的算法和外溢成飞时表现相当不错的移动用户群是温和的，但随着人口的增加，从而用户总流量的增加，他们不能产生一个合法的解决方案，以满足服务等级的QoS约束。

Answer 2

结论和未来工作。
本文讨论了两种优化服务质量满意度和奖励的CAC设计概念和发展，分析了服务于移动无线网络的多个服务类的弹性阈值的基础之CAC。我们比较了弹性基于阈值的最优解成飞与成飞现有算法的性能。我们提出一个贪婪搜索算法，该算法确定弹性阈值附近的成飞最优解。我们发现，分割成飞各性能很差。基于阈值的算法和外溢成飞时表现相当不错的移动用户群是温和的，但随着人口的增加，从而用户总流量的增加，他们不能产生一个合法的解决方案，以满足服务等级的QoS约束。

Answer 3

6。结论和未来的工作
在讨论计算机辅助控制的总体设计思想对于有保证的服务品质满意度和奖励优化和发达和分析弹性threshold-based CAC为服务多重的服务类在移动无线网络。我们比较了性能threshold-based CAC与现有的弹性算法在溶液中天最优。提出了一种贪婪的搜索算法,决定了接近最优解弹性threshold-based CAC。我们发现,分区CAC经营状况不佳时,在所有。Threshold-based与溢出CAC算法时进行合理人口的移动用户适中然而,当用户人口增加,因此总信息流量增加,他们无法产生一个合理的解决方案,以满足约束下的质量服务类。

Answer 4

结论和未来工作这篇论文我们讨论中艺的设计概念对两服务质量满意和报酬优化，开发，分析弹threshold-based中艺为服务多种服务类在移动无线网络。我们比较弹的性能threshold-ba