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 in | Systems & control letters Vol. 199; p. 106062 |
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Language | English |
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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. |
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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 |
Author_xml | – sequence: 1 givenname: Mohammadreza orcidid: 0000-0003-0959-6608 surname: Doostmohammadian fullname: Doostmohammadian, Mohammadreza email: doost@semnan.ac.ir organization: Mechatronics Group, Faculty of Mechanical Engineering, Semnan University, Semnan, Iran – sequence: 2 givenname: Zulfiya R. surname: Gabidullina fullname: Gabidullina, Zulfiya R. email: Zulfiya.Gabidullina@kpfu.ru organization: Institute of Computational Mathematics and Information Technologies, Kazan Federal University, Russia – sequence: 3 givenname: Hamid R. surname: Rabiee fullname: Rabiee, Hamid R. email: rabiee@sharif.edu organization: Computer Engineering Department, Sharif University of Technology, Tehran, Iran |
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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 |
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