在线VNF链接与预测调度：最优性与权衡
Online VNF Chaining and Predictive Scheduling: Optimality and Trade-offs
摘要：
对于NFV系统，关键设计空间包括网络请求的功能链接和服务器的资源调度。这个问题是具有挑战性的，因为NFV系统通常需要多个（往往是冲突的）设计目标和计算效率的实时决策有限的信息。此外，预测调度对NFV系统的好处仍然未被探索。在本文中，我们提出了POSCARS，一个有效的预测和在线服务链和资源调度方案，实现可调的各种系统指标之间的权衡与队列稳定性保证。通过在系统建模中仔细选择粒度，我们可以更好地理解设计空间中的权衡。通过一个非平凡的转换，我们将复杂的优化问题解耦成一系列的在线子问题，以实现最优只有有限的信息。通过采用随机负载均衡技术，我们提出了三种变体的POSCARS，以减少决策的开销。理论分析和仿真结果表明，POSCARS及其变种只需要未来信息的温和价值，以实现接近最优的系统成本与超低的请求响应时间。
英文摘要：
For NFV systems, the key design space includes the function chaining for network requests and resource scheduling for servers. The problem is challenging since NFV systems usually require multiple (often conflicting) design objectives and the computational efficiency of real-time decision making with limited information. Furthermore, the benefits of predictive scheduling to NFV systems still remain unexplored. In this paper, we propose POSCARS, an efficient predictive and online service chaining and resource scheduling scheme that achieves tunable trade-offs among various system metrics with queue stability guarantee. Through a careful choice of granularity in system modeling, we acquire a better understanding of the trade-offs in our design space. By a non-trivial transformation, we decouple the complex optimization problem into a series of online sub-problems to achieve the optimality with only limited information. By employing randomized load balancing techniques, we propose three variants of POSCARS to reduce the overheads of decision making. Theoretical analysis and simulations show that POSCARS and its variants require only mild-value of future information to achieve near-optimal system cost with an ultra-low request response time.
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