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22nd World Congress of the International Federation of Automatic Control (IFAC)

作者： Charalambous, Themistoklis Panzieri, Stefano Oliva, Gabriele Univ Cyprus Sch Engn Dept Elect & Comp Engn Nicosia Cyprus Univ Roma Tre Via Vasca Navale 79 I-00146 Rome Italy Univ Campus Biomed Roma Dept Engn Unit Automat Control Rome Italy

ISBN: (纸本)9781713872344

In this paper, we investigate the problem of distributed load balancing under network capacity constraints, where the participating agents cooperate with the aim of jointly minimizing both the workload disparity among them as well as the overall workload transfer. Classical approaches for asymptotic convergence to the global optimum in a distributed fashion typically assume timely exchange of information between neighboring agents of a given multi-agent system. This assumption is not necessarily valid in practical settings due to non-commensurate (heterogeneous) communication and processing delays that might affect transmissions at different times. More specifically, we consider what effect multiple heterogeneous time-varying delays, among the agents can have on the distributed load balancing problem. We show that the distributed load balancing problem under bounded heterogeneous time-varying delays is globally asymptotically stable, but the rate of convergence is affected. Bounds on the convergence rate are provided with respect to an upper bound on the delays. Simulation examples are provided to show the validity and performance of our theoretical results. Copyright (c) 2023 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)

关键词： distributed load balancing time-delays distributed algorithms minimum effort

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Faster Deterministic distributed MIS and Approximate Matching 2023

Faster Deterministic Distributed MIS and Approximate Matchin...

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55th Annual ACM Symposium on Theory of Computing (STOC) part of the ACM Federated Computing Research Conference (FCRC)

作者： Ghaffari, Mohsen Grunau, Christoph MIT Cambridge MA 02139 USA Swiss Fed Inst Technol Zurich Switzerland

ISBN: (纸本)9781450399135

We present an (O) over tilde (log(2) n) round deterministic distributed algorithm for the maximal independent set problem. By known reductions, this round complexity extends also to maximal matching, Delta+ 1 vertex coloring, and 2 Delta- 1 edge coloring. These four problems are among the most central problems in distributed graph algorithms and have been studied extensively for the past four decades. This improved round complexity comes closer to the (Omega) over tilde (log n) lower bound of maximal independent set and maximal matching [Balliu et al. FOCS '19]. The previous best known deterministic complexity for all of these problems was Phi (log(3) n). Via the shattering technique, the improvement permeates also to the corresponding randomized complexities, e.g., the new randomized complexity of. + 1 vertex coloring is now (O) over tilde (log(2) log n) rounds. Our approach is a novel combination of the previously known (and seemingly orthogonal) two methods for developing fast deterministic algorithms for these problems, namely global derandomization via network decomposition (see e.g., [Rozhon, Ghaffari STOC'20;Ghaffari, Grunau, Rozhon SODA'21;Ghaffari et al. SODA'23]) and local rounding of fractional solutions (see e.g., [Fischer DISC'17;Harris FOCS'19;Fischer, Ghaffari, Kuhn FOCS'17;Ghaffari, Kuhn FOCS'21;Faour et al. SODA'23]). We consider a relaxation of the classic network decomposition concept, where instead of requiring the clusters in the same block to be non-adjacent, we allow each node to have a small number of neighboring clusters. We also show a deterministic algorithm that computes this relaxed decomposition faster than standard decompositions. We then use this relaxed decomposition to signiffcantly improve the integrality of certain fractional solutions, before handing them to the local rounding procedure that now has to do fewer rounding steps.

关键词： distributed algorithms maximal independent set matching derandomization rounding

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Secure Computation Meets distributed Universal Optimality 64

Secure Computation Meets Distributed Universal Optimality

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64th Annual IEEE Symposium on the Foundations of Computer Science (FOCS)

作者： Parter, Merav Weizmann Inst Sci Dept Comp Sci & Appl Math Rehovot Israel

ISBN: (纸本)9798350318944

We present a new algorithmic approach to distributed secure algorithms that is based on combining two independent lines of research: secure computation and distributed universal optimality. Our end result provides round-efficient distributed algorithms that protect the privacy of the graph vertices against a (possibly large) coalition of semi-honest adversaries. Secure Computation: The notion of perfect privacy dates back to Yao [FOCS '82], and has been extensively addressed by the Cryptographic community over the years. Most of the prior work considers the Multi-Party-Communication (MPC) model, in which the parties are fully connected. Considerably less is known on the (round) complexity of secure algorithms for general graphs, especially under the classical message passing models, such as the CONGEST model. For any biconnected D-diameter graph, a recent line of works [Parter and Yogev, SODA 19, ICALP 19, PODC 19] presented a simulation result that protects against a single semi-honest corruption, by paying an overhead of D . poly(Delta) CONGEST rounds, where Delta is the maximum degree. Due to an inherent structural barrier, the generalization of the current framework to handling f corruptions, provably leads to an overhead of O(Delta D)(Theta(f)) rounds. This can also be shown to be tight for the class of store-and-forward algorithms(1). Secure Computation & Universal Optimality. We present an improved framework for secure computation which bypasses the current exponential in f barrier. For every graph G = (V, E) with vertex-connectivity (Omega) over tilde (f), our simulation provides a round overhead of poly(Delta) . (o) over capO(SQ(G)).(2) The graph measure SQ(G) (Shortcut Quality) captures the universal optimal complexity of many network optimization tasks in the (non-secure) CONGEST model, as demonstrated in a recent breakthrough result of [Haeupler, Wajc and Zuzic, STOC 2021]. We are hopeful that the extended graph-theoretic machinery provided in this paper

关键词： Perfect security CONGEST distributed algorithms

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Analyzing Malicious Data Injection Attacks on distributed Optimal Power Flow algorithms

Analyzing Malicious Data Injection Attacks on Distributed Op...

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Annual North-American Power Symposium

作者： Mohannad Alkhraijah Rachel Harris Samuel Litchfield David Huggins Daniel K. Molzahn Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Georgia Tech Research Institute Atlanta GA USA

ISBN: (纸本)9781665499224

The rapid growth of distributed energy resources motivates the application of distributed optimization algorithms for solving optimal power flow (OPF) problems. Using distributed optimization to solve OPF problems requires repeated data sharing between agents responsible for different regions of the power system. The performance of distributed optimization algorithms depends on the integrity of the shared data and the communications between the agents. This paper investigates the vulnerability of a distributed algorithm called Auxiliary Problem Principle (APP) with respect to cyberattacks on the communications between the agents. We propose cyberattack models that manipulate the shared data between neighboring agents to achieve an objective such as driving the algorithm to converge to a suboptimal solution. We investigate the convergence characteristics of the APP algorithm in the context of the DC optimal power flow (DC OPF) problem with and without manipulating the shared data. Last, we demonstrate how trained neural networks can provide highly accurate attack detection.

关键词： Threat modeling Scalability distributed databases Power systems Pattern recognition Computer crime distributed algorithms

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Nash Equilibrium Seeking for Multi-Cluster Games of Second-Order Systems Over Weight-Unbalanced Digraphs

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2024年第4期71卷 2209-2213页

作者： Nian, Xiaohong Liu, Dongxin Li, Fan Cent South Univ Sch Automat Key Lab Inst Cluster Unmanned Syst Changsha 410083 Peoples R China

In this brief, the multi-cluster game of second-order systems over weight-unbalanced directed graphs is studied for the first time, where each local cost function depends on the decisions of all participants. A novel algorithm is designed based on state feedback and left eigenvector estimation under the partial information setting, where each agent only knows its own local decision and cost function information. It is demonstrated by Lyapunov stability theory that the algorithm can converge to the Nash equilibrium (NE) with the weight-unbalanced directed graphs. Finally, the effectiveness of the algorithm is illustrated by a numerical simulation.

关键词： Games Heuristic algorithms distributed algorithms Directed graphs Clustering algorithms Nash equilibrium Laplace equations distributed algorithms weight-unbalanced digraphs second-order multi-agent systems

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Steam computing paradigm: Cross-layer solutions over cloud, fog, and edge computing

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IET WIRELESS SENSOR SYSTEMS 2024年第5期14卷 157-180页

作者： Mchergui, Abir Hajlaoui, Rejab Moulahi, Tarek Alabdulatif, Abdulatif Lorenz, Pascal Univ Gabes Higher Inst Management Dept Comp Gabes Tunisia Univ Besancon Femto st Besancon France Qassim Univ Coll Comp Dept Informat Technol Buraydah Saudi Arabia Kairouan Univ Dept Math & Comp Sci FSTSBZ Kairouan Tunisia Qassim Univ Coll Comp Dept Comp Sci Buraydah Saudi Arabia Univ Haute Alsace Colmar Colmar France Rue Jilani Habib Gabes 6002 Tunisia

Conventional infrastructures based on the cloud are not sufficient for the emerging Internet of Things (IoT) applications requirements. Many big problems are shortcomings, especially in terms of network bandwidth and latency. Throughout recent years, the idea to relieve fog computing and edge computing was suggested by bringing data processing capacities closer to these limits to the edge of the network. The authors assume that the full potential of IoT will, in many cases, only be activated by the combination of cloud, fog, and edge computing in a new computing paradigm, given IoT growth and development forecasts. This article discusses the possibility and need for such a paradigm by introducing steam computing as a new distributed type of computing using cloud, fog, and edge utilities to carry out data processing and storage. The authors treat steam computing through four planes: security and privacy plane, data analytics and fault tolerance plane and deployment and test beds plane. Finally, the authors focus on the open issues and future trends in steam computing.

关键词： cloud computing data analysis distributed algorithms Internet of Things security of data

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Maximum Length-Constrained Flows and Disjoint Paths: distributed, Deterministic, and Fast 2023

Maximum Length-Constrained Flows and Disjoint Paths: Distrib...

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55th Annual ACM Symposium on Theory of Computing (STOC) part of the ACM Federated Computing Research Conference (FCRC)

作者： Haeupler, Bernhard Hershkowitz, D. Ellis Saranurak, Thatchaphol Swiss Fed Inst Technol Zurich Switzerland Carnegie Mellon Univ Pittsburgh PA 15213 USA Univ Michigan Ann Arbor MI USA

ISBN: (纸本)9781450399135

Computing routing schemes that support both high throughput and low latency is one of the core challenges of network optimization. Such routes can be formalized as h-length flows which are defined as flows whose flow paths have length at most h. Many well-studied algorithmic primitives-such as maximal and maximum length-constrained disjoint paths-are special cases of h-length flows. Likewise the optimal h-length flow is a fundamental quantity in network optimization, characterizing, up to poly-log factors, how quickly a network can accomplish numerous distributed primitives. In this work, we give the first efficient algorithms for computing (1 - epsilon)-approximate h-length flows that are nearly "as integral as possible." We give deterministic algorithms that take (O) over tilde (poly(h, 1/epsilon)) parallel time and (O) over tilde (poly(h, 1/epsilon) center dot 2(O) (root log n)) distributed CONGEST time. We also give a CONGEST algorithm that succeeds with high probability and only takes (O) over tilde (poly(h, 1/epsilon)) time. Using our h-length flow algorithms, we give the first efficient deterministic CONGEST algorithms for the maximal disjoint paths problem with length constraints-settling an open question of Chang and Saranurak (FOCS 2020)-as well as essentially-optimal parallel and distributed approximation algorithms for maximum length-constrained disjoint paths. The former greatly simplifies deterministic CONGEST algorithms for computing expander decompositions. We also use our techniques to give the first efficient and deterministic (1-epsilon)-approximation algorithms for bipartite b-matching in CONGEST. Lastly, using our flow algorithms, we give the first algorithms to efficiently compute h-length cutmatches, an object at the heart of recent advances in length-constrained expander decompositions.

关键词： length-bounded flows hop-bounded flows distributed algorithms parallel algorithms flow rounding cycle covers b-matching

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distributed MIS with Low Energy and Time Complexities 23

Distributed MIS with Low Energy and Time Complexities

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

作者： Ghaffari, Mohsen Portmann, Julian MIT Cambridge MA 02139 USA Swiss Fed Inst Technol Zurich Switzerland

ISBN: (纸本)9798400701214

We present randomized distributed algorithms for the maximal independent set problem (MIS) that, while keeping the time complexity nearly matching the best known, reduce the energy complexity substantially. These algorithms work in the standard CONGEST model of distributed message passing with O (log n) bit messages. The time complexity measures the number of rounds in the algorithm. The energy complexity measures the number of rounds each node is awake;during other rounds, the node sleeps and cannot perform any computation or communications. Our first algorithm has an energy complexity of O (log log n) and a time complexity of O ( log(2) n). Our second algorithm is faster but slightly less energy-efficient: it achieves an energy complexity of O (log(2) log n) and a time complexity of O (log n center dot log log n center dot log* n). Thus, this algorithm nearly matches the O (log n) time complexity of the state-of-the-art MIS algorithms while significantly reducing their energy complexity from O (log n) to O ( log(2) log n).

关键词： Maximal Independent Set MIS sleeping model worst-case energy complexity energy complexity awake complexity round complexity energy-efficiency distributed algorithms

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A distributed stochastic first-order method for strongly concave-convex saddle point problems 62

A distributed stochastic first-order method for strongly con...

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62nd IEEE Conference on Decision and Control (CDC)

作者： Qureshi, Muhammad, I Khan, Usman A. Tufts Univ Medford MA 02155 USA

ISBN: (纸本)9798350301243

In this paper, we propose a distributed stochastic first-order method for saddle point problems over strongly connected graphs. Existing methods generally suffer from a steady-state error that arises due to the heterogeneous nature of data distribution (captured by the local versus global cost gaps) and the variance of the stochastic gradients. We propose GT-SGDA, a distributed stochastic gradient descent ascent method that uses network-level gradient tracking to eliminate the steady-state error component due to the local versus global cost gap. We show that GT-SGDA converges linearly to an error ball around the unique saddle point for sufficiently small constant step-sizes when the global cost is strongly concave-convex (a necessary condition for the existence of a unique saddle point). Moreover, we show that the size of this error ball depends on the variance of the stochastic gradients. We provide numerical experiments to illustrate the convergence properties of GT-SGDA for different applications and highlight the significance of gradient tracking. We also show the performance of GT-SGDA for training modern applications like distributed generative adversarial networks (GANs).

关键词： Stochastic min-max optimization first-order methods saddle point problems distributed algorithms

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A Fully distributed Robust Secure Consensus Protocol for Linear Multi-Agent Systems

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2022年第7期69卷 3264-3268页

作者： Wang, Jingyao Li, Yige Duan, Zhisheng Zeng, Jianping Xiamen Univ Dept Automat Xiamen 361104 Peoples R China Jilin Univ State Key Lab Automot Simulat & Control Changchun 130025 Peoples R China Peking Univ Dept Mech & Engn Sci Beijing 100871 Peoples R China

This brief analyzes the robust secure consensus control problem for linear multi-agent systems under random Denial-of-Service (DoS) attacks and external disturbances. When agents communicate with its neighbors, a malicious attacker randomly carries out DoS attacks to certain communication channels in the network, thereby causing the communication topology to be Markovian switching. Solely depending on the immediate partial information per node rather than global information, a fully distributed robust secure consensus protocol is put forward under DoS attacks and external disturbances by using the Lyapunov function analysis. A simulation case of leader-follower formation is taken to explain the efficiency of the consensus algorithm.

关键词： Topology Denial-of-service attack Consensus protocol Switches Circuits and systems Network topology Markov processes Denial-of-service (DoS) attacks distributed algorithms Markovian switching topologies multi-agent systems robustness

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