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International Conference Parallel distributed Grid Computing

作者： Mann, Behnish Arvavid, Alex Univ Northern British Columbia Prince George BC Canada

ISBN: (纸本)9781479976836

distributed systems offer many features such as resource sharing, scalability, fault tolerance and reliability. Several distributed algorithms have been proposed in literature to solve fundamental problems such as mutual exclusion and leader election in distributed systems. When more than one algorithm is invented to solve the same problem particularly in asynchronous distributed systems, their performance is compared mostly based on the message complexity. This paper reviews the concept of message complexity and offers more clarity by studying the performance of the two most popular distributed algorithms - Ricart-Agrawala's algorithm and Raymond algorithm designed to solve the mutual exclusion problem. The paper has four main contributions (i) observes how the message complexity is understood and computed in the asynchronous distributed system so far and exposes its elusiveness;(ii) offers a more suitable definition of message complexity;(iii) briefly presents the simulator designed to study the performance of the distributed algorithms using the refined metric;and finally (iv) discusses about the simulation study to illustrate the significance and usefulness of the proposed metric.

关键词： communication complexity distributed algorithms Raymond algorithm Ricart-Agrawala algorithm distributed algorithm distributed system message complexity Algorithm design and analysis Complexity theory distributed algorithms Engines Measurement Network topology Topology distributed algorithms communication complexity distributed Systems Algorithm design and analysis Complexity theory Network topology Engines topology

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Impact of Stochastic Generation/Load Variations on distributed Optimal Energy Management in DC Microgrids for Transportation Electrification

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2022年第7期23卷 7196-7205页

作者： Xie, Siyu Nazari, Masoud H. Wang, Le Yi Yin, George Chen, Wen Wayne State Univ Dept Elect & Comp Engn Detroit MI 48202 USA Univ Connecticut Dept Math Storrs CT 06269 USA Wayne State Univ Div Engn Technol Detroit MI 48202 USA

This paper studies the impact of stochastic load variations on distributed optimal load tracking and allocation (OLTA) problems in cyber-physical DC microgrids (NIGs) for transportation electrification. Without load variations, the distributed optimization strategies developed in our earlier work can achieve convergence to global optimal solutions in a multiobjective optimization that balances fair load allocation and power loss reduction. Under persistent stochastic load variations, this paper develops distributed optimal strategies to track time-varying loads under noisy observations and establishes their convergence properties and error bounds. The limiting behavior of the errors characterizes the fundamental impact of the step size on irreducible errors due to conflict between attenuating observation noises and tracking load changes. Optimality conditions and algorithms for selecting the optimal step size are introduced to guide step size selection in practical applications. Simulation studies on real-world systems demonstrate the effectiveness of the proposed algorithms and validate the theoretical results.

关键词： DC microgrids optimal load distribution load variations distributed algorithms stochastic analysis

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Robust integral of sign of error-based distributed flocking control of double-integrator multi-agent systems with a varying virtual leader

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INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL 2022年第1期32卷 286-303页

作者： Wang, Ximing Sun, Jinsheng Wu, Zixing Li, Zhitao Nanjing Univ Sci & Technol Sch Automat Nanjing 210094 Peoples R China

This article investigates the flocking control problem of double-integrator multi-agent systems with a virtual leader subject to unknown external disturbances. A robust integral of sign of error (RISE) based control method is leveraged to design a distributed flocking controller with advantages of zero initial input value and continuous control input. By means of a new second-order differential virtual potential field function, and the navigational feedback from a virtual leader, the proposed flocking controller assures agents of velocity consensus with the virtual leader and a quasi alpha-lattice formation within a circular neighborhood centered on the virtual leader. Moreover, this algorithm guarantees collision avoidance and connectivity preservation of a proximity-induced communication topology. Numerical simulations of the algorithm are provided to illustrate the effectiveness of the proposed flocking algorithm.

关键词： distributed algorithms control flocking control networked control systems networks of autonomous agents

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Adapting Progressive Hedging for Solving Two-Stage Stochastic Programs Under a Peer-to-Peer Computing Network

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2024年第4期11卷 3611-3622页

作者： Du, Bin Kong, Nan Sun, Dengfeng Nanjing Univ Aeronaut & Astronaut Coll Automat Engn Nanjing 210016 Peoples R China Purdue Univ Weldon Sch Biomed Engn W Lafayette IN 47906 USA Purdue Univ Sch Aeronaut & Astronaut W Lafayette IN 47906 USA

Following recent technology advances and increasing applications in peer-to-peer network computing, we explore the potential of using decentralized optimization methods to solve notoriously hard stochastic programs. As the first attempt, we adapt the well-known progressive hedging (PH) method under a peer-to-peer computing network for solving two-stage stochastic programs efficiently. Similar to the existing parallel PH method, our decentralized variant assigns each node within the network to take charge of the computing tasks covering one or few scenarios, and thus it distributes the overall computational burden over the entire network. However, unlike the parallel PH method, the decentralized variant no longer needs a master node to realize central coordination, and thus it improves the scalability of the network computing as well. In this paper, we show the exact convergence of our decentralized method for solving two-stage stochastic programs with continuous variables subject to convex constraints. Further, we investigate several computational issues for the mixed-integer cases to improve the adaptation efficiency. Finally, the efficiency of our method is demonstrated through comparative computational experiments on a set of benchmark test instances.

关键词： Peer-to-peer computing Convergence Uncertainty Stochastic processes Standards Programming Inspection Computing networks distributed algorithms stochastic programs

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distributed Online Convex Optimization With an Aggregative Variable

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IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS 2022年第1期9卷 438-449页

作者： Li, Xiuxian Yi, Xinlei Xie, Lihua Inst Adv Study Dept Control Sci & Engn Coll Elect & Informat Engn Shanghai 201804 Peoples R China Tongji Univ Shanghai Res Inst Intelligent Autonomous Syst Shanghai 201804 Peoples R China KTH Royal Inst Technol Sch Elect Engn & Comp Sci Div Decis & Control Syst S-10044 Stockholm Sweden Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

This article investigates distributed online convex optimization in the presence of an aggregative variable without any global/central coordinators over a multiagent network. In this problem, each individual agent is only able to access partial information of time-varying global loss functions, thus requiring local information exchanges between neighboring agents. Motivated by many applications in reality, the considered local loss functions depend not only on their own decision variables, but also on an aggregative variable, such as the average of all decision variables. To handle this problem, an online distributed gradient tracking algorithm (O-DGT) is proposed with exact gradient information and it is shown that the dynamic regret is upper bounded by three terms: 1) a sublinear term;2) a path variation term;and 3) a gradient variation term. Meanwhile, the O-DGT algorithm is also analyzed with stochastic/noisy gradients, showing that the expected dynamic regret has the same upper bound as the exact gradient case. To our best knowledge, this article is the first to study online convex optimization in the presence of an aggregative variable, which enjoys new characteristics in comparison with the conventional scenario without the aggregative variable. Finally, a numerical experiment is provided to corroborate the obtained theoretical results.

关键词： Aggregative variable distributed algorithms dynamic regret multiagent networks online convex optimization

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distributed Negotiation for Reaching Agreement Among Reluctant Players in Cooperative Multiagent Systems

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2022年第9期67卷 4838-4845页

作者： Oliva, Gabriele Rikos, Apostolos, I Gasparri, Andrea Hadjicostis, Christoforos N. Univ Campus Biomed Roma Dept Engn Unit Automat Control I-00128 Rome Italy Royal Inst Technol Stockholm KTH Div Decis & Control Syst S-11428 Stockholm Sweden Univ Roma Tre Dept Engn I-00146 Rome Italy Univ Cyprus Dept Elect & Comp Engn CY-1678 Nicosia Cyprus

In this article, we propose a distributed negotiation framework that allows a set of cooperative agents to find a common ground with their neighbors while attempting to modify their initial opinion by the least possible amount. Based on such a framework, we develop a distributed agreement approach where the effort spent in the local agreement reflects the relevance of the agents in a weighted consensus process. In particular, we assume that players whose ideas happen to satisfactory mediate the standpoint of their interlocutors will end-up being more influential in the overall decision-making process. We conclude the article by applying the proposed methodology in the context of distributed data aggregation scenarios, as a way to mitigate the effect of outliers (e.g., faulty sensors).

关键词： Robot sensing systems Decision making Symmetric matrices Optimization Multi-agent systems distributed algorithms Topology distributed algorithms distributed optimization opinion dynamics cooperative multiagent systems

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Bidirectional Service Function Chain Embedding for Interactive Applications in Mobile Edge networks

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2024年第5期23卷 3964-3980页

作者： Tian, Fengsen Zhang, Xinglin Liang, Junbin Yang, Zheng South China Univ Technol Sch Comp Sci & Engn Guangzhou 510640 Peoples R China Guangxi Univ Sch Comp Elect & Informat Guangxi Key Lab Multimedia Commun & Network Techno Nanning 530003 Peoples R China Tsinghua Univ Sch Software Beijing 100190 Peoples R China

Bidirectional service function chain (BSFC) consists of multiple virtual network functions (VNFs). Through VNF deployment and link mapping, BSFCs can be embedded into resource-constrained mobile edge networks to provide low-latency network function services to users participating in interactive applications such as multi-player online games. Data from these users are routed through BSFCs to the edge node where the application is located for interaction and then returned to the users through the BSFCs, thus enabling synchronization among multiple users. However, the edge nodes or links have limited computing or bandwidth resources to serve only a fraction of users simultaneously. Therefore, the embedding decisions among different users can affect each other. In this paper, we propose a novel BSFC embedding strategy for interactive applications with the goal of minimizing computing and bandwidth resources while satisfying users' latency requirements. We first model the BSFC embedding problem as an integer nonlinear programming problem. Then, by closely examining the complexity of the problem, we propose a distributed algorithm based on game theory. We theoretically analyze the properties of the proposed algorithm and show that it can obtain a solution with a worst-case performance bound. Finally, extensive experiments show that the proposed algorithm outperforms several existing algorithms.

关键词： Bandwidth Routing Mobile computing Service function chaining Game theory distributed algorithms Delays Bidirectional service function chain game theory interactive applications mobile edge network VNF deployment

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Decentralized Generalized Approximate Message-Passing for Tree-Structured Networks

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IEEE TRANSACTIONS ON INFORMATION THEORY 2024年第10期70卷 7385-7409页

作者： Takeuchi, Keigo Toyohashi Univ Technol Dept Elect & Elect Informat Engn Toyohashi 4418580 Japan

Decentralized generalized approximate message-passing (GAMP) is proposed for compressed sensing from distributed generalized linear measurements in a tree-structured network. Consensus propagation is used to realize average consensus required in GAMP via local communications between adjacent nodes. Decentralized GAMP is applicable to all tree-structured networks that do not necessarily have central nodes connected to all other nodes. State evolution is used to analyze the asymptotic dynamics of decentralized GAMP for zero-mean independent and identically distributed Gaussian sensing matrices. The state evolution recursion for decentralized GAMP is proved to have the same fixed points as that for centralized GAMP when homogeneous measurements with an identical dimension in all nodes are considered. Furthermore, existing long-memory proof strategy is used to prove that the state evolution recursion for decentralized GAMP with the Bayes-optimal denoisers converges to a fixed point. These results imply that the state evolution recursion for decentralized GAMP with the Bayes-optimal denoisers converges to the Bayes-optimal fixed point for the homogeneous measurements when the fixed point is unique. Numerical results for decentralized GAMP are presented in the cases of linear measurements and clipping. As examples of tree-structured networks, a one-dimensional chain and a tree with no central nodes are considered.

关键词： Bayes methods distributed algorithms Ad hoc networks Convergence Sensors Symmetric matrices Signal processing algorithms Compressed sensing generalized approximate message-passing decentralized algorithms consensus propagation tree-structured networks state evolution

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A Novel Real-Time Coordinated Ridesharing Route Choice Mechanism

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2024年第5期25卷 3548-3560页

作者： Peng, Wang Du, Lili Univ Florida Dept Civil & Coastal Engn Gainesville FL 32603 USA

Ridesharing service, as a sustainable transportation mode, has gained great interest in both industry and academic fields. Existing TNC ridesharing services provide prescriptive solutions without coordinating riders' interactions and intentions on route choices. As a result, ridesharing services often end with ride-hailing services, and they are still under a relatively low usage rate. Motivated by this view, this study developed a real-time coordinated ridesharing route choice mechanism (CSM) for guiding riders' ridesharing route choices to fill this research and application gap. Specifically, this study modeled this CSM as a pure-strategy atomic fare-sharing game based on the assumption that every rider is selfish and tries to choose the best route to minimize his/her travel fare among multiple feasible candidate routes. An existing tree-generation algorithm was used to find the candidate routes for each rider. This study proved the existence of a Nash Equilibrium in this game by constructing a potential function and proving this game is a potential game. This study further developed a sequential updated distributed algorithm and proved its convergence to explore an equilibrium solution of the CSM. To address the scalability issue, this study created a coalition formation approach based on ridesharing potential, to separate riders into ridesharing coalitions and then independently implement the CSM for each ridesharing coalition. Our experiments illustrate that the coalition approach scales down the problem size of each CSM and dramatically improves the computation efficiency while maintaining the same level of system performance. More importantly, the CSM can significantly promote riders' usage of the ridesharing service by greatly saving their travel fares while satisfying their trip requirements.

关键词： Shared transport Games Real-time systems Routing distributed algorithms Delays Costs Coordinated ridesharing mechanism fare-sharing game coalition

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Dynamic Average Consensus of Time-Varying Signals With Known Frequency Components

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2024年第2期11卷 1971-1985页

作者： Xiao, Jinshuo Lin, Zongli Wan, Yan Shamash, Yacov A. Univ Virginia Charles L Brown Dept Elect & Comp Engn Charlottesville VA 22904 USA Univ Texas Arlington Dept Elect Engn Arlington TX 76019 USA SUNY Stony Brook Dept Elect & Comp Engn Stony Brook NY 11794 USA

The dynamic average consensus problem, a group of agents, each associated with a time-varying signal, reaching consensus at the average of these signals by their own distributed estimators that interact with each other through the communication network, finds many applications such as distributed estimation, formation control and sensor fusion. Many distributed estimators have been constructed that achieve either consensus precisely at the average of the signals or around it depending on the properties of the signals. In this paper, we revisit the dynamic average consensus problem in both the continuous-time and discrete-time settings. By utilizing the information on the frequency components of the signals, we construct distributed estimators that achieve accurate consensus at the average of the signals. We further establish that our distributed estimators are robust to the interruption of the network connectivity in the sense that connected subgroups of agents will continue to reach consensus around the average of all signals after an interruption occurs as along as the signals are bounded and the later the interruption occurs the more accurate the consensus will be. Numerical simulation is carried out to illustrate the theoretical results.

关键词： Heuristic algorithms Steady-state Topology Batteries Eigenvalues and eigenfunctions distributed algorithms Robustness distributed estimation dynamic average consensus multi-agent systems network connectivity robustness time-varying signals

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