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Truthful unsplittable flow for large capacity networks

机译:大容量网络的真实不可分割的流量

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摘要

The unsplittable flow problem is one of the most extensively studied optimization problems in the field of networking. An instance of it consists of an edge capacitated graph and a set of connection requests, each of which is associated with source and target vertices, a demand, and a value. The objective is to route a maximum value subset of requests subject to the edge capacities. It is a well known fact that as the capacities of the edges are larger with respect to the maximal demand among the requests, the problem can be approximated better. In particular, it is known that for sufficiently large capacities, the integrality gap of the corresponding integer linear program becomes 1 + ε, which can be matched by an algorithm that utilizes the randomized rounding technique. In this article, we focus our attention on the large capacities unsplittable flow problem in a game theoretic setting. In this setting, there are selfish agents, which control some of the requests characteristics, and may be dishonest about them. It is worth noting that in game theoretic settings many standard techniques, such as randomized rounding, violate certain monotonicity properties, which are imperative for truthfulness, and therefore cannot be employed. In light of this state of affairs, we design a monotone deterministic algorithm, which is based on a primal-dual machinery, which attains an approximation ratio of e/e-1, up to a disparity of away. This implies an improvement on the current best truthful mechanism, as well as an improvement on the current best combinatorial algorithm for the problem under consideration. Surprisingly, we demonstrate that any algorithm in the family of reasonable iterative path minimizing algorithms, cannot yield a better approximation ratio. Consequently, it follows that in order to achieve a monotone PTAS, if that exists, one would have to exert different techniques. We also consider the large capacities single-minded multi-unit combinatorial auction problem. This problem is closely related to the unsplittable flow problem since one can formulate it as a special case of the integer linear program of the unsplittable flow problem. Accordingly, we obtain a comparable performance guarantee by refining the algorithm suggested for the unsplittable flow problem.
机译:不可分割的流量问题是网络领域中研究最广泛的优化问题之一。它的一个实例由一个边缘限制图和一组连接请求组成,每个连接请求都与源和目标顶点,需求和值相关联。目的是根据边缘容量路由请求的最大值子集。众所周知的事实是,当相对于请求中的最大需求而言,边缘的容量更大时,可以更好地近似该问题。特别是,已知对于足够大的容量,相应的整数线性程序的积分间隙变为1 +ε,可以通过利用随机舍入技术的算法进行匹配。在本文中,我们将注意力集中在博弈论背景下的大容量不可拆分流问题上。在这种情况下,存在自私的代理,它们控制某些请求特征,并且可能对此不诚实。值得注意的是,在游戏理论设置中,许多标准技术(例如随机取整)违反了某些单调性,这对于真实性是必不可少的,因此不能使用。鉴于这种情况,我们设计了一种基于单对偶机制的单调确定性算法,该算法达到e / e-1的近似比率,相距不远。这意味着对当前最佳诚实机制的改进,以及对所考虑问题的当前最佳组合算法的改进。令人惊讶地,我们证明了合理的迭代路径最小化算法家族中的任何算法都无法产生更好的近似率。因此,随之而来的是,为了实现单调PTAS(如果存在的话),人们将不得不运用不同的技术。我们还考虑了大容量单心多单元组合拍卖问题。这个问题与不可分裂流动问题密切相关,因为可以将其表述为不可分裂流动问题的整数线性程序的一种特殊情况。因此,通过改进针对不可分裂流动问题建议的算法,我们获得了可比的性能保证。

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