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IEEE/IAS Industrial and Commercial Power System Asia (IEEE I and CPS Asia)

作者： Yang, Donghua Yang, Ming Shandong Univ Jinan Peoples R China

ISBN: (纸本)9798350339345

In recent years, the rapid development of national economy leads to the severe expansion of power consumption and the scale of power grids, coupled with the continuous reduction of non-renewable energy such as fossil energy, etc., people have high expectations for the efficient use of clean energy. In order to cope with the shortcomings of large power grids that are likely to spread to the whole network once a failure occurs due to the strong integrity of the large power grid, and the efficient use of new energy, multi-micro grid distributed power generation has occurred to our mind. Currently, there are two mainstream control strategies for microgrids, one is centralized algorithm and the other is distributed algorithm. The two algorithms have their own advantages and disadvantages. However, with the continuous development and expansion of the power grid, the centralized algorithm is increasingly burdened by the system, and gradually becomes inefficient and slow in response and process. Aiming at the multi-microgrid distributed system in the grid-connected operation state, this paper proposes optimization goals by constructing mathematical models for each part of the microgrid and the main grid. Finally, a case analysis is carried out based on the IEEE33 node model, and the calculation of the application of the alternating direction method of multipliers (ADMM) is discussed. Analyzes the feasibility, advantages and disadvantages of the ADMM algorithm in the distributed optimization operation of multi- microgrid, the results show that the ADMM algorithm has a well feasibility in the distributed optimization operation of multi- microgrid.

关键词： Microgrid Large power grid Renewable energy distributed algorithm ADMM

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distributed Symmetry Breaking on Power Graphs via Sparsification 23

Distributed Symmetry Breaking on Power Graphs via Sparsifica...

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42nd ACM SIGACT-SIGOPS Symposium on Principles of distributed Computing (PODC)

作者： Maus, Yannic Peltonen, Saku Uitto, Jara Graz Univ Technol Graz Austria Aalto Univ Espoo Finland

ISBN: (纸本)9798400701214

In this paper we present efficient distributed algorithms for classical symmetry breaking problems, maximal independent sets (MIS) and ruling sets, in power graphs. We work in the standard CONGEST model of distributed message passing, where the communication network is abstracted as a graph G. Typically, the problem instance in CONGEST is identical to the communication network G, that is, we perform the symmetry breaking in G. In this work, we consider a setting where the problem instance corresponds to a power graph G(k), where each node of the communication network G is connected to all of its k-hop neighbors. A beta-ruling set is a set of non-adjacent nodes such that each node in.. has a ruling neighbor within beta hops;a natural generalization of an MIS. On top of being a natural family of problems, ruling sets (in power graphs) are well-motivated through their applications in the powerful shattering framework [BEPS JACM'16, Ghaffari SODA'19] (and others). We present randomized algorithms for computing maximal independent sets and ruling sets of G(k) in essentially the same time as they can be computed in G. Our main contribution is a deterministic poly(k, logn) time algorithm for computing k-ruling sets of G(k), which (for k > 1) improves exponentially on the current state-of-the-art runtimes. Our main technical ingredient for this result is a deterministic sparsification procedure which may be of independent interest. We also revisit the shattering algorithm for MIS [BEPS J'ACM'16] and present different approaches for the post-shattering phase. Our solutions are algorithmically and analytically simpler (also in the LOCAL model) than existing solutions and obtain the same runtime as [Ghaffari SODA'16].

关键词： distributed algorithm CONGEST model maximal independent set ruling sets power graphs sparsification shattering

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distributed Dual Gradient Tracking Method for Economic Dispatch Problem 35

Distributed Dual Gradient Tracking Method for Economic Dispa...

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35th Chinese Control and Decision Conference (CCDC)

作者： Huang, Long Liu, Ring Chai, Li Wuhan Univ Sci & Technol Wuhan 430081 Peoples R China Zhejiang Univ Hangzhou 310027 Peoples R China

ISBN: (纸本)9798350334722

In this paper, we focus on solving the economic dispatch problem (EDP) in the smart grid, which aims to minimize the total generation cost while ensuring the supply-demand coordination and generation capacity constraints. First, we develop a distributed optimization algorithm by employing the gradient tracking method. Different from most existing works, our proposed algorithm allows the objective function to be strongly convex only in the range of generation capacity constraint rather than in the whole interval. Then, we prove that the convergence rate of the proposed algorithm is O(1/k) with k being the number of iteration and becomes linear rate when the average value of optimization parameters for each agent falls into a closed interval. The closed interval consists of two endpoints, which are the minimum and the maximum gradients obtained from the cost function of all generations. Finally, numerical simulations are given to demonstrate the effectiveness of the proposed algorithm.

关键词： Economic dispatch distributed algorithm gradient tracking method linear convergence

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A distributed algorithm for data collection in low-duty-cycled WSNs 3

A distributed algorithm for data collection in low-duty-cycl...

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3rd Asian Pacific Conference on Mechanical Components and Control Engineering (ICMCCE)

作者： Liu, Feng Wang, Yufei Lin, Mu Beihang Univ Sch Elect & Informat Engn Beijing 100191 Peoples R China

ISBN: (纸本)9783038353126

In order to prolong the lifetime of WSNs, low-duty-cycled scheduling is a widely used strategy. However, there exists high latency with traditional routing algorithms. In this paper, we model the data collection scheme of WSNs to be a delay optimization problem and propose a distributed algorithm based on Network Utility Maximization. The proposed algorithm can distributed find an optimal routing to achieve minimal average end-to-end delay. The simulation results show that our algorithm performs better than the traditional shortest path algorithm on end-to-end delay with less control message.

关键词： low-duty-cycled data collection distributed algorithm wireless sensor networks

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Joint computation offloading and resource allocation in vehicular edge computing networks

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Digital Communications and Networks 2023年第6期9卷 1399-1410页

作者： Shuang Liu Jie Tian Chao Zhai Tiantian Li School of Information Science and Engineering Shandong Normal UniversityJinan250358China School of Information Science and Engineering Shandong UniversityQingdao266237China

Vehicular Edge Computing(VEC)is a promising technique to accommodate the computation-intensive and delaysensitive tasks through offloading the tasks to the RoadSide-Unit(RSU)equipped with edge computing servers or neighboring ***,the limited computation resources of edge computing servers and the mobility of vehicles make the offloading policy design very *** this context,through considering the potential transmission gains brought by the mobility of vehicles,we propose an efficient computation offloading and resource allocation scheme in VEC networks with two kinds of offloading modes,i.e.,Vehicle to Vehicle(V2V)and Vehicle to RSU(V2R).We define a new cost function for vehicular users by incorporating the vehicles’offloading delay,energy consumption,and expenses with a differentiated pricing strategy,as well as the transmission *** optimization problem is formulated to minimize the average cost of all the task vehicles under the latency and computation capacity constraints.A distributed iterative algorithm is proposed by decoupling the problem into two subproblems for the offloading mode selection and the resource *** theorybased and Lagrangian-based algorithms are proposed to solve the two subproblems,*** results show the proposed algorithm achieves low complexity and significantly improves the system performance compared with three benchmark schemes.

关键词： Vehicular edge computing Task offloading Matching theory Lagrangian method distributed algorithm

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distributed Primal-Dual Mirror Dynamics for Constraint-Coupled Optimization

Distributed Primal-Dual Mirror Dynamics for Constraint-Coupl...

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2022 International Conference on Guidance, Navigation and Control

作者： Li, Jingwang Miao, Suoxia Su, Housheng Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Nanchang Inst Technol Sch Sci Nanchang 330099 Jiangxi Peoples R China

ISBN: (纸本)9789811966149;9789811966132;9789811966125

In this work, a class of distributed constrained-coupled optimization problems is studied. A primal-dual mirror dynamics is proposed, which is a generalization of the classical primal-dual gradient dynamics. However, the primal-dual mirror dynamics cannot be implemented distributedly, due to the existence of the coupled equality constraint. Therefore, a distributed primal-dual mirror dynamics is further designed and its convergence is proved under the assumption that local objectives are strictly convex and the communication topology among agents is undirected and connected. In the end, numerical simulations are taken to verify the theoretical analysis.

关键词： Primal-dual mirror dynamics Constraint-coupled optimization distributed algorithm

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A Review on Matching-based Models for distributed Computation Offloading in Fog-enabled IoT Systems 37

A Review on Matching-based Models for Distributed Computatio...

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37th International Conference on Information Networking (ICOIN)

作者： Tran-Dang, Hoa Kim, Dong-Seong Kumoh Natl Inst Technol Dept IT Convergence Engn Gumi South Korea

ISBN: (纸本)9781665462686

This paper provides a state-of-the-art review regarding matching-based distributed computation offloading frameworks for Fog-enabled IoT systems. Given the powerful tool of matching theory, its full capability is still unexplored and unexploited in the literature. We thereby discover and discuss existing challenges and corresponding solutions that the matching theory can be applied to resolve them. Furthermore, new problems and open issues for application scenarios of modern fog-enabled IoT systems are also investigated.

关键词： Fog computing Matching theory distributed algorithm Computational offloading

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An incentive mechanism design for multitask and multipublisher mobile crowdsensing environment

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JOURNAL OF SUPERCOMPUTING 2023年第5期79卷 5248-5275页

作者： Esmaeilyfard, Rasool Moghisi, Mahsa Shiraz Univ Technol Dept Comp Engn & Informat Technol Shiraz Iran

Smartphones and mobile networks have created a new paradigm called mobile crowdsensing for data gathering about a large-scale phenomenon. However, in a multitask and multi-publisher environment, user participation in tasks plays a crucial role in their success due to competition. An effective way is to provide incentives to users. This paper presents an incentive mechanism design for a multitask and multi-publisher mobile crowdsensing system based on the game theory and Stackelberg game. We aim to determine a sustainable strategy for distributing incentives between users performing tasks to multiple publishers. We study the publisher's optimal rewards for its tasks to maximize its profitability in competition with other publishers. The existence of a unique Nash equilibrium is proved, and a distributed algorithm has also been proposed to specify this equilibrium point. Extensive simulations of the mechanism and its convergence to the Nash equilibrium are conducted. The performance evaluation has revealed that this solution has the required efficiency and scalability;the proposed algorithm also converged to the game's equilibrium point.

关键词： Mobile crowdsensing Incentive mechanism Game theory Stackelberg game distributed algorithm

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Communication-efficient low-dimensional parameter estimation and inference for high-dimensional L^P-quantile regression

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SCANDINAVIAN JOURNAL OF STATISTICS 2024年第1期51卷 302-333页

作者： Gao, Junzhuo Wang, Lei Nankai Univ Sch Stat & Data Sci KLMDASR LEBPS Tianjin 300071 Peoples R China Nankai Univ LPMC Tianjin 300071 Peoples R China

The L-P-quantile regression generalizes both quantile regression and expectile regression, and has become popular for its robustness and effectiveness especially when 1 < p = 2. In this paper, we consider the data that are inherently distributed and propose two distributed L-P-quantile regression estimators for a preconceived low-dimensional parameter in the presence of high-dimensional extraneous covariates. To handle the impact of high-dimensional nuisance parameters, we first investigate regularized projection score for estimating low-dimensional parameter of main interest in L-P-quantile regression. To deal with the distributed data, we further propose two communication-efficient surrogate projection score estimators and establish their theoretical properties. The finite-sample performance of the proposed estimators is studied through simulations and an application to Communities and Crime data set is also presented.

关键词： L-P-quantile regression communication-efficient distributed algorithm regularized projection score

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Online distributed Coordinated Precoding for Virtualized MIMO Networks With Delayed CSI

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IEEE WIRELESS COMMUNICATIONS LETTERS 2022年第5期11卷 1012-1016页

作者： Wang, Juncheng Liang, Ben Dong, Min Boudreau, Gary Abou-Zeid, Hatem Univ Toronto Dept Elect & Comp Engn Toronto ON M5S 1A1 Canada Ontario Tech Univ Dept Elect Comp & Software Engn Oshawa ON L1G 0C5 Canada Ericsson Canada Ottawa ON K2K 2V6 Canada Univ Calgary Dept Elect & Software Engn Calgary AB T2N 1N4 Canada

We consider online wireless network virtualization in a multi-cell multiple-input multiple-output system with delayed feedback of channel state information (CSI). Multiple service providers (SPs) simultaneously share the base station resources of an infrastructure provider (InP). We aim at minimizing the accumulated precoding deviation of the InP's actual precoder from the SPs' virtualization demands via managing both inter-SP and inter-cell interference, subject to both long-term and short-term per-cell transmit power constraints. We develop an online coordinated precoding solution and show that it provides provable performance bounds. Our precoding solution is fully distributed at each cell, based only on delayed local CSI. Furthermore, it has a closed-form expression with low computational complexity. Simulation results demonstrate the substantial performance gain of our precoding solution over the current best alternative.

关键词： Precoding Indium phosphide III-V semiconductor materials MIMO communication Virtualization Interference Optimization Network virtualization delayed CSI coordinated precoding online optimization distributed algorithm

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