Joint Computation and Communication Cooperation for Mobile Edge Computing

This paper proposes a novel joint computation and communication cooperation approach in mobile edge computing (MEC) systems, which enables user cooperation in both computation and communication for improving the MEC performance. In particular, we consider a basic three-node MEC system that consists of a user node, a helper node, and an access point (AP) node attached with an MEC server. We focus on the user's latency-constrained computation over a finite block, and develop a four-slot protocol for implementing the joint computation and communication cooperation. Under this setup, we jointly optimize the computation and communication resource allocation at both the user and the helper, so as to minimize their total energy consumption subject to the user's computation latency constraint. We provide the optimal solution to this problem. Numerical results show that the proposed joint cooperation approach significantly improves the computation capacity and the energy efficiency at the user and helper nodes, as compared to other benchmark schemes without such a joint design.Comment: 8 pages, 4 figure

Bridging Transient and Steady-State Performance in Voltage Control: A Reinforcement Learning Approach with Safe Gradient Flow

Deep reinforcement learning approaches are becoming appealing for the design of nonlinear controllers for voltage control problems, but the lack of stability guarantees hinders their deployment in real-world scenarios. This paper constructs a decentralized RL-based controller featuring two components: a transient control policy and a steady-state performance optimizer. The transient policy is parameterized as a neural network, and the steady-state optimizer represents the gradient of the long-term operating cost function. The two parts are synthesized through a safe gradient flow framework, which prevents the violation of reactive power capacity constraints. We prove that if the output of the transient controller is bounded and monotonically decreasing with respect to its input, then the closed-loop system is asymptotically stable and converges to the optimal steady-state solution. We demonstrate the effectiveness of our method by conducting experiments with IEEE 13-bus and 123-bus distribution system test feeders.Comment: Published in IEEE Control Systems Letters, vol. 7, pp. 2845-2850, 2023 with CDC presentatio

Bis[3-chloro-6-(3,5-dimethyl-1H-pyrazol-1-yl)picolinato]nickel(II) tetra­hydrate

In the title complex, [Ni(C11H9ClN3O2)2]·4H2O, the Ni atom is coordinated by four N atoms and two O atoms derived from two tridentate 3-chloro-6-(3,5-dimethyl-1H-pyrazol-1-yl)picolinate ligands. The cis-N4O2 donor set defines a distorted octa­hedral geometry. In the crystal structure, the complex and water mol­ecules are linked by O—H⋯O hydrogen bonds

Bis[6-(3,5-dimethyl-1H-pyrazol-1-yl)picolinato-κ2 N 1,O 2]cadmium(II) 1.75-hydrate

In the title complex, [Cd(C11H10N3O2)2]·1.75H2O, the Cd atom is coordinated by four N atoms and two O atoms from two tridentate 6-(3,5-dimethyl-1H-pyrazol-1-yl)picolinate ligands in a distorted cis-N4O2 octa­hedral geometry. Three water mol­ecules, with occupancies of 1.0, 0.5 and 0.25, complete the asymmetric unit. The components of the crystal structure are linked via hydrogen bonds, forming a three-dimensional network

[3-Chloro-6-(3,5-dimethyl-1H-pyrazol-1-yl)picolinato](pyridine-2,6-dicarboxyl­ato)nickel(II) dihydrate

In the title compound, [Ni(C11H9ClN3O2)(C7H3NO4)]·2H2O, the NiII atom is coordinated by two N atoms and one O atom of 3-chloro-6-(3,5-dimethyl-1H-pyrazol-1-yl)picolinate and by one N atom and two O atoms of pyridine-2,6-dicarboxyl­ate in a distorted octa­hedral coordination. In the crystal structure, mol­ecules are linked together by inter­molecular O—H⋯O hydrogen bonds. One water mol­ecule is disordered over two positions; the site occupancies are ca 0.53 and 0.47