Abstract
The configuration of network resources greatly impacts the communication overhead for data intensive tasks and constitutes a critical problem in the design and maintenance of networks. To address the issue of resource placement, we analyze and implement a semidefinite programming-based heuristic for solving a known NP-complete graph optimization problem called Maximum Size Bounded Capacity Cut. Experimental results for our heuristic demonstrate promising performance on both synthetic and real world data. Next our heuristic is used as a sub-routine to solve another known NP-complete problem called Min-Max Multiway Cut whose traits we adapt to yield a resource placement scheme that exploits correlations between network resources. Our experimental results show that the resulting placement scheme achieves a significant savings in communication overhead.
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Boutaba, R., Karsten, M., Young, M. (2009). A Heuristic for Fair Correlation-Aware Resource Placement. In: Vahrenhold, J. (eds) Experimental Algorithms. SEA 2009. Lecture Notes in Computer Science, vol 5526. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02011-7_10
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DOI: https://doi.org/10.1007/978-3-642-02011-7_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02010-0
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