Cluster Before You Hallucinate: Approximating Node-Capacitated Network Design and Energy Efficient Routing
Ravishankar Krishnaswamy, Viswanath Nagarajan, Kirk Pruhs, Cliff Stein

TL;DR
This paper introduces poly-logarithmic approximation algorithms for node-capacitated network design and energy-efficient routing, addressing both single and multi-commodity demands with capacity violations and novel clustering techniques.
Contribution
It provides the first poly-logarithmic approximation guarantees for node-capacitated network design with new clustering methods and applies these results to energy-efficient virtual circuit routing.
Findings
Achieved $O(\log^2 n)$ approximation for single-commodity demands.
Achieved $O(\log^4 n)$ approximation for multi-commodity demands.
Developed new clustering techniques for demand grouping.
Abstract
We consider the following node-capacitated network design problem. The input is an undirected graph, set of demands, uniform node capacity and arbitrary node costs. The goal is to find a minimum node-cost subgraph that supports all demands concurrently subject to the node capacities. We consider both single and multi-commodity demands, and provide the first poly-logarithmic approximation guarantees. For single-commodity demands (i.e., all request pairs have the same sink node), we obtain an approximation to the cost with an factor violation in node capacities. For multi-commodity demands, we obtain an approximation to the cost with an factor violation in node capacities. We use a variety of techniques, including single-sink confluent flows, low-load set cover, random sampling and cut-sparsification. We also develop new…
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Taxonomy
TopicsComplexity and Algorithms in Graphs · Interconnection Networks and Systems · Advanced Graph Theory Research
