An algorithm for finding Hamilton cycles in random graphs
STOC '85 Proceedings of the seventeenth annual ACM symposium on Theory of computing
Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
Algorithms and Complexity
Computational Experience with an Interior Point Algorithm on the Satisfiability Problem
Proceedings of the 1st Integer Programming and Combinatorial Optimization Conference
JCDCG '98 Revised Papers from the Japanese Conference on Discrete and Computational Geometry
Clique is hard to approximate within n1-
FOCS '96 Proceedings of the 37th Annual Symposium on Foundations of Computer Science
Edge coloring, polyhedra and probability
Edge coloring, polyhedra and probability
Impact of interference on multi-hop wireless network performance
Proceedings of the 9th annual international conference on Mobile computing and networking
The impact of imperfect scheduling on cross-layer congestion control in wireless networks
IEEE/ACM Transactions on Networking (TON)
Communication models for throughput optimization in mesh networks
Proceedings of the 5th ACM symposium on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks
Practical computation of optimal schedules in multihop wireless networks
IEEE/ACM Transactions on Networking (TON)
Communication models for throughput optimization in mesh networks
Proceedings of the 5th ACM symposium on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks
Sarnoff'10 Proceedings of the 33rd IEEE conference on Sarnoff
Practical computation of optimal schedules in multihop wireless networks
IEEE/ACM Transactions on Networking (TON)
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It is well known that the maximum weighted independent set (MWIS) problem is NP-complete. Moreover, optimal scheduling in wireless networks requires solving a MWIS problem. Consequently, it is widely believed that optimal scheduling cannot be solved in practical networks. However, there are many cases where there is a significant difference between worst-case complexity and practical complexity. This paper examines the practical complexity of the MWIS problem through extensive computational experimentation. In all, over 10000 topologies are examined. It is found that the MWIS problem can be solved quickly, for example, for a 2048 node topology, it can be solved in approximately one second. Moreover, it appears that the average computational complexity grows polynomially with the number of nodes and linearly with the mean degree of the conflict graph.