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Robust distributed Monitoring of Traffic Flows

IEEE-ACM TRANSACTIONS ON NETWORKING 2021年第1期29卷 275-288页

作者： Demianiuk, Vitalii Gorinsky, Sergey Nikolenko, Sergey I. Kogan, Kirill Ariel Univ Dept Comp Sci IL-40700 Ariel Israel IMDEA Networks Inst NetEcon Res Grp Leganes 28918 Spain Steklov Inst Math St Petersburg 191023 Russia Natl Res Univ Higher Sch Econ St Petersburg 194100 Russia

Unrelenting traffic growth, device heterogeneity, and load unevenness create scalability challenges for traffic monitoring. In this paper, we propose Robust distributed Computation (RoDiC), a new approach that addresses these challenges by shifting a portion of the monitoring-task execution from an overloaded network element to another element that has spare resources. Moving the entire execution of the task away from the overloaded element might be infeasible because execution on multiple elements is inherent in the task or requires at least partial participation by the designated overloaded element. Furthermore, distributed execution of a stateful task has to be resilient to network noise in the form of packet reordering and loss. The RoDiC approach relies on two main principles of packet grouping and state overlap to support exact robust distributed monitoring of traffic flows under network noise. RoDiC uses an open-loop paradigm that does not add any control packets, communicates flow state in-band by appending few control bits to packets of monitored flows, and keeps measurement latency low. We apply RoDiC to the problem of flow-size computation and discuss how to instantiate our general technique for real-time packet-loss telemetry. The paper develops robust algorithms, proves their correctness and performance properties, and reports an evaluation driven by realistic traffic traces. The RoDiC algorithms successfully distribute the monitoring-task load while keeping the memory and computation overhead low.

关键词： Switches Monitoring Task analysis Measurement Telemetry Synchronization Technological innovation Traffic monitoring distributed algorithm stateful task network noise robust design flow-size computation real-time telemetry

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distributed multi-munition cooperative guidance based on clock synchronization for switching and noisy networks

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JOURNAL OF SUPERCOMPUTING 2021年第1期77卷 212-243页

作者： Yi, Sheng She, Xiaoyu Guo, Dong Zhao, Tong Yang, Chengwei Li, Jie Beijing Inst Technol Sch Mechatron Engn Beijing 100081 Peoples R China Beijing Special Electromech Res Inst Beijing 100081 Peoples R China Beihang Univ Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China Univ Chinese Acad Sci Sch Math Sci Beijing 100190 Peoples R China

This paper proposes a novel three-dimensional guidance method based on clock synchronization algorithms, creatively solving the problems of randomized change, non-connection and even communication outage caused by packet loss and delay in the co-guidance of loitering munitions. The proposed method is characterized by fast convergence of the aspect angle rate in the longitudinal plane, and the attack time constrains in the lateral plane. Normal accelerations on the two sub-planes are thereby calculated, so as to control the munitions' co-attack. Simulation experiments show that the proposed method can ensure reliable and stable asymptotic agreement of attack time expectation for the cooperative multiple munitions under the switching and noisy networks.

关键词： Loitering munition Cooperative guidance Clock synchronization distributed algorithm

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Multi-Agent Reinforcement Learning Based distributed Transmission in Collaborative Cloud-Edge Systems

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2021年第2期70卷 1658-1672页

作者： Xu, Chunmei Liu, Shengheng Zhang, Cheng Huang, Yongming Lu, Zhaohua Yang, Luxi South East Univ Sch Informat Sci & Engn Nanjing 210096 Peoples R China Purple Mt Labs Nanjing 211111 Peoples R China ZTE Corp Shenzhen 518057 Peoples R China State Key Lab Mobile Network & Mobile Multimedia Shenzhen 518057 Peoples R China

Millimeter-wave (mmWave) cloud-edge collaboration has emerged as an effective solution for low-latency transmission by harnessing the potentials of cloud and edge nodes (eNodes) as well as abundant bandwidth. In a mmWave dense network, centralized processing and coordinated multi-points processing require large amounts of signaling exchange overhead, which in turn increase the latency. As such, distributed mechanism is demanded. In this paper, we investigate joint user scheduling and beam selection strategies for eNodes and formulate the problem as a constrained Markov decision process. The objective and constraints are long-term average network delay cost minimization and instantaneous quality of service (QoS) guarantee for each user equipment. To update the distributed strategies, we apply the multi-agent reinforcement learning technique and propose a hybrid learning framework by extending the actor-critic model, where centralized training and decentralized execution are implemented. We utilize the Lagrange technique to design the reward functions. Additionally, a novel actor network architecture and an exploration scheme are proposed. Simulation results validate the effectiveness of the proposed intelligent distributed algorithm with a high degree of scalability, and show superior performance in terms of long-term average network delay cost and QoS satisfaction rates compared with other methods.

关键词： Collaboration Cloud computing Interference Array signal processing Quality of service Delays Wireless communication Cloud-edge collaboration user scheduling beam selection distributed algorithm multi-agent reinforcement learning (MARL)

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distributed Optimal Contract for Data Rewarding with Network Effects

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IEEE Transactions on Control of Network Systems 2024年

作者： Baneshi, Alireza Montazeri, Mina Kebriaei, Hamed University of Tehran School of Electrical and Computer Engineering College of Engineering Tehran Iran Swiss Federal Laboratories for Materials Science and Technology Urban Energy Systems Laboratory Dübendorf Switzerland School of Computer Science Tehran Iran

Data rewarding is a novel business model that leads to an economic trend in mobile networks. In this scheme, the advertiser incentivizes mobile users (MUs) to watch advertisement (ads) and, in return, receive a reward in the form of mobile data. In this work, we model the interaction between an advertiser who has asymmetric information about MUs and MUs who are connected to each other under a network, using the contract theory approach. We obtain the necessary and sufficient conditions for an optimal and practical contract to motivate MUs to participate in the data rewarding scheme and encourage them to declare their private information truthfully. The formulation of this contract is a non-convex-constrained optimization problem. Using lemmas and propositions, we reformulate the initial optimization problem that is challenging to solve as an optimization problem with convex constraints and prove that these two problems are equivalent. Then, with the help of a distributed and non-convex algorithm, we obtain the amount of ads demand and incentive reward. © 2014 IEEE.

关键词： asymmetric information contract theory Data rewarding distributed algorithm incentive compatibility

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A Unified Approach for Finite-Time Global Stabilization of Affine, Rigid, and Translational Formation

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2022年第4期67卷 1869-1881页

作者： Lin, Yanjun Lin, Zhiyun Sun, Zhiyong Anderson, Brian D. O. Zhejiang Univ Coll Elect Engn Hangzhou 310027 Peoples R China Southern Univ Sci & Technol Shenzhen Peoples R China Hangzhou Dianzi Univ Artificial Intelligence Inst Sch Automat Hangzhou 310018 Peoples R China Eindhoven Univ Technol Dept Elect Engn NL-5612 AZ Eindhoven Netherlands Australian Natl Univ Sch Engn Acton ACT 2601 Australia

This article studies the multiagent control problem for affine, rigid, and translational formation, with the aim of developing a unified distributed control strategy for global and finite-time convergence. Global stabilization of rigid formation in arbitrary dimensional spaces still remains open and challenging. This article provides a general solution to this open problem based on the sliding mode control idea. The control law design consists of two parts: the main control force regulates the trajectories of all agents to reach a sliding surface defined by an affine formation space in finite time and remain in it thereafter;the extra control force governs certain chosen leader agents towards the desired formation in the sliding surface. The article then presents in detail two approaches for designing the extra control force, one based on distance constraints and the other based on relative position constraints. For the first time, the proposed sliding mode formation control laws solve the open problem of (almost) global and finite-time stabilization of affine, rigid, and translational formations in any dimensional space. Simulation results are provided to illustrate the effectiveness of the proposed control schemes.

关键词： Aerospace electronics Convergence Shape Force Decentralized control Sun Manifolds Affine formation distributed algorithm formation control multiagent systems

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Weakly Byzantine Gathering with a Strong Team

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2022年第3期E105D卷 541-555页

作者： Hirose, Jion Nakamura, Junya Ooshita, Fukuhito Inoue, Michiko Nara Inst Sci & Technol Ikoma 6300192 Japan Toyohashi Univ Technol Toyohashi Aichi 4418580 Japan

We study the gathering problem requiring a team of mobile agents to gather at a single node in arbitrary networks. The team consists of k agents with unique identifiers (IDs), and f of them are weakly Byzantine agents, which behave arbitrarily except falsifying their identifiers. The agents move in synchronous rounds and cannot leave any information on nodes. If the number of nodes n is given to agents, the existing fastest algorithm tolerates any number of weakly Byzantine agents and achieves gathering with simultaneous termination in O(n(4). vertical bar Lambda(good)vertical bar . X(n)) rounds, where vertical bar Lambda(good)vertical bar is the length of the maximum ID of non-Byzantine agents and X(n) is the number of rounds required to explore any network composed of n nodes. In this paper, we ask the question of whether we can reduce the time complexity if we have a strong team, i.e., a team with a few Byzantine agents, because not so many agents are subject to faults in practice. We give a positive answer to this question by proposing two algorithms in the case where at least 4f(2) + 9f + 4 agents exist. Both the algorithms assume that the upper bound N of n is given to agents. The first algorithm achieves gathering with non-simultaneous termination in O((f + vertical bar Lambda(good)vertical bar) . X(N)) rounds. The second algorithm achieves gathering with simultaneous termination in O((f + vertical bar Lambda(all)vertical bar) . X(N)) rounds, where vertical bar Lambda(all)vertical bar is the length of the maximum ID of all agents. The second algorithm significantly reduces the time complexity compared to the existing one if n is given to agents and vertical bar Lambda(all)vertical bar = O(vertical bar Lambda(good)vertical bar) holds.

关键词： distributed algorithm deterministic algorithm mobile agents gathering Byzantine faults

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Operationally-Safe Peer-to-Peer Energy Trading in Distribution Grids: A Game-Theoretic Market-Clearing Mechanism

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IEEE TRANSACTIONS ON SMART GRID 2022年第4期13卷 2897-2907页

作者： Belgioioso, Giuseppe Ananduta, Wicak Grammatico, Sergio Ocampo-Martinez, Carlos Swiss Fed Inst Technol Automat Control Lab CH-8092 Zurich Switzerland Delft Univ Technol Delft Ctr Syst & Control NL-2628 CD Delft Netherlands Univ Politecn Cataluna Automat Control Dept Barcelona 08028 Spain

In future distribution grids, prosumers (i.e., energy consumers with storage and/or production capabilities) will trade energy with each other and with the main grid. To ensure an efficient and safe operation of energy trading, in this paper, we formulate a peer-to-peer energy market of prosumers as a generalized aggregative game, in which a network operator is responsible to enforce the operational constraints of the system. We design a distributed market-clearing mechanism with convergence guarantee to an economically-efficient, strategically-stable, and operationally-safe configuration (i.e., a variational generalized Nash equilibrium). Numerical studies on the IEEE 37-bus testcase show the scalability of the proposed approach and suggest that active participation in the market is beneficial for both prosumers and the network operator.

关键词： Costs Reliability Peer-to-peer computing Couplings Automatic voltage control Distribution networks Production Prosumers energy management distributed algorithm generalized Nash equilibrium

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Online Multicell Coordinated MIMO Wireless Network Virtualization With Imperfect CSI

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2022年第12期21卷 10455-10471页

作者： Wang, Juncheng Liang, Ben Dong, Min Boudreau, Gary 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

We consider online coordinated precoding design for downlink wireless network virtualization (WNV) in a multi-cell multiple-input multiple-output (MIMO) network with imperfect channel state information (CSI). In our WNV framework, an infrastructure provider (InP) owns each base station that is shared by several service providers (SPs) oblivious of each other. The SPs design their precoders as virtualization demands for user services, while the InP designs the actual precoding solution to meet the service demands from the SPs. Our aim is to minimize the long-term time-averaged expected precoding deviation over MIMO fading channels, subject to both per-cell long-term and short-term transmit power limits. We propose an online coordinated precoding algorithm for virtualization, which provides a fully distributed semi-closed-form precoding solution at each cell, based only on the current imperfect CSI without any CSI exchange across cells. Taking into account the two-fold impact of imperfect CSI on both the InP and the SPs, we show that our proposed algorithm is within an $O(\delta)$ gap from the optimum over any time horizon, where $\delta $ is a CSI inaccuracy indicator. Simulation results validate the performance of our proposed algorithm under two commonly used precoding techniques in a typical urban micro-cell network environment.

关键词： Precoding Virtualization MIMO communication Indium phosphide III-V semiconductor materials Optimization Downlink Wireless network virtualization massive MIMO imperfect CSI coordinated precoding Lyapunov optimization distributed algorithm

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Grid exploration by a swarm of autonomous robots with minimum repetitions

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THEORETICAL COMPUTER SCIENCE 2022年 933卷 67-87页

作者： Sardar, Madhumita Das, Deepanwita Mukhopadhyaya, Srabani Haji Md Serafat Mondal Govt Polytech Comp Sci & Technol Birbhum 731202 W Bengal India Natl Inst Technol Comp Sci & Engn Mahatma Gandhi Ave Durgapur 713209 W Bengal India Birla Inst Technol Lalpur Extens Ctr Comp Sci & Engn Ranchi 834001 Bihar India

We address the terminating exploration problem where a team of k autonomous robots explores a grid such that each node of the grid is visited at least once and all robots stop moving when the task is completed. Robots considered for the task are anonymous, asynchronous, oblivious and non-communicating that have unlimited visibility and a pebble each. Visiting a node more than once by the robots during exploration is a waste of energy due to energy constraints. In this work we aim at minimizing the total number of wasteful repeated visits of the nodes that occur during exploration. Our proposed algorithm explores a grid with minimum repeated visits of nodes. (c) 2022 Elsevier B.V. All rights reserved.

关键词： distributed algorithm Swarm Exploration Discrete domain

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distributed Successive Convex Approximation for Nonconvex Economic Dispatch in Smart Grid

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2021年第12期17卷 8288-8298页

作者： Xu, Bowen Guo, Fanghong Zhang, Wen-An Wang, Wei Wen, Changyun Li, Zhengguo Zhejiang Univ Technol Dept Automat Hangzhou 310023 Peoples R China Beihang Univ Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China Beihang Univ Beijing Adv Innovat Ctr Big Data & Brain Comp Beijing 100191 Peoples R China Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore Agcy Sci Technol & Res SRO Dept Inst Infocomm Res Singapore 138632 Singapore

This article presents a distributed consensus-based successive convex approximation (DSCA) algorithm to solve nonconvex nondifferentiable economic dispatch (ED) problems. The ED model formulated incorporates generation constraints, valve-point effects, and multiple fuel types. A perturbation technique enables the proposed DSCA to tackle such a nondifferentiable and nonconvex optimization, which paves the way to solving more complicated optimization problems that occur in practical applications. The local generation constraint is taken care by a local surrogate convex optimization directly. The global equality constraint is handled based on a consensus protocol, where the local generation-demand mismatch among all dispatchable generators (DGs) is shared in a distributed manner. As a result, the power distribution of DGs is updated, and the generation cost is minimized. Several case studies show that the proposed DSCA algorithm can achieve superior ED solutions and computational efficiency over existing nonconvex optimization algorithms.

关键词： Approximation algorithms Smart grids Perturbation methods Heuristic algorithms Fuels Informatics Generators distributed algorithm economic dispatch (ED) nonconvex optimization smart grid successive convex approximation (SCA)

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