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distributed algorithms for Spectral and Energy-Efficiency Maximization of K-User Interference Channels

IEEE ACCESS 2021年 9卷 96948-96963页

作者： Soleymani, Mohammad Santamaria, Ignacio Schreier, Peter J. Univ Paderborn Signal & Syst Theory Grp D-33098 Paderborn Germany Univ Cantabria Dept Commun Engn Santander 39005 Spain

In this paper, we propose a cooperative distributed framework to optimize a variety of rate and energy-efficiency (EE) utility functions, such as the minimum-weighted rate or the global EE, for the K-user interference channel. We focus on the single-input multiple-output (SIMO) case, where each user, based solely on local channel state information (CSI) and limited exchange information from other users, optimizes its transmit power and receive beamformer, although the framework can also be extended to the multiple-output multiple-input (MIMO) case. The distributed framework combines an alternating optimization approach with majorization-minimization (MM) techniques, thus ensuring convergence to a stationary point of the centralized cost function. Closed-form power update rules are obtained for some utility functions, thus obtaining very fast convergence algorithms. The receivers treat interference as noise (TIN) and apply the beamformers that maximize the signal-to-interference-plus-noise (SINR). The proposed cooperative distributed algorithms are robust against channel variations and network topology changes and, as our simulation results suggest, they perform close to the centralized solution that requires global CSI. As a benchmark, we also study a non-cooperative distributed framework based on the so-called "signal-to-leakage-plus-noise ratio" (SNLR) that further reduces the overhead of the cooperative version.

关键词： distributed algorithms energy-efficiency region fairness rate global energy efficiency majorization minimization SIMO systems sum-rate maximization

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distributed algorithms for reaching consensus on general functions

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AUTOMATICA 2008年第3期44卷 726-737页

作者： Cortes, Jorge Univ Calif San Diego Dept Mech & Aerosp Engn San Diego CA 92093 USA

This paper presents analysis and design results for distributed consensus algorithms in multi-agent networks. We consider continuous consensus functions of the initial state of the network agents. Under mild smoothness assumptions, we obtain necessary and sufficient conditions characterizing any algorithm that asymptotically achieves consensus. This characterization is the building block to obtain various design results for networks with weighted, directed interconnection topologies. We first identify a class of smooth functions for which one can synthesize in a systematic way distributed algorithms that achieve consensus. We apply this result to the family of weighted power mean functions, and characterize the exponential convergence properties of the resulting algorithms. We establish the validity of these results for scenarios with switching interconnection topologies. Finally, we conclude with two discontinuous distributed algorithms that achieve, respectively, max and min consensus in finite time. (C) 2007 Elsevier Ltd. All rights reserved.

关键词： cooperative control network consensus distributed algorithms balanced directed graphs weighted power means

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distributed algorithms for Multirobot Task Assignment With Task Deadline Constraints

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2015年第3期12卷 876-888页

作者： Luo, Lingzhi Chakraborty, Nilanjan Sycara, Katia Carnegie Mellon Univ Sch Comp Sci Inst Robot Pittsburgh PA 15213 USA SUNY Stony Brook Dept Mech Engn Stony Brook NY 11794 USA

We present distributed algorithms for multirobot task assignment where the tasks have to be completed within given deadlines. Each robot has a limited battery life and thus there is an upper limit on the amount of time that it has to perform tasks. Performing each task requires certain amount of time (called the task duration) and each robot can have different payoffs for the tasks. Our problem is to assign the tasks to the robots such that the total payoff is maximized while respecting the task deadline constraints and the robot's battery life constraints. Our problem is NP-hard since a special case of our problem is the classical generalized assignment problem (which is NP-hard). There are no known algorithms (distributed or centralized) for this problem with provably good guarantees of performance. We present a distributed algorithm for solving this problem and prove that our algorithm has an approximation ratio of 2. For the special case of constant task duration we present a distributed algorithm that is provably almost optimal. Our distributed algorithms are polynomial in the number of robots and the number of tasks. We also present simulation results to depict the performance of our algorithms. Note to Practitioners-In this paper, we present provably good multirobot task assignment algorithms, while considering practical constraints like task deadlines and limited battery life of robots. Such constraints are relevant in many applications including parts movement by robots in manufacturing, delivery of goods by unmanned vehicles, and search and rescue operations. Our solution is applicable to a group of heterogeneous robots with different suitability (i.e., payoffs) for different tasks. Our distributed approach is independent of the underlying robot communication network topology, and thus can be applied to a wide range of robot network deployments. Finally, our approach is easy to implement, has low communication requirements, and it is scalable, since its ru

关键词： Auction algorithms distributed algorithms generalized assignment multi-agent coordination multirobot task allocation task deadline

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distributed algorithms for the constrained routing problem in computer networks

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COMPUTER COMMUNICATIONS 1998年第16期21卷 1476-1485页

作者： Hung, YC Soochow Univ Dept Comp & Informat Sci Taipei Taiwan

The quickest path problem is possibly the most important problem for data routing in computer networks. The quickest path problem is to find quickest paths in a computer network to transmit a given amount of data with minimal transmission time. The selection of quickest paths depends on both the characteristics of the computer network and the amount of data to be transmitted. In addition, if the quickest paths are required to go through a specified path, then the restricted problem is called the constrained quickest path problem. In this study, some new distributed routing algorithms are developed for multimedia data transfer in an asynchronous computer network. For all pairs of nodes in a network, an O(mn) messages and O(m) time distributed algorithm is first presented to find constrained quickest paths, and then an O(mn) messages and O(m) time distributed algorithm is present to enumerate the first k quickest paths. (C) 1998 Elsevier Science B.V. All rights reserved.

关键词： computer networks routing algorithms distributed algorithms quickest path problem

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distributed algorithms for Network Lifetime Maximization in Wireless Visual Sensor Networks

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2009年第5期19卷 704-718页

作者： He, Yifeng Lee, Ivan Guan, Ling Ryerson Univ Dept Elect & Comp Engn Toronto ON M5B 2K3 Canada Univ S Australia Sch Comp & Informat Sci Adelaide SA 5001 Australia

Network lifetime maximization is a critical issue in wireless sensor networks since each sensor has a limited energy supply. In contrast with conventional sensor networks, video sensor nodes compress the video before transmission. The encoding process demands a high power consumption, and thus raises a great challenge to the maintenance of a long network lifetime. In this paper, we examine a strategy for maximizing the network lifetime in wireless visual sensor networks by jointly optimizing the source rates, the encoding powers, and the routing scheme. Fully distributed algorithms are developed using the Lagrangian duality to solve the lifetime maximization problem. We also examine the relationship between the collected video quality and the maximal network lifetime. Through extensive numerical simulations, we demonstrate that the proposed algorithm can achieve a much longer network lifetime compared to the scheme optimized for the conventional wireless sensor networks.

关键词： Convex optimization distributed algorithms network lifetime maximization power consumption wireless visual sensor network

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distributed algorithms for Computing a Common Fixed Point of a Group of Nonexpansive Operators

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2021年第5期66卷 2130-2145页

作者： Li, Xiuxian Feng, Gang City Univ Hong Kong Dept Biomed Engn Kowloon Hong Kong Peoples R China

This article addresses the problem of seeking a common fixed point for a finite collection of nonexpansive operators over time-varying multi-agent networks in real Hilbert spaces. Each operator is assumed to be only privately and approximately known to each individual agent, and all agents need to cooperate to solve this problem by local communications over time-varying networks. To handle this problem, inspired by the centralized inexact Krasnoselski.i-Mann iteration, we propose a distributed algorithm, called distributed inexact averaged operator algorithm (DIO). It is shown that the DIO can converge weakly to a common fixed point of the family of nonexpansive operators. Moreover, under the assumption that all operators and their own fixed point sets are (boundedly) linearly regular, it is proved that the distributed averaged operator algorithm converges with a rate O(gamma l(og16(4k))) for some constant gamma is an element of (0, 1), where k is the iteration number. To reduce computational complexity, a scenario, where only a random part of coordinates of each operator is computed at each iteration, is further considered. In this case, a corresponding algorithm, named distributed block-coordinate inexact averaged operator algorithm, is developed. The algorithm is proved to be weakly convergent to a common fixed point of the group of considered operators almost surely, and, with the extra assumption of (bounded) linear regularity, the distributed block-coordinate averaged operator algorithm is convergent in the mean square sense with a rate O(gamma(log4(4k))) for some constant eta is an element of (0, 1). Furthermore, it is shown that the same convergence rates can still be guaranteed under a more relaxed (bounded) power regularity condition. A couple of examples are finally presented to illustrate the effectiveness of the proposed algorithms.

关键词： distributed algorithms fixed point Krasnoselski.i-Mann iteration multi-agent networks nonexpansive operators optimization

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distributed algorithms FOR THE QUICKEST PATH PROBLEM

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PARALLEL COMPUTING 1992年第7期18卷 823-834页

作者： HUNG, YC CHEN, GH Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan ROC

Let N = (V, A, C, L) be a network with node set V, arc set A, positive arc capacity function C, and nonnegative arc lead time function L. The quickest path problem is to find paths in N to transmit a given amount of data such that the transmission time is minimized. In this paper, distributed algorithms are developed for the quickest path problem in an asynchronous communication network. For the one-source quickest path problem, we present three algorithms that require O(rn2) messages and O(rn2) time, O(rmn) messages and O(rn) time, and O(rm(1+epsilon)log w) messages and O(rn(1+epsilon)log w) time for any epsilon, 0 < epsilon < 1, respectively, where m = \A\, n = \V\, r is the number of distinct capacity values of N, and w is the maximal arc weight of N. For the all-pairs quickest path problem, we present an algorithm that requires O(mn) messages and O(m) time.

关键词： ASYNCHRONOUS NETWORKS distributed algorithms QUICKEST PATH PROBLEM

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distributed algorithms Involving Fixed Step Size for Mixed Equilibrium Problems With Multiple Set Constraints

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2021年第11期32卷 5254-5260页

作者： Lu, Kaihong Zhu, Qixin Jiangsu Univ Sch Elect & Informat Engn Zhenjiang 212013 Jiangsu Peoples R China Suzhou Univ Sci & Technol Sch Mech Engn Suzhou 215009 Peoples R China

In this brief, the problem of distributively solving a mixed equilibrium problem (EP) with multiple sets is investigated. A network of agents is employed to cooperatively find a point in the intersection of multiple convex sets ensuring that the sum of multiple bifunctions with a free variable is nonnegative. Each agent can only access information associated with its own bifunction and a local convex set. To solve this problem, a distributed algorithm involving a fixed step size is proposed by combining the mirror descent algorithm, the primal-dual algorithm, and the consensus algorithm. Under mild conditions on bifunctions and the graph, we prove that all agents' states asymptotically converge to a solution of the mixed EP. A numerical simulation example is provided for demonstrating the effectiveness of theoretical results.

关键词： Optimization distributed algorithms Convergence Learning systems Resistance Electric potential Mirrors distributed algorithm mixed equilibrium problem (MEP) multiagent networks

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distributed algorithms for Minimum Cost Multicast With Network Coding

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IEEE-ACM TRANSACTIONS ON NETWORKING 2010年第2期18卷 379-392页

作者： Xi, Yufang Yeh, Edmund M. Yale Univ Dept Elect Engn New Haven CT 06520 USA

Network coding techniques are used to find the minimum-cost transmission scheme for multicast sessions with or without elastic rate demand. It is shown that in wireline networks, solving for the optimal coding subgraphs in network coding is equivalent to finding the optimal routing scheme in a multicommodity flow problem. A set of node-based distributed gradient projection algorithms are designed to jointly implement congestion control/routing at the source node and "virtual" routing at intermediate nodes. The analytical framework and distributed algorithms are further extended to interference-limited wireless networks where link capacities are functions of the signal-to-interference-plus-noise ratio (SINR). To achieve minimum-cost multicast in this setting, the transmission powers of links must be jointly optimized with coding subgraphs and multicast input rates. Node-based power allocation and power control algorithms are developed for the power optimization. The power algorithms, when iterated in conjunction with the congestion control and routing algorithms, converge to the jointly optimal multicast configuration. The scaling matrices required in the gradient projection algorithms are explicitly derived and are shown to guarantee fast convergence to the optimum from any initial condition.

关键词： Cross-layer optimization distributed algorithms network coding wireless networks

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distributed algorithms via Saddle-Point Dynamics for Multi-Robot Task Assignment

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IEEE ROBOTICS AND AUTOMATION LETTERS 2024年第12期9卷 11178-11185页

作者： Huang, Yi Kuai, Jiacheng Cui, Shisheng Meng, Ziyang Sun, Jian Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China Tsinghua Univ Dept Precis Instrument Beijing 100084 Peoples R China

This letter develops two distributed algorithms to solve multi-robot task assignment problems (MTAP). We first describe MTAP as an integer linear programming (ILP) problem and then reformulate it as a relaxed convex optimization problem. Based on the saddle-point dynamics, we propose two distributed optimization algorithms using optimistic gradient decent ascent (OGDA) and extra-gradient (EG) methods, which achieve exact convergence to an optimal solution of the relaxed problem. In most cases, such an solution reflects the optimality of the original ILP problems. For some special ILP problems, we provide a perturbation-based distributed method to avoid the inconsistency phenomenon, such that an optimal solution to any ILP problem is obtained. Compared with some decentralized algorithms requiring a central robot that communicates with the other robots, our developed algorithms are fully distributed, in which each robot only communicates with the nearest neighbors for an arbitrary connected graph. We evaluate the developed algorithms in terms of computation, communication, and data storage complexities, and compare them with some typical algorithms. It is shown that the developed algorithms have low computational and communication complexities. We also verify the effectiveness of our algorithms via numerical examples.

关键词： Robots Heuristic algorithms Cost function distributed algorithms Convex functions Sun Resource management Multi-robot systems NP-hard problem Linear programming multi-robot task assignment integer linear programming (ILP) problem saddle-point dynamics inconsistency phenomenon

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