TY - GEN
T1 - Fast-Convergent Anytime-Feasible Dynamics for Distributed Allocation of Resources over Switching Sparse Networks with Quantized Communication Links
AU - Doostmohammadian, Mohammadreza
AU - Aghasi, Alireza
AU - Pirani, Mohammad
AU - Nekouei, Ehsan
AU - Khan, Usman A.
AU - Charalambous, Themistoklis
N1 - Publisher Copyright:
© 2022 EUCA.
PY - 2022
Y1 - 2022
N2 - This paper proposes anytime feasible networked dynamics to solve resource allocation problems over time-varying multi-agent networks. The state of agents represents the assigned resources while their total (equal to demand) is constant. The idea is to optimally allocate the resources among the group of agents by minimizing the overall cost subject to fixed sum of resources. Each agent's information is local and restricted to its own state, cost function, and the ones from its immediate neighbors. This work provides a fast convergent solution (compared to linear dynamics) while considering more-relaxed uniform network connectivity and (logarithmic) quantized communications among agents. The proposed dynamics reaches optimal solution over switching (sparsely-connected) undirected networks as far as their union over some bounded non-overlapping time-intervals has a spanning tree. Moreover, we prove anytime-feasibility of the solution, uniqueness, and convergence to the optimal value irrespective of the specific nonlinearity in the proposed dynamics. Such general proof analysis applies to many similar 1st-order allocation dynamics subject to strongly sign-preserving nonlinearities, e.g., actuator saturation in generator coordination. Further, anytime feasibility (despite the nonlinearities) ensures that our solution satisfies the fixed-sum resources constraint at all times.
AB - This paper proposes anytime feasible networked dynamics to solve resource allocation problems over time-varying multi-agent networks. The state of agents represents the assigned resources while their total (equal to demand) is constant. The idea is to optimally allocate the resources among the group of agents by minimizing the overall cost subject to fixed sum of resources. Each agent's information is local and restricted to its own state, cost function, and the ones from its immediate neighbors. This work provides a fast convergent solution (compared to linear dynamics) while considering more-relaxed uniform network connectivity and (logarithmic) quantized communications among agents. The proposed dynamics reaches optimal solution over switching (sparsely-connected) undirected networks as far as their union over some bounded non-overlapping time-intervals has a spanning tree. Moreover, we prove anytime-feasibility of the solution, uniqueness, and convergence to the optimal value irrespective of the specific nonlinearity in the proposed dynamics. Such general proof analysis applies to many similar 1st-order allocation dynamics subject to strongly sign-preserving nonlinearities, e.g., actuator saturation in generator coordination. Further, anytime feasibility (despite the nonlinearities) ensures that our solution satisfies the fixed-sum resources constraint at all times.
KW - consensus
KW - Distributed optimization
KW - logarithmic quantization
KW - resource allocation
KW - spanning tree
UR - http://www.scopus.com/inward/record.url?scp=85136658200&partnerID=8YFLogxK
U2 - 10.23919/ECC55457.2022.9838141
DO - 10.23919/ECC55457.2022.9838141
M3 - Conference contribution
AN - SCOPUS:85136658200
T3 - 2022 European Control Conference, ECC 2022
SP - 84
EP - 89
BT - 2022 European Control Conference, ECC 2022
PB - IEEE
T2 - European Control Conference
Y2 - 12 July 2022 through 15 July 2022
ER -