On the Approximability of Some Network Design Problems
被引:23
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作者:
Chuzhoy, Julia
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机构:
MIT, Comp Sci & Artificial Intelligence Lab, Toyota Technol Inst Chicago, Chicago, IL USA
Univ Penn, Philadelphia, PA 19104 USAMIT, Comp Sci & Artificial Intelligence Lab, Toyota Technol Inst Chicago, Chicago, IL USA
Chuzhoy, Julia
[1
,2
]
Gupta, Anupam
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机构:
Carnegie Mellon Univ, Dept Comp Sci, Pittsburgh, PA 15213 USAMIT, Comp Sci & Artificial Intelligence Lab, Toyota Technol Inst Chicago, Chicago, IL USA
Gupta, Anupam
[3
]
Naor, Joseph
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Technion, Dept Comp Sci, Israel Inst Technol, IL-32000 Haifa, IsraelMIT, Comp Sci & Artificial Intelligence Lab, Toyota Technol Inst Chicago, Chicago, IL USA
Naor, Joseph
[4
]
Sinha, Amitabh
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Univ Michigan, Ross Sch Business, Ann Arbor, MI 48109 USAMIT, Comp Sci & Artificial Intelligence Lab, Toyota Technol Inst Chicago, Chicago, IL USA
Sinha, Amitabh
[5
]
机构:
[1] MIT, Comp Sci & Artificial Intelligence Lab, Toyota Technol Inst Chicago, Chicago, IL USA
[2] Univ Penn, Philadelphia, PA 19104 USA
[3] Carnegie Mellon Univ, Dept Comp Sci, Pittsburgh, PA 15213 USA
[4] Technion, Dept Comp Sci, Israel Inst Technol, IL-32000 Haifa, Israel
[5] Univ Michigan, Ross Sch Business, Ann Arbor, MI 48109 USA
Consider the following classical network design problem: a set of terminals T = {t(i)}wishes to send traffic to a root r in an n-node graph G = (V, E). Each terminal t(i) sends d(i) units of traffic and enough bandwidth has to be allocated on the edges to permit this. However, bandwidth on an edge e can only be allocated in integral multiples of some base capacity u(e), and hence provisioning k x u(e) bandwidth on edge e incurs a cost of inverted right perpendicular k inverted left perpendicular times the cost of that edge. The objective is a minimum-cost feasible solution. This is one of many network design problems widely studied where the bandwidth allocation is governed by side constraints: edges can only allow a subset of cables to be purchased on them or certain quality-of-service requirements may have to be met. In this work, we show that this problem and, in fact, several basic problems in this general network design framework cannot be approximated better than Omega( log log n) unless NP subset of DTIME (n(O(log log log n))), where vertical bar V vertical bar = n. In particular, we show that this inapproximability threshold holds for (i) the Priority-Steiner Tree problem, (ii) the (single-sink) Cost-Distance problem, and (iii) the single-sink version of an even more fundamental problem, Fixed Charge Network Flow. Our results provide a further breakthrough in the understanding of the level of complexity of network design problems. These are the first nonconstant hardness results known for all these problems.