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IEEE 34th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Kriouile, Saad Tsilimantos, Dimitrios Giannakas, Theodoros Huawei Paris Res Ctr Paris France

ISBN: (纸本)9781665464833

To accommodate low latency and computation-intensive services, such as the Internet-of-Things (IoT), 5G networks are expected to have cloud and edge computing capabilities. To this end, we consider a generic network setup where devices, performing analytics-related tasks, can partially process a task and offload its remainder to base stations, which can then reroute it to cloud and/or to edge servers. To account for the potentially unpredictable traffic demands and edge network dynamics, we formulate the resource allocation as an online convex optimization problem with service violation constraints and allow limited communication between neighboring nodes. To address the problem, we propose an online distributed (across the nodes) primal-dual algorithm and prove that it achieves sublinear regret and violation;in fact, the achieved bound is of the same order as the best known centralized alternative. Our results are further supported using the publicly available Milano dataset.

关键词： Online convex optimization edge computing resource allocation distributed algorithms

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distributed algorithm for simulating dynamic interactions within a general cyber-physical system 11

Distributed algorithm for simulating dynamic interactions wi...

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11th Workshop on Modelling and Simulation of Cyber-Physical Energy Systems (MSCPES) Held as part of the Cyber-Physical Systems and Internet-of-Things Week

作者： Ilic, Marija Kosanic, Miroslav MIT EECS Dept 77 Massachusetts Ave Cambridge MA 02139 USA MIT LIDS 77 Massachusetts Ave Cambridge MA 02139 USA

ISBN: (纸本)9798350336825

In this paper we exploit the structure of dynamic models for general cyber-physical systems (CPS). Key to this structure is a unifying notion of an interaction variable between components/subsystems and the neighbouring sub-systems within a multi-layered CPS. The higher-level aggregate model derived in terms of unifying energy and power dynamics explicitly captures dynamic interactions of interest. In this paper this structure is utilised further to formulate a distributed interactive algorithm for simulating dynamic interactions and for aligning them according to generalised Tellegen's theorem. Proof of concept simulations are bench-marked against the centralised simulations of a simple DC circuit serving constant power load (CPL). Notably, the simulation results reflect the underlying physics and explicitly capture oscillations between neighbouring modules. This algorithm lends itself to multi-layered parallel implementation by means of minimal information exchange. As such, it supports simulating complex electric energy systems, in particular power-electronically controlled DC micro-grids, and, more generally multi-energy systems.

关键词： Energy dynamics structure of cyber-physical systems (CPS) distributed algorithms DC microgrids with constant power load generalised reactive power in time domain composition of complex algorithms

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distributed Fixed-Time Resource Allocation Algorithm for the General Linear Multi-Agent Systems

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2022年第6期69卷 2867-2871页

作者： Shi, Xiasheng Xu, Lei Yang, Tao Lin, Zhiyun Wang, Xuesong China Univ Min & Technol Engn Res Ctr Intelligent Control Underground Spac Minist Educ Xuzhou 221116 Jiangsu Peoples R China China Univ Min & Technol Sch Informat & Control Engn Xuzhou 221116 Jiangsu Peoples R China Northeastern Univ State Key Lab Synthet Automat Proc Ind Shenyang 110819 Peoples R China Southern Univ Sci & Technol Dept Elect & Elect Engn Shenzhen 518055 Peoples R China

This brief focuses on the distributed resource allocation problem (RAP) for a general linear heterogeneous multi-agent system (MAS), in which each agent adopts different structure parameters. By means of multi-agent consensus approach and symbolic-function-based fixed-time control theory, an initialization-free distributed resource allocation algorithm is designed. Moreover, the equality constraint is solved based on the proportional-integral (PI) control idea and the output of all agents tracks to the optimal solution within fixed-time. Finally, we reveal the effectiveness and fast convergence performance of our proposed algorithm by a simulation example.

关键词： Linear programming Convergence Resource management Optimization Eigenvalues and eigenfunctions distributed algorithms Circuits and systems Resource allocation fixed-time heterogenous initialization-free

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distributed Primal Decomposition for Large-Scale MILPs

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2022年第1期67卷 413-420页

作者： Camisa, Andrea Notarnicola, Ivano Notarstefano, Giuseppe Univ Bologna Dept Elect Elect & Informat Engn I-40126 Bologna Italy

This article deals with a distributed Mixed-Integer Linear Programming (MILP) setup arising in several control applications. Agents of a network aim to minimize the sum of local linear cost functions subject to both individual constraints and a linear coupling constraint involving all the decision variables. A key, challenging feature of the considered setup is that some components of the decision variables must assume integer values. The addressed MILPs are NP-hard, nonconvex, and large-scale. Moreover, several additional challenges arise in a distributed framework due to the coupling constraint, so that feasible solutions with guaranteed suboptimality bounds are of interest. We propose a fully distributed algorithm based on a primal decomposition approach and an appropriate tightening of the coupling constraint. The algorithm is guaranteed to provide feasible solutions in finite time. Moreover, asymptotic and finite-time suboptimality bounds are established for the computed solution. Monte Carlo simulations highlight the extremely low suboptimality bounds achieved by the algorithm.

关键词： Couplings Resource management distributed algorithms Heuristic algorithms Linear programming Approximation algorithms Task analysis Constraint-coupled optimization distributed optimization mixed-integer linear programming

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◊P-vCube: An Eventually Perfect Hierarchical Failure Detector for Asynchronous distributed Systems 12

◊P-vCube: An Eventually Perfect Hierarchical Failure Detect...

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12th Latin-American Symposium on Dependable and Secure Computing (LADC)

作者： Stein, Gabriela Rodrigues, Luiz Antonio Duarte, Elias Procopio, Jr. Arantes, Luciana Western Parana State Univ UNIOESTE Cascavel Parana Brazil Fed Univ Parana UFPR Dept Informat Curitiba Parana Brazil Sorbonne Univ UPMC CNRS INRIALIP6 Paris France

ISBN: (纸本)9798400708442

In this work, we introduce lozenge P-vCube, a push-based failure detector for asynchronous distributed systems. Processes running lozenge P-vCube are hierarchically organized on the vCube virtual topology, which presents several logarithmic properties. As there are no bounds on communication delays and process execution times, false suspicions may occur. To ensure eventual accuracy, a process exits the system when it learns that it has been suspected by another process or suspects every other process. We show that lozenge P-vCube guarantees completeness in any situation, and eventual accuracy if all correct processes remain strongly connected among themselves. We implemented the proposed algorithm using simulation and presented comparison results with the traditional all-test-all solution and a ring approach. The results demonstrate the trade-off between the speed of detecting actual failures and the number of messages used, as well as the scalability of lozenge P-vCube.

关键词： Dependability Fault-Tolerance Unreliable Failure Detectors Autonomic Systems distributed algorithms

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distributed Low-Effort Load Balancing in the Presence of Time-Delays 22

Distributed Low-Effort Load Balancing in the Presence of Tim...

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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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