Balanced allocations (extended abstract)
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
Randomized algorithms
The art of computer programming, volume 3: (2nd ed.) sorting and searching
The art of computer programming, volume 3: (2nd ed.) sorting and searching
Expected Length of the Longest Probe Sequence in Hash Code Searching
Journal of the ACM (JACM)
Chord: A scalable peer-to-peer lookup service for internet applications
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
Online Perfect Matching and Mobile Computing
WADS '95 Proceedings of the 4th International Workshop on Algorithms and Data Structures
How Asymmetry Helps Load Balancing
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
The power of two choices in randomized load balancing
The power of two choices in randomized load balancing
Geometric generalizations of the power of two choices
Proceedings of the sixteenth annual ACM symposium on Parallelism in algorithms and architectures
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Balanced allocations with heterogenous bins
Proceedings of the nineteenth annual ACM symposium on Parallel algorithms and architectures
Control of Multipath TCP and Optimization of Multipath Routing in the Internet
NET-COOP '09 Proceedings of the 3rd Euro-NF Conference on Network Control and Optimization
Balls into bins with related random choices
Proceedings of the twenty-second annual ACM symposium on Parallelism in algorithms and architectures
A generalization of multiple choice balls-into-bins
Proceedings of the 30th annual ACM SIGACT-SIGOPS symposium on Principles of distributed computing
Balls into bins with related random choices
Journal of Parallel and Distributed Computing
Journal of Parallel and Distributed Computing
Hi-index | 0.00 |
In the standard balls-and-bins model of balanced allocations, m balls are placed sequentially into n bins. Each ball chooses d uniform-random bins and is placed in the least loaded bin. It is well known that when d = logΘ(1) n, after placing m = n balls, the maximum load (number of balls in a bin) is Θ(1) w.h.p. In this paper we show that as long as d = Ω(log n), independent random choices are not necessary to achieve a constant load balance: these choices may be structured in a very general way. Specifically, we allow each ball i to have an associated random set of bins Bi. We require that [Bi] = Ω(log n) and that bins are included in Bi with approximately the same probability; but the distributions of the Bis are otherwise arbitrary, so that there may be correlations in the choice of bins. We show that this model captures structure important to two applications, nearby server selection and load balance in distributed hash tables.