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Cooperative/Parallel Kalman Filtering for decentralized Network Navigation

IEICE TRANSACTIONS ON COMMUNICATIONS 2016年第9期E99B卷 2087-2098页

作者： Gao, Wenyun Chen, Xi Hu, Dexiu Xu, Haisheng Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China Tsinghua Univ Space Ctr Beijing 100084 Peoples R China

This paper presents non-iterative cooperative/parallel Kalman filtering algorithms for decentralized network navigation, in which mobile nodes cooperate in both spatial and temporal domains to infer their positions. We begin by presenting an augmented minimum-mean-square error (MMSE) estimator for centralized navigation network, and then decouple it into a set of local sub-ones each corresponding to a mobile node;all these sub-estimators work in parallel and cooperatively-with the state estimates exchanging between neighbors-to provide results similar to those obtained by the augmented one. After that, we employ the approximation methods that adopted in the conventional nonlinear Kalman filters to calculate the second-order terms involved in these sub-estimators, and propose a decentralized cooperative/parallel Kalman filtering based network navigation framework. Finally, upon the framework, we present two cooperative/parallel Kalman filtering algorithms corresponding to the extended and unscented Kalman filters respectively, and compare them with conventional decentralized methods by simulations to show the superiority.

关键词： network navigation decentralized algorithm cooperative algorithms Kalmen filter

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Spatial gossip and resource location protocols

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JOURNAL OF THE ACM 2004年第6期51卷 943-967页

作者： Kempe, D Kleinberg, J Demers, A Univ So Calif Los Angeles CA USA Cornell Univ Ithaca NY USA

The dynamic behavior of a network in which information is changing continuously over time requires robust and efficient mechanisms for keeping nodes updated about new information. Gossip protocols are mechanisms for this task in which nodes communicate with one another according to some underlying deterministic or randomized algorithm, exchanging information in each communication step. In a variety of contexts, the use of randomization to propagate information has been found to provide better reliability and scalability than more regimented deterministic approaches. In many settings, such as a cluster of distributed computing hosts, new information is generated at individual nodes, and is most "interesting" to nodes that are nearby. Thus, we propose distance-based propagation bounds as a performance measure for gossip mechanisms: a node at distance d from the origin of a new piece of information should be able to learn about this information with a delay that grows slowly with d, and is independent of the size of the network. For nodes arranged with uniform density in Euclidean space, we present natural gossip mechanisms, called spatial gossip, that satisfy such a guarantee: new information is spread to nodes at distance d, with high probability, in O(log(1+epsilon) d) time steps. Such a bound combines the desirable qualitative features of uniform gossip, in which information is spread with a delay that is logarithmic in the full network size, and deterministic flooding, in which information is spread with a delay that is linear in the distance and independent of the network size. Our mechanisms and their analysis resolve a conjecture of Demers et al. [1987]. We further show an application of our gossip mechanisms to a basic resource location problem, in which nodes seek to rapidly learn of the nearest copy of a resource in a network. This problem, which is of considerable practical importance, can be solved by a very simple protocol using Spatial Gossip, whereas we

关键词： algorithms gossip resource location decentralized algorithm

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Capri: Consensus Accelerated Proximal Reweighted Iteration for A Class of Nonconvex Minimizations

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2022年第3期34卷 1066-1079页

作者： Sun, Tao Li, Dongsheng Natl Univ Def Technol Coll Comp Changsha 410073 Peoples R China

We consider a class of nonconvex regularized optimization problems, which appear frequently in machine learning and data processing. Due to the structure of the problems, the iteratively reweighted algorithm was developed and applied to the consensus optimization. In this paper, we propose the acceleration of this scheme by adding an inertial term in each iteration. The proposed algorithms inherit the advantages of classical decentralized algorithms: they can be implemented over a connected network, in which the agents communicate with their neighbors and perform local computations. We also employ the diminishing stepsizes technique for the iteratively reweighted algorithm and consider its acceleration. In specific cases, our algorithms reduce to existing decentralized schemes and also indicate novel ones. Mathematically, we prove the convergence for both algorithms with several assumptions on the objective functions. With Kurdyka-Lojasiewicz property, convergence rates can be derived for constant stepsize case. Numerical results demonstrate the efficiency of the algorithms.

关键词： Minimization Acceleration Convergence Optimization Machine learning Machine learning algorithms Manganese decentralized algorithm nonconvexity nonsmooth acceleration momentum

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Energy-Efficient Base Station Association and Beamforming for Multi-Cell Multiuser Systems

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2020年第4期19卷 2841-2854页

作者： An, Jianping Zhang, Yihao Gao, Xiaozheng Yang, Kai Beijing Inst Technol Sch Informat & Elect Beijing 100081 Peoples R China

This paper investigates the joint base station (BS) association and beamforming for energy efficiency maximization in coordinated multi-cell multiuser downlink systems. In particular, we assume that only the channel distribution information is known to the BSs. The considered problem is difficult to be solved optimally due to the non-smooth and non-convex functions in the formulation. Therefore, we propose an iterative suboptimal algorithm to solve the problem efficiently based on the successive convex approximation (SCA). More specifically, the convex approximation of the original problem at each iteration can be solved efficiently by the second-order cone programming and the solution obtained by the proposed algorithm satisfies the generalized Karush-Kuhn-Tucker (KKT) conditions. To facilitate the implementation of decentralized beamforming, we transform the convex approximation problem at each iteration of the SCA into an equivalent form, which is amenable to applying the alternating direction method of multipliers (ADMM). By combining the SCA and the ADMM, a decentralized energy-efficient beamforming algorithm is proposed. Numerical results are presented to show the performance of the proposed algorithms.

关键词： Energy efficient base station association coordinated beamforming outage probability decentralized algorithm

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decentralized Failure-Tolerant Optimization of Electric Vehicle Charging

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IEEE TRANSACTIONS ON SMART GRID 2021年第5期12卷 4068-4078页

作者： Aravena, Ignacio Chapin, Steve J. Ponce, Colin Lawrence Livermore Natl Lab Livermore CA 94550 USA

We present a decentralized failure-tolerant algorithm for optimizing electric vehicle (EV) charging, using charging stations as computing agents. The algorithm is based on the alternating direction method of multipliers (ADMM) and it has the following features: (i) It handles coupling constraints for capacity, peak demand, and ancillary services. (ii) It does not require a central agent collecting information and performing coordination (e.g., an aggregator), instead all agents exchange information and computations are carried out in a fully decentralized fashion. (iii) It can withstand the failure of any number of computing agents, as long as the remaining computing agents are in a connected communications network. We construct this algorithm by reformulating the optimal EV charging problem in a decomposable form, amenable to ADMM, and then developing efficient decentralized solution methods for the subproblems dealing with coupling constraints. We conduct numerical experiments on industry-scale synthetic EV charging datasets, with up to 1 152 charging stations, using a high-performance computing cluster. The experiments demonstrate that the proposed algorithm can solve the optimal EV charging problem fast enough to permit the integration of EV charging with real-time electricity markets, even in the presence of failures.

关键词： Electric vehicle charging Processor scheduling Games Real-time systems Job shop scheduling Optimization Couplings Electric vehicle charging ADMM decentralized algorithm fail-proof algorithm

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Sponge Grid With Numerous Virtual Energy Storage Systems: Concept, Model, and decentralized Control

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IEEE TRANSACTIONS ON SMART GRID 2023年第4期14卷 2986-2998页

作者： Mu, Chenggang Ding, Tao Huang, Yuhan Zhu, Shanying Siano, Pierluigi Shahidehpour, Mohammad Xi An Jiao Tong Univ Sch Elect Engn Xian 710049 Shaanxi Peoples R China Shanghai Jiao Tong Univ Dept Automation Shanghai 200240 Peoples R China Univ Salerno Dept Management & Innovat Syst I-84084 Fisciano Italy IIT ECE Dept Chicago IL 60616 USA

High proportion of energy storage systems (ESSs) and flexible loads signify the main features of a modern power system. ESS with its bi-directional flow characteristic can flexibly change power network operations, thus providing a new solution for voltage regulation and control. However, since ESS resources are dispersed throughout the power system, it is necessary to design an effective aggregation scheme to achieve a concise voltage regulation. In this paper, a novel sponge grid is proposed, which is capable of both local and global tasks to offer greater flexibility and initiative in power system operations. On the one hand, it constructs the source and forms virtual energy storage (VES) systems to satisfy local demands. On the other hand, the sponge grid applies the superposition of a large number of VES systems spontaneous effects to present a collective voltage regulation behavior. Then, a message passing-based decentralized algorithm is proposed and designed for the local voltage regulation in the sponge grid. Various constraints including those representing inequality boundary, state of charge, and complex line flows, are expressed analytically and computed fast by the proposed portable projection approach. The proposed sponge grid model is tested on a modified IEEE 33-bus system to verify its effectiveness and superior performance.

关键词： Voltage control Regulation Microgrids Energy storage Power systems State of charge Reactive power Sponge grid virtual energy storage message passing decentralized algorithm projection

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Multicast Beamforming Design in Multicell Networks With Successive Group Decoding

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2017年第6期16卷 3492-3506页

作者： Ashraphijuo, Mehdi Wang, Xiaodong Tao, Meixia Columbia Univ Dept Elect Engn New York NY 10027 USA Shanghai Jiao Tong Univ Dept Elect Engn Shanghai 200240 Peoples R China

We consider a generic problem of multicast beamforming design in multicell networks where each base station (BS) has multiple independent messages to multicast and each user intends to decode an arbitrary subset of messages sent from all BSs using successive group decoding (SGD). We first formulate the total transmit power minimization problem subject to the constraints that a target rate vector is achievable by the SGDs at all receivers. This problem is a non-convex quadratically constrained quadratic program and NP-hard. We propose a new method based on solving a sequence of linearly regularized semi-definite programming (SDP) relaxation of the original problem that yields feasible and near-optimal solutions with high probability. Moreover, we propose a decentralized algorithm based on the alternating direction method of multipliers to solve each linearly regularized SDP, which consists of solving a quadratic program at the central controller, and closed-form analytic computations at each BS. Finally, we propose an iterative procedure for joint beamformer and rate optimization under the SGD framework. Numerical results confirm the superiority of the proposed beamformer design in both performance and complexity. It is also demonstrated that, compared with the traditional linear receivers, the SGD receivers achieve both significant rate improvement and energy savings.

关键词： Successive group decoding multicell multicast beamforming semi-definite program decentralized algorithm ADMM

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A decentralized Damage Detection System for Wireless Sensor and Actuator Networks

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IEEE TRANSACTIONS ON COMPUTERS 2016年第5期65卷 1363-1376页

作者： Santos, Igor L. Pirmez, Luci Carmo, Luiz R. Pires, Paulo F. Delicato, Flavia C. Khan, Samee U. Zomaya, Albert Y. Univ Fed Rio de Janeiro BR-21941901 Rio De Janeiro Brazil Inst Nacl Metrol Qualidade & Tecnol Inmetro Av NS Gracas Duque De Caxias Brazil N Dakota State Univ Elect & Comp Engn Fargo ND 58108 USA Univ Sydney Sch Informat Technol Adv Networks Res Grp Sydney NSW 2006 Australia

The unprecedented capabilities of monitoring and responding to stimuli in the physical world of wireless sensor and actuator networks (WSAN) enable these networks to provide the underpinning for several Smart City applications, such as structural health monitoring (SHM). In such applications, civil structures, endowed with wireless smart devices, are able to self-monitor and autonomously respond to situations using computational intelligence. This work presents a decentralized algorithm for detecting damage in structures by using a WSAN. As key characteristics, beyond presenting a fully decentralized (in-network) and collaborative approach for detecting damage in structures, our algorithm makes use of cooperative information fusion for calculating a damage coefficient. We conducted experiments for evaluating the algorithm in terms of its accuracy and efficient use of the constrained WSAN resources. We found that our collaborative and information fusion-based approach ensures the accuracy of our algorithm and that it can answer promptly to stimuli (1.091s), triggering actuators. Moreover, for 100 nodes or less in the WSAN, the communication overhead of our algorithm is tolerable and the WSAN running our algorithm, operating system and protocols can last as long as 468 days.

关键词： decentralized algorithm information fusion structural health monitoring wireless sensor and actuator networks smart cities

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Zonally Robust decentralized Optimization for Global Energy Interconnection: Case Study on Northeast Asian Countries

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2020年第4期17卷 2120-2129页

作者： Ding, Tao Yang, Qingrun Wen, Ya Ning, Ye Yang, Yongheng Blaabjerg, Frede Xi An Jiao Tong Univ Dept Elect Engn Xian 710049 Peoples R China Global Energy Interconnect Res Inst Beijing 100072 Peoples R China Aalborg Univ Dept Energy Technol DK-9220 Aalborg Denmark

Nowadays, the entire world is facing challenges in energy and environment. To resolve these problems, the power systems are interconnected to promote the development of renewable energy sources (RESs). However, the economic dispatch (ED) problem for the global energy interconnection (GEI) should tackle two issues: 1) handle the uncertainty from RES and allocate the responsibility among the interconnected countries and 2) protect the information privacy through the dispatch. Motivated by the above, this article proposes a zonally adjustable robust decentralized ED model for the GEI. In the model, each country is only responsible for its own uncertainty, and tie-line power flows remain unchanged under uncertainties. Moreover, an alternating direction method of multipliers (ADMM)-based fully distributed algorithm is used, in which only limited information should be exchanged between neighboring countries. Finally, a case study on the Northeast Asian countries verifies the effectiveness of the proposed method. Note to Practitioners-Since the renewable energy generation has a spatial correlation among regional countries, global energy interconnection (GEI) aims to combine several power systems together to promote the renewable energy accommodation. However, two problems need to be considered: 1) Information Privacy: The information privacy of the power system in each country should be preserved, which prevents the GEI from conducting a centralized optimal dispatch framework and 2) Uncertainty: The uncertain output of renewable energy resources brings challenge to the power system secure operation. The main contribution of this article is to set up a zonally robust decentralized optimization for the GEI, where the zonally robust economic dispatch (ED) is conducted by the area control error (ACE) system to manage the difference between scheduled and actual generation under the uncertainties, and the alternating direction method of multipliers (ADMMs) algorithm is adopted f

关键词： Robustness Uncertainty Optimization Economics Power systems Distributed algorithms Privacy decentralized algorithm economic dispatch (ED) global energy interconnection (GEI) zonal robustness

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Research on decentralized operation scheduling strategy of integrated energy system based on energy blockchain

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INTERNATIONAL JOURNAL OF ENERGY RESEARCH 2022年第15期46卷 21558-21582页

作者： Liu, Xiaoou China Energy Engn Grp Tianjin Elect Power Design Energy Planning & Res Ctr Tianjin Peoples R China

With the increasing proportion of renewable energy generation connected to grid, the architecture, control method, and operation mode of the energy system begin to change. The energy system has some problems, such as difficult to maintain the privacy of energy suppliers, difficult to distinguish the authenticity of data, and low security and reliability. The introduction of blockchain technology into energy system to form an energy blockchain network is conducive to solving the information security and other issues. Aiming at the integrated energy system (IES) with renewable energy generation, the practical Byzantine fault tolerance (PBFT) algorithm consensus mechanism suitable for IES is proposed to realize the two-stage robust optimal scheduling model, which uses decentralized scheduling strategy and blockchain technology. In the first stage, the technology of decoupling heat power is used to form electrical/thermal iteration chain, and the decentralized scheduling model based on Lagrange multiplier method is built. For the data consistency of decentralized scheduling, the undirected unicom structure is used to establish the communication network between energy suppliers. The thermal/electrical iterative chain and the terminal chain apply the consistency protocol algorithm and Byzantine fault tolerance consensus mechanism to solve the prescheduling scheme based on the decentralized algorithm. In the second stage, the blockchain technology is used to obtain historical data, and a data-driven renewable generation power uncertain set is established to solve the Regulation scheme. This constraint set can exclude some extreme scenarios to reduce the conservatism of the model. In the two-stage optimization process, the verification function of Byzantine fault tolerance consensus mechanism is used to discard the information tampered by malicious attack and enhance the system fault tolerance capability. The example verification results show that the proposed architecture

关键词： consensus mechanism decentralized algorithm energy blockchain integrated energy system operation scheduling

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