Momentum-based distributed resource scheduling optimization subject to sector-bound nonlinearity and latency

This paper proposes an accelerated consensus-based distributed iterative algorithm for resource allocation and scheduling. The proposed gradient-tracking algorithm introduces an auxiliary variable to add momentum towards the optimal state. We prove that this solution is all-time feasible, implying t...

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Published inSystems & control letters Vol. 199; p. 106062
Main Authors Doostmohammadian, Mohammadreza, Gabidullina, Zulfiya R., Rabiee, Hamid R.
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.05.2025
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Abstract This paper proposes an accelerated consensus-based distributed iterative algorithm for resource allocation and scheduling. The proposed gradient-tracking algorithm introduces an auxiliary variable to add momentum towards the optimal state. We prove that this solution is all-time feasible, implying that the coupling constraint always holds along the algorithm iterative procedure; therefore, the algorithm can be terminated at any time. This is in contrast to the ADMM-based solutions that meet constraint feasibility asymptotically. Further, we show that the proposed algorithm can handle possible link nonlinearity due to logarithmically-quantized data transmission (or any sign-preserving odd sector-bound nonlinear mapping). We prove convergence over uniformly-connected dynamic networks (i.e., a hybrid setup) that may occur in mobile and time-varying multi-agent networks. Further, the latency issue over the network is addressed by proposing delay-tolerant solutions. To our best knowledge, accelerated momentum-based convergence, nonlinear linking, all-time feasibility, uniform network connectivity, and handling (possible) time delays are not altogether addressed in the literature. These contributions make our solution practical in many real-world applications. •Introducing accelerated momentum-based algorithm for distributed resource allocation.•Proving all-time feasibility to ensure coupling constraint holds at every iteration•Managing link nonlinearity arising from sign-preserving odd sector-bound mappings.•Proof of convergence over uniformly-connected dynamic networks.•Addressing latency and time-delay issues in network communication.
AbstractList This paper proposes an accelerated consensus-based distributed iterative algorithm for resource allocation and scheduling. The proposed gradient-tracking algorithm introduces an auxiliary variable to add momentum towards the optimal state. We prove that this solution is all-time feasible, implying that the coupling constraint always holds along the algorithm iterative procedure; therefore, the algorithm can be terminated at any time. This is in contrast to the ADMM-based solutions that meet constraint feasibility asymptotically. Further, we show that the proposed algorithm can handle possible link nonlinearity due to logarithmically-quantized data transmission (or any sign-preserving odd sector-bound nonlinear mapping). We prove convergence over uniformly-connected dynamic networks (i.e., a hybrid setup) that may occur in mobile and time-varying multi-agent networks. Further, the latency issue over the network is addressed by proposing delay-tolerant solutions. To our best knowledge, accelerated momentum-based convergence, nonlinear linking, all-time feasibility, uniform network connectivity, and handling (possible) time delays are not altogether addressed in the literature. These contributions make our solution practical in many real-world applications. •Introducing accelerated momentum-based algorithm for distributed resource allocation.•Proving all-time feasibility to ensure coupling constraint holds at every iteration•Managing link nonlinearity arising from sign-preserving odd sector-bound mappings.•Proof of convergence over uniformly-connected dynamic networks.•Addressing latency and time-delay issues in network communication.
ArticleNumber 106062
Author Gabidullina, Zulfiya R.
Rabiee, Hamid R.
Doostmohammadian, Mohammadreza
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Keywords Distributed constrained optimization
Resource scheduling and allocation
Graph theory
Consensus
Convex analysis
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SSID ssj0002033
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Snippet This paper proposes an accelerated consensus-based distributed iterative algorithm for resource allocation and scheduling. The proposed gradient-tracking...
SourceID crossref
elsevier
SourceType Index Database
Publisher
StartPage 106062
SubjectTerms Consensus
Convex analysis
Distributed constrained optimization
Graph theory
Resource scheduling and allocation
Title Momentum-based distributed resource scheduling optimization subject to sector-bound nonlinearity and latency
URI https://dx.doi.org/10.1016/j.sysconle.2025.106062
Volume 199
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