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Optimizing resource utilization in NFV dynamic systems: New exact and heuristic approaches

机译:在NFV动态系统中优化资源利用:新的精确和启发式方法

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Network Function Virtualization (NFV) orchestration and management have attracted a lot of attention in recent years as it provides new opportunities regarding performance and deployment. In particular, several models have attempted to capture the behavior of such systems under various restricted assumptions. However, previously proposed mathematical models can only handle problems of fairly small size. This paper proposes a Mixed Integer Linear Programming (MILP) model for the resource utilization problem in an NFV dynamic context with several enhancements regarding the state of the art. We include the utilization of flow constraints to ensure the order of functions in a service chain. By systematic generation of Flow Cover inequalities, significant improvements in processing time are obtained with a standard MILP solver to compute exact optimal solutions. We also propose three efficient heuristics (two MILP-based heuristics) to find high-quality feasible solutions for large-scale systems within reduced execution time. We also carry out a set of experiments to evaluate the proposed algorithms and provide valuable guidelines for the efficient design of such systems. The results show that our approach is capable of handling large size instances of the NFV deployment problem involving up to 200 nodes and 100 demands. (C) 2018 Elsevier B.V. All rights reserved.
机译:近年来,网络功能虚拟化(NFV)的编排和管理吸引了很多关注,因为它为性能和部署提供了新的机会。特别地,几种模型试图在各种受限的假设下捕获此类系统的行为。但是,先前提出的数学模型只能处理较小尺寸的问题。本文针对NFV动态环境中的资源利用问题提出了一种混合整数线性规划(MILP)模型,并对现有技术进行了一些改进。我们包括利用流约束来确保服务链中功能的顺序。通过系统生成Flow Cover不等式,使用标准的MILP求解器可以计算出最佳的解决方案,从而大大缩短了处理时间。我们还提出了三种有效的启发式方法(两种基于MILP的启发式方法),以在减少的执行时间内为大型系统找到高质量的可行解决方案。我们还进行了一组实验,以评估提出的算法,并为有效设计此类系统提供有价值的指导。结果表明,我们的方法能够处理涉及多达200个节点和100个需求的NFV部署问题的大型实例。 (C)2018 Elsevier B.V.保留所有权利。

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