Approximation algorithms for data placement in arbitrary networks
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
Approximation algorithms for data management in networks
Proceedings of the thirteenth annual ACM symposium on Parallel algorithms and architectures
A polylogarithmic approximation of the minimum bisection
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
Haplotype Phasing Using Semidefinite Programming
BIBE '05 Proceedings of the Fifth IEEE Symposium on Bioinformatics and Bioengineering
Ensemble Pruning Via Semi-definite Programming
The Journal of Machine Learning Research
Can ISPS and P2P users cooperate for improved performance?
ACM SIGCOMM Computer Communication Review
SpaseLoc: An Adaptive Subproblem Algorithm for Scalable Wireless Sensor Network Localization
SIAM Journal on Optimization
P4p: provider portal for applications
Proceedings of the ACM SIGCOMM 2008 conference on Data communication
Correlation-Aware Object Placement for Multi-Object Operations
ICDCS '08 Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems
Using semi-definite programming to enhance supertree resolvability
WABI'05 Proceedings of the 5th International conference on Algorithms in Bioinformatics
Real datasets for file-sharing peer-to-peer systems
DASFAA'05 Proceedings of the 10th international conference on Database Systems for Advanced Applications
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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.