Abstract

We investigate decentralized gradient descent (DGD) with emphasis on efficient communication and computation resource utilization under budget constraints. As a first step toward the broader communication-computation allocation problem, we consider and analyze a \textit{multi-consensus decentralized gradient descent} (mcDGD) scheme, where the number of consensus rounds and the stepsize are allowed to vary across iterations. Building on a unified analytical framework for DGD, we derive finite-time convergence bounds that explicitly characterize the interaction between consensus quality and optimization dynamics. Our analysis requires only convexity of the local objective functions while assuming smoothness and strong convexity of the global objective. The resulting bounds enable a principled consensus-allocation strategy under resource constraints, for which we show that equal allocation of consensus rounds across iterations is optimal under our stepsize rule, up to integer rounding. Numerical experiments corroborate the theoretical findings and demonstrate favorable communication-computation tradeoffs compared with existing multi-consensus decentralized optimization baselines.

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Open access
Green open access

Cite this article

APA 7

Ren, S., Michelusi, N., & Larsson, E. G. (2026). Budget-Constrained Multi-Consensus Decentralized Gradient Descent. https://omanscience.com/en/articles/budget-constrained-multi-consensus-decentralized-gradient-descent

MLA 9

Ren, Shuyi, et al. "Budget-Constrained Multi-Consensus Decentralized Gradient Descent." https://omanscience.com/en/articles/budget-constrained-multi-consensus-decentralized-gradient-descent.

Chicago (author–date)

Ren, Shuyi, Nicol`o Michelusi, and Erik G. Larsson. 2026. "Budget-Constrained Multi-Consensus Decentralized Gradient Descent." https://omanscience.com/en/articles/budget-constrained-multi-consensus-decentralized-gradient-descent.

Harvard

Ren, S., Michelusi, N. and Larsson, E. G. (2026) 'Budget-Constrained Multi-Consensus Decentralized Gradient Descent', Available at: https://omanscience.com/en/articles/budget-constrained-multi-consensus-decentralized-gradient-descent.

Vancouver

Ren S, Michelusi N, Larsson EG. Budget-Constrained Multi-Consensus Decentralized Gradient Descent. https://omanscience.com/en/articles/budget-constrained-multi-consensus-decentralized-gradient-descent

IEEE

S. Ren, N. Michelusi, and E. G. Larsson, "Budget-Constrained Multi-Consensus Decentralized Gradient Descent," https://omanscience.com/en/articles/budget-constrained-multi-consensus-decentralized-gradient-descent.