Dynamic load balancing for distributed memory multiprocessors
Journal of Parallel and Distributed Computing
An analysis of diffusive load-balancing
SPAA '94 Proceedings of the sixth annual ACM symposium on Parallel algorithms and architectures
An analytical comparison of nearest neighbor algorithms for load balancing in parallel computers
IPPS '95 Proceedings of the 9th International Symposium on Parallel Processing
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
Polynomial real root isolation using Descarte's rule of signs
SYMSAC '76 Proceedings of the third ACM symposium on Symbolic and algebraic computation
Simulating a Random Walk with Constant Error
Combinatorics, Probability and Computing
Memory Efficient Anonymous Graph Exploration
Graph-Theoretic Concepts in Computer Science
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Deterministic and randomized balancing schemes are used to distribute workload evenly in networks. In this paper, we compare two very general ones: The random walk and the (deterministic) Propp machine. Roughly speaking, we show that on the two-dimensional grid, the Propp machine always has the same number of tokens on a node as does the random walk in expectation, apart from an additive error of less than eight. This constant is independent of the total number of tokens and the runtime of the two processes. However, we also show that it makes a difference whether the Propp machine serves the neighbors in a circular or non-circular order.