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This paper proposes networked dynamics to solve resource allocation problemsover time-varying multi-agent networks. The state of each agent represents theamount of used resources (or produced utilities) while the total amount ofresources is fixed. The idea is to optimally allocate the resources among thegroup of agents by minimizing the overall cost function subject to fixed sum ofresources. Each agents' information is restricted to its own state and costfunction and those of its immediate in-neighbors. This is motivated bydistributed applications such as mobile edge-computing, economic dispatch oversmart grids, and multi-agent coverage control. This work provides a fastconvergent solution (in comparison with linear dynamics) while consideringrelaxed network connectivity with quantized communication links. The proposeddynamics reaches optimal solution over switching (possibly disconnected)undirected networks as far as their union over some bounded non-overlappingtime-intervals has a spanning-tree. We prove feasibility of the solution,uniqueness of the optimal state, and convergence to the optimal value under theproposed dynamics, where the analysis is applicable to similar 1st-orderallocation dynamics with strongly sign-preserving nonlinearities, such asactuator saturation.

Fast-Convergent Dynamics for Distributed Allocation of Resources Over Switching Sparse Networks with Quantized Communication Links