Parallel and distributed computation: numerical methods
Parallel and distributed computation: numerical methods
Dynamic load balancing for distributed memory multiprocessors
Journal of Parallel and Distributed Computing
Analysis of a graph coloring based distributed load balancing algorithm
Journal of Parallel and Distributed Computing
Load balancing and Poisson equation in a graph
Concurrency: Practice and Experience
Journal of the ACM (JACM)
A combinatorial treatment of balancing networks
Journal of the ACM (JACM)
The art of computer programming, volume 3: (2nd ed.) sorting and searching
The art of computer programming, volume 3: (2nd ed.) sorting and searching
Local Divergence of Markov Chains and the Analysis of Iterative Load-Balancing Schemes
FOCS '98 Proceedings of the 39th Annual Symposium on Foundations of Computer Science
Counting networks with arbitrary fan-out
Distributed Computing
A delay-based dynamic load balancing method and its stability analysis and simulation
EuroPar'10 Proceedings of the 16th international Euro-Par conference on Parallel processing: Part I
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We investigate the following very simple load-balancing algorithm on the N-cycle (N even) which we call Odd-Even Transposition Balancing (OETB). The edges of the cycle are partitioned into two matchings canonically. A matching defines a single step, the two matchings form a single round. Processors connected by an edge of the matching perfectly balance their loads, and, if there is an excess token, it is sent to the lower-numbered processor. The difference between the real process where the tokens are assumed integral and the idealized process where the tokens are assumed divisible can be expressed in terms of the local divergence [1]. We show that Odd-Even Transposition Balancing has a local divergence of N/2 -1. Combining this with previous results, this shows that after O(N2 log(KN)) rounds, any input sequence with initial imbalance K is perfectly balanced. Experiments are presented that show that the number of rounds necessary to perfectly balance a load sequence with imbalance K that has been obtained by pre-balancing a random sequence with much larger imbalance is significally larger than the average number of rounds necessary for balancing random sequences with imbalance K.