Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
The competitiveness of on-line assignments
SODA '92 Proceedings of the third annual ACM-SIAM symposium on Discrete algorithms
Theoretical Computer Science - Special issue on dynamic and on-line algorithms
An efficient cost scaling algorithm for the assignment problem
Mathematical Programming: Series A and B
Augment or push: a computational study of bipartite matching and unit-capacity flow algorithms
Journal of Experimental Algorithmics (JEA)
LEDA: a platform for combinatorial and geometric computing
LEDA: a platform for combinatorial and geometric computing
Scheduling independent tasks to reduce mean finishing time
Communications of the ACM
Introduction to Algorithms
Load balancing in the L/sub p/ norm
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Aggregation convergecast scheduling in wireless sensor networks
Wireless Networks
Online scheduling of two job types on a set of multipurpose machines with unit processing times
Computers and Operations Research
Scheduling unit length jobs on parallel machines with lookahead information
Journal of Scheduling
Brief announcement: distributed approximations for the semi-matching problem
DISC'11 Proceedings of the 25th international conference on Distributed computing
Discrete Applied Mathematics
On computing an optimal semi-matching
WG'11 Proceedings of the 37th international conference on Graph-Theoretic Concepts in Computer Science
Distributed 2-approximation algorithm for the semi-matching problem
DISC'12 Proceedings of the 26th international conference on Distributed Computing
ACM Computing Surveys (CSUR)
Exploiting locality in distributed SDN control
Proceedings of the second ACM SIGCOMM workshop on Hot topics in software defined networking
Matching with sizes (or scheduling with processing set restrictions)
Discrete Applied Mathematics
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We consider the problem of fairly matching the left-hand vertices of a bipartite graph to the right-hand vertices. We refer to this problem as the optimal semi-matching problem; it is a relaxation of the known bipartite matching problem. We present a way to evaluate the quality of a given semi-matching and show that, under this measure, an optimal semi-matching balances the load on the right-hand vertices with respect to any L"p-norm. In particular, when modeling a job assignment system, an optimal semi-matching achieves the minimal makespan and the minimal flow time for the system. The problem of finding optimal semi-matchings is a special case of certain scheduling problems for which known solutions exist. However, these known solutions are based on general network optimization algorithms, and are not the most efficient way to solve the optimal semi-matching problem. To compute optimal semi-matchings efficiently, we present and analyze two new algorithms. The first algorithm generalizes the Hungarian method for computing maximum bipartite matchings, while the second, more efficient algorithm is based on a new notion of cost-reducing paths. Our experimental results demonstrate that the second algorithm is vastly superior to using known network optimization algorithms to solve the optimal semi-matching problem. Furthermore, this same algorithm can also be used to find maximum bipartite matchings and is shown to be roughly as efficient as the best known algorithms for this goal.