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An Online Multistep-Forward Voltage-Prediction Approach Based on an LSTM-TD Model and KF Algorithm

COMPUTER 2021年第8期54卷 56-65页

作者： Ni, Ye Xia, Zhilong Fang, Chunrong Chen, Zhenyu Zhao, Fangtong Nanjing Univ Nanjing Peoples R China Univ Akron Akron OH 44325 USA

We propose a multistep-forward voltage-prediction approach combining a long short-term memory time-distributed model and the Kalman filter algorithm to improve prediction efficiency and reduce the demand for computing... 详细信息

关键词： distributed algorithms Kalman Filters Recurrent Neural Nets LSTM TD Model KF Algorithm Kalman Filter Algorithm Prediction Efficiency Online Multistep Forward Voltage Prediction Approach Long Short Term Memory Time distributed Model Computing Capability Computational Modeling Memory Management Predictive Models Prediction algorithms Kalman Filters

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Totally Asynchronous Large-Scale Quadratic Programming: Regularization, Convergence Rates, and Parameter Selection

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IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS 2021年第3期8卷 1465-1476页

作者： Ubl, Matthew Hale, Matthew Univ Florida Dept Mech & Aerosp Engn Gainesville FL 32611 USA

Quadratic programs arise in robotics, communications, smart grids, and many other applications. As these problems grow in size, finding solutions becomes more computationally demanding, and new algorithms are needed to efficiently solve them at massive scales. Targeting large-scale problems, we develop a multiagent quadratic programming framework in which each agent updates only a small number of the total decision variables in a problem. Agents communicate their updated values to each other, though we do not impose any restrictions on the timing with which they do so, nor on the delays in these transmissions. Furthermore, we allow agents to independently choose their stepsizes, subject to mild restrictions. We further provide the means for agents to independently regularize the problems they solve, thereby improving convergence properties while preserving agents' independence in selecting parameters. Larger regularizations accelerate convergence but increase the error in the solution obtained, and we quantify the tradeoff between convergence rates and quality of solutions. Simulation results are presented to illustrate these developments.

关键词： Autonomous agents distributed algorithms optimization network control systems quadratic programming

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Integrated Energy and Trust-Based Semi-Markov Prediction for Lifetime Maximization in Wireless Sensor Networks

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WIRELESS PERSONAL COMMUNICATIONS 2021年第1期118卷 505-522页

作者： Famila, S. Jawahar, A. Vimalraj, S. Leones Sherwin Lydia, J. SSN Engn Coll Dept Elect & Commun Engn Chennai Tamil Nadu India Panimalar Engn Coll Dept Elect & Commun Engn Chennai Tamil Nadu India Easwari Engn Coll Dept Elect & Elect Engn Chennai Tamil Nadu India

Many of today's computing and communication models are distributed systems that are composed of autonomous computational entities that communicate with each other, usually by passing messages. distributed systems encompass a variety of applications and wireless sensor networks (WSN) is an important application of it. The tiny, multiple functionality and low power sensor nodes are considered to be interconnected in the WSN for efficient process of aggregating and transmitting the data to the base station. The clustering-based schemes of sensor networks are capable of organizing the network through the utilization of a specifically designated node termed as the cluster head for the objective of energy conservation and data aggregation. Further, the cluster head is responsible for conveying potential information collected by the cluster member nodes and aggregate them before transmitting it to the base station. In this paper, a Reliable Cluster Head Selection Technique using Integrated Energy and Trust-based Semi-Markov Prediction (RCHST-IETSMP) is proposed with the view to extend the lifetime of sensor networks. This proposed RCHST-IETSMP incorporated two significant parameters associated with energy and trust for effective selection of cluster head facilitated through the merits of Semi-Markoc prediction integrated with the Hyper Erlang distribution process. The simulation results of the proposed RCHST-IETSMP scheme is proving to be efficient in upholding the residual energy of the network and the throughput to a maximum level of 23% and 19% predominant to the trust and energy-based clustering schemes considered for investigation.

关键词： distributed algorithms Clustering Semi-Markov prediction Data aggregation Parallel algorithms

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Max-Consensus Over Fading Wireless Channels

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IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS 2021年第2期8卷 791-802页

作者： Molinari, Fabio Agrawal, Navneet Stanczak, Slawomir Raisch, Joerg Tech Univ Berlin Control Syst Grp D-10623 Berlin Germany Tech Univ Berlin Network Informat Theory Grp D-10623 Berlin Germany Fraunhofer Heinrich Hertz Inst D-10587 Berlin Germany

This article deals with the problem of achieving finite-time max-consensus in a multiagent system that communicates over a fading wireless channel. A key feature of the wireless channel is the superposition (or broadcast) property. In traditional wireless communication systems, the superposition property is usually undesired since it might cause interference that drastically degrades system performance. In contrast, in the multiagent system considered in this article, different agents aim at achieving max-consensus. Therefore, rather than combatting interference due to the superposition property, we design a communication system that exploits this property for a more efficient usage of wireless resources. By simultaneously accessing the wireless channel, each agent obtains a weighted average of the neighboring agents' information states, where weights (namely, channel coefficients) are unknown and fading. Given that each agent has access to this piece of information, we present a switching consensus protocol employing broadcast authorization for agents and show that max-consensus can be achieved under this protocol within a finite number of iterations.

关键词： Decentralized control distributed algorithms networked control systems wireless communication

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Accelerated Voltage Regulation in Multi-Phase Distribution Networks Based on Hierarchical distributed Algorithm

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IEEE TRANSACTIONS ON POWER SYSTEMS 2020年第3期35卷 2047-2058页

作者： Zhou, Xinyang Liu, Zhiyuan Zhao, Changhong Chen, Lijun Natl Renewable Energy Lab Power Syst Engn Dept Golden CO 80401 USA Univ Colorado Coll Engn & Appl Sci Boulder CO 80309 USA Chinese Univ Hong Kong Dept Informat Engn Hong Kong Peoples R China

We propose a hierarchical distributed algorithm to solve optimal power flow (OPF) problems that aim at dispatching controllable distributed energy resources (DERs) for voltage regulation at minimum cost. The proposed algorithm features unprecedented scalability to large multi-phase distribution networks by jointly exploring the tree/subtrees structure of a large radial distribution network and the structure of the linearized distribution power flow (LinDistFlow) model to derive a hierarchical, distributed implementation of the primal-dual gradient algorithm that solves OPF. The proposed implementation significantly reduces the computation loads compared to the centrally coordinated implementation of the same primal-dual algorithm without compromising optimality. Numerical results on a 4,521-node test feeder show that the designed algorithm achieves more than 10-fold acceleration in the speed of convergence compared to the centrally coordinated primal-dual algorithm through reducing and distributing computational loads.

关键词： Convergence Voltage control distributed algorithms Computational modeling Load modeling Microgrids Acceleration distributed algorithms gradient methods large-scale systems optimal control voltage control

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Minimizing the Signaling Overhead and Latency Based on Users' Mobility Patterns

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IEEE SYSTEMS JOURNAL 2021年第1期15卷 77-84页

作者： Dzaferagic, Merim Marchetti, Nicola Macaluso, Irene Trinity Coll Dublin Elect & Elect Engn Dept CONNECT Dublin D02 PN40 Ireland

We demonstrate a distributed and a centralized 4G/5G compliant approach to minimize signaling and latency related to user mobility in cellular networks. This is crucial due to the densification of networks and the additional signaling introduced by the new 5G service-based architecture. By exploiting standardized protocols, our solutions dynamically reorganize the association between nodes in radio access network (RAN) and the core. We validated the proposed approaches using real user mobility datasets. Our results show that both our distributed and centralized solutions significantly reduce the signaling between core and RAN compared to the traditional approach based on geographical proximity. As a result, both approaches significantly reduce the average handover procedure processing time. Moreover, by relying on locally available information, the distributed approach can quickly adapt to changes in the user movement patterns as they happen.

关键词： Handover Optimization 5G mobile communication Radio access networks Computational complexity 5G mobile communication distributed algorithms handover mobile radio mobility mobile radio mobility management

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Achieving Acceleration for distributed Economic Dispatch in Smart Grids Over Directed Networks

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2020年第3期7卷 1988-1999页

作者： Lu, Qingguo Liao, Xiaofeng Li, Huaqing Huang, Tingwen Southwest Univ Chongqing Key Lab Nonlinear Circuits & Intelligen Coll Elect & Informat Engn Chongqing 400715 Peoples R China Chongqing Univ Coll Comp Chongqing 400044 Peoples R China Texas A&M Univ Qatar Texas A&amp M Univ Qatar Doha 23874 Qatar

In this paper, the economic dispatch problem (EDP) in smart grids is investigated over a directed network, which concentrates on allocating the generation power among the generators to satisfy the load demands with minimal total generation cost while complying with all constraints of local generation capacity. Each generator possesses its own local generation cost, and the total generation cost is the sum of all local generation costs. To deal with EDP, most of the existing methods, such as strategy based on push-sum, surmount the unbalancedness induced by the directed network via employing column-stochastic weights, which might be infeasible in distributed implementation. In contrast, in order to be suitable for the directed network with row-stochastic weights, we develop a novel directed distributed Lagrangian momentum algorithm, named as D-DLM, which integrates distributed gradient tracking method with two types of momentum terms and utilizes non-uniform step-sizes with respect to the updates of Lagrangian multipliers. If the largest step-size and the maximum momentum coefficient are positive and sufficiently small, D-DLM can linearly allocate the optimal dispatch on condition that the generation costs are smooth and strongly convex. Finally, a variety of studies on EDP in smart grids are simulated.

关键词： Generators Smart grids Convergence Cost function Economics distributed algorithms distributed economic dispatch smart grids directed network distributed Lagrangian momentum algorithm linear convergence

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distributed H∞ Estimation Resilient to Biasing Attacks

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IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS 2020年第1期7卷 458-470页

作者： Ugrinovskii, Valery Univ New South Wales Canberra Sch Engn & Informat Technol Canberra ACT 2600 Australia

We consider the distributed H estimation problem with an additional requirement of resilience to biasing attacks. An attack scenario is considered, where an adversary misappropriates some of the observer nodes and injects biasing signals into observer dynamics. This paper proposes a procedure for the derivation of a distributed observer, which endows each node with an attack detector, which also functions as an attack compensating feedback controller for the main observer. Connecting these controlled observers into a network results in a distributed observer whose nodes produce unbiased robust estimates of the plant. We show that the gains for each controlled observer in the network can be computed in a decentralized fashion, thus reducing vulnerability of the network.

关键词： distributed algorithms control distributed attack detection estimation theory resilient estimation and control robust performance

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distributed Optimal Allocation with Quantized Communication and Privacy-Preserving Guarantees

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IFAC-PapersOnLine 2022年第41期55卷 64-70页

作者： Apostolos I. Rikos Jakob Nylöf Sebin Gracy Karl H. Johansson

In this paper, we analyze the problem of optimally allocating resources in a distributed and privacy-preserving manner. We propose a novel distributed optimal resource allocation algorithm with privacy-preserving guarantees, which operates over a directed communication network. Our algorithm converges in finite time and allows each node to process and transmit quantized messages. Our algorithm utilizes a distributed quantized average consensus strategy combined with a privacy-preserving mechanism. We show that the algorithm converges in finite-time, and we prove that, under specific conditions on the network topology, nodes are able to preserve the privacy of their initial state. Finally, to illustrate the results, we consider an example where test kits need to be optimally allocated proportionally to the number of infections in a region. It is shown that the proposed privacy-preserving resource allocation algorithm performs well with an appropriate convergence rate under privacy guarantees.

关键词： distributed algorithms Optimal Resource Allocation Privacy-Preservation distributed Optimization

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Synchronous distributed Greedy Weighted Graph Matching algorithms For Wireless Sensor Networks 4

Synchronous Distributed Greedy Weighted Graph Matching Algor...

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4th International Conference on Computer Science and Engineering (UBMK)

作者： Ersin, Ismail Ileri, Can Umut Dagdeviren, Orhan Ege Univ Int Comp Inst Izmir Turkey

ISBN: (纸本)9781728139647

Wireless Sensor Networks (WSN) consist of devices that can communicate with each other without using any fixed infrastructure. These devices can gather necessary information from the environment via their sensors and share collected data with each others. WSNs can be modelled with graphs (G (V, E)) where V is the set of vertices (nodes) and E is the set of edges. Graph theoretical structures such as graph matching can be used to solve various problems such as backup assignment in WSNs. With this aim, we first design a synchronous distributed weighted graph matching algorithm based on Hoepman's algorithm. After this the synchronous algorithm is improved by using overhearing method to design ICO algorithm. Proposed ICO algorithm aims to decrease the transmitted message count for graph matching operation by applying in-network processing. These algorithms are tested on various settings having different node counts and degrees in TOSSIM simulator by comparing with each other. The results of these extensive tests reveal us that ICO is more effective in terms of energy consumption and transmitted bytes.

关键词： Matching algorithms Hoepman Wireless Sensor Networks distributed algorithms

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