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Resource Allocation in Bounded Degree Trees

机译:有界度树中的资源分配

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We study the bandwidth allocation problem (bap) in bounded degree trees. In this problem we are given a tree and a set of connection requests. Each request consists of a path in the tree, a bandwidth requirement, and a weight. Our goal is to find a maximum weight subset S of requests such that, for every edge e, the total bandwidth of requests in S whose path contains e is at most 1. We also consider the storage allocation problem (sap), in which it is also required that every request in the solution is given the same contiguous portion of the resource in every edge in its path. We present a deterministic approximation algorithm for bap in bounded degree trees with ratio (2Öe-1)/(Öe-1)+e < 3.542(2sqrt{e}-1)/(sqrt{e}-1)+varepsilon<3.542 . Our algorithm is based on a novel application of the local ratio technique in which the available bandwidth is divided into narrow strips and requests with very small bandwidths are allocated in these strips. We also present a randomized (2+ε)-approximation algorithm for bap in bounded degree trees. The best previously known ratio for bap in general trees is 5. We present a reduction from sap to bap that works for instances where the tree is a line and the bandwidths are very small. It follows that there exists a deterministic 2.582-approximation algorithm and a randomized (2+ε)-approximation algorithm for sap in the line. The best previously known ratio for this problem is 7.
机译:我们研究有界度树中的带宽分配问题。在这个问题中,我们得到了一棵树和一组连接请求。每个请求均包含树中的路径,带宽要求和权重。我们的目标是找到请求的最大权重子集S,以便对于每个边缘e,路径中包含e的S中的请求的总带宽最多为1。我们还考虑了存储分配问题(sap),其中还要求解决方案中的每个请求在其路径的每个边缘都被赋予资源相同的连续部分。我们提出了比率为(2Öe-1)/(Öe-1)+ e <3.542(2sqrt {e} -1)/(sqrt {e} -1)/ varepsilon <3.542的有界树中bap的确定性近似算法。我们的算法基于局部比率技术的新颖应用,其中将可用带宽划分为窄带,并在这些带中分配带宽非常小的请求。我们还提出了有界度树中bap的随机(2 +ε)-近似算法。以前在一般树中,bap的最佳比率是5。我们提出了从sap到bap的降低,这种情况适用于树是线且带宽很小的情况。因此,该行中存在针对液汁的确定性2.582近似算法和随机(2 +ε)近似算法。以前对此问题最好的比率是7。

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