MON：任务优化覆盖网络
MON: Mission-optimized Overlay Networks
摘要：
大型组织通常在通过Internet连接的多个站点中拥有用户。由于资源有限，这些站点之间的通信需要精心安排，以便为组织带来最大利益。我们提出了一个任务优化的覆盖网络（MON），一个混合的覆盖网络架构，最大限度地提高效用的组织。我们结合了离线和在线系统来解决非凹效用最大化问题。离线层，预测流优化器（PFO），使用网络条件模型创建路由流量的计划。在线层MONtra能够准确了解本地网络状况，并能够对网络中的问题做出快速反应。单靠这两个层次是不够的。PFO可能需要太长时间才能对网络更改做出反应。MONtra仅具有本地信息，不能优化非凹任务效用。然而，通过结合这两个系统，MON是强大的，并在广泛的网络条件下实现接近最佳的效用。虽然尽力而为的覆盖网络得到了很好的研究，我们的工作是第一个设计的任务效用优化的覆盖。
英文摘要：
Large organizations often have users in multiple sites which are connected over the Internet. Since resources are limited, communication between these sites needs to be carefully orchestrated for the most benefit to the organization. We present a Mission-optimized Overlay Network (MON), a hybrid overlay network architecture for maximizing utility to the organization. We combine an offline and an online system to solve non-concave utility maximization problems. The offline tier, the Predictive Flow Optimizer (PFO), creates plans for routing traffic using a model of network conditions. The online tier, MONtra, is aware of the precise local network conditions and is able to react quickly to problems within the network. Either tier alone is insufficient. The PFO may take too long to react to network changes. MONtra only has local information and cannot optimize non-concave mission utilities. However, by combining the two systems, MON is robust and achieves near-optimal utility under a wide range of network conditions. While best-effort overlay networks are well studied, our work is the first to design overlays that are optimized for mission utility.
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