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Load Balancing Under Strict Compatibility Constraints

Author

Listed:
  • Daan Rutten

    (H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

  • Debankur Mukherjee

    (H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

Abstract

Consider a system with N identical single-server queues and a number of task types, where each server is able to process only a small subset of possible task types. Arriving tasks select d ≥ 2 random compatible servers and join the shortest queue among them. The compatibility constraints are captured by a fixed bipartite graph between the servers and the task types. When the graph is complete bipartite, the mean-field approximation is accurate. However, such dense compatibility graphs are infeasible for large-scale implementation. We characterize a class of sparse compatibility graphs for which the mean-field approximation remains valid. For this, we introduce a novel notion, called proportional sparsity , and establish that systems with proportionally sparse compatibility graphs asymptotically match the performance of a fully flexible system. Furthermore, we show that proportionally sparse random compatibility graphs can be constructed, which reduce the server degree almost by a factor N / ln ( N ) compared with the complete bipartite compatibility graph.

Suggested Citation

  • Daan Rutten & Debankur Mukherjee, 2023. "Load Balancing Under Strict Compatibility Constraints," Mathematics of Operations Research, INFORMS, vol. 48(1), pages 227-256, February.
    • Handle: RePEc:inm:ormoor:v:48:y:2023:i:1:p:227-256
    DOI: 10.1287/moor.2022.1258
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