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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ILOG CPLEX, http://www.ilog.com/products/cplex/
BRITE, http://www.cs.bu.edu/brite/
Aggarwal, V., Feldmann, A., Scheideler, C.: Can ISPs and P2P users cooperate for improved performance. Computer Communication Review 37(3), 29–40 (2007)
Baev, I.D., Rajaraman, R.: Approximation algorithms for data placement in arbitrary networks. In: 12th Annual ACM-SIAM Symposium on Discrete algorithms, pp. 661–670 (2001)
Boutaba, R., Karsten, M., Young, M.: A heuristic for fair correlation-aware resource placement. Technical Report CS-2009-04, University of Waterloo Technical Report (January 2009)
Carter, M., Jin, H., Saunders, M., Ye, Y.: Spaseloc: An adaptive subproblem algorithm for scalable wireless sensor network localization. SIAM Journal on Optimization 17(4), 1102–1128 (2006)
Feige, U., Krauthgamer, R.: A polylogarithmic approximation of the minimum bisection. In: IEEE Symposium on Foundations of Computer Science, pp. 105–115 (2000)
Ghaddar, B., Anjos, M., Liers, F.: A branch-and-cut algorithm based on semidefinite programming for the minimum k-partition problem (2007) (unpub. manuscript)
Goh, S.-T., Kalnis, P., Bakiras, S., Tan, K.-L.: Real datasets for file-sharing peer-to-peer systems. In: Zhou, L.-z., Ooi, B.-C., Meng, X. (eds.) DASFAA 2005. LNCS, vol. 3453, pp. 201–213. Springer, Heidelberg (2005)
P. Heywood. Caching in on p2p, www.lightreading.com/document.asp?doc_id=34399
Kalpakis, K., Namjoshi, P.: Haplotype phasing using semidefinite programming. In: Proc. 5th IEEE Symposium on Bioinformatics and Bioengineering, pp. 145–152 (2005)
Krick, C., Racke, H., Westermann, M.: Approximation algorithms for data management in networks. In: SPAA 2001, pp. 237–246 (2001)
Kulis, B., Surendran, A.C., Platt, J.C.: Fast low-rank semidefinite programming for embedding and clustering. In: 11th Int. Conf. on A.I. and Statistics, pp. 512–521 (2007)
Moran, S., Rao, S., Snir, S.: Using semi-definite programming to enhance supertree resolvability. In: Casadio, R., Myers, G. (eds.) WABI 2005. LNCS (LNBI), vol. 3692, pp. 89–103. Springer, Heidelberg (2005)
Nakata, K., Yamashita, M., Fujisawa, K., Kojima, M.: A parallel primal-dual interior-point method for semidefinite programs using positive definite matrix completion. Parallel Computing 32(1), 24–43 (2006)
Svitkina, Z., Tardos, É.: Min-max multiway cut. In: Jansen, K., Khanna, S., Rolim, J.D.P., Ron, D. (eds.) RANDOM 2004 and APPROX 2004. LNCS, vol. 3122, pp. 207–218. Springer, Heidelberg (2004)
Waxman, B.M.: Routing of multipoint connections. IEEE Journal on Selected Areas in Communications 6(9), 1617–1622 (1988)
Xie, H., Yang, Y.R., Krishnamurthy, A., Liu, Y., Silberschatz, A.: P4P: Provider portal for applications. In: SIGCOMM, pp. 351–362 (2008)
Zhang, Y., Burer, S., Nick Street, W.: Ensemble pruning via semi-definite programming. Journal of Machine Learning Research 7, 1315–1338 (2006)
Zhong, M., Shen, K., Seiferas, J.: Correlation-aware object placement for multi-object operations. In: 28th International Conference on Distributed Computing Systems (ICDCS), pp. 512–521 (2008)
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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
Online ISBN: 978-3-642-02011-7
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