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An Externalities-Based decentralized Optimal Power Allocation algorithm for Wireless Networks

IEEE-ACM TRANSACTIONS ON NETWORKING 2009年第6期17卷 1819-1831页

作者： Sharma, Shrutivandana Teneketzis, Demosthenis Univ Michigan Dept Elect Engn & Comp Sci Ann Arbor MI 48109 USA

The rapidly growing demand for wireless communication makes efficient power allocation a critical factor in the network's efficient operation. Power allocation in decentralized wireless systems, where the transmission of a user creates interference to other users and directly affects their utilities, has been recently studied by pricing methods. However, pricing methods do not result in efficient/optimal power allocations for such systems for the following reason. Systems where a user's actions directly affect the utilities of other users are known to have externalities. It is well known from Mas-Colell et al. that in systems with externalities, standard efficiency theorems on market equilibrium do not apply and pricing methods do not result in Pareto optimal outcomes. In this paper, we formulate the power allocation problem for a wireless network as an allocation problem with "externalities." We consider a system where each user knows only its own utility and the channel gains from the transmitters of other users to its own receiver. The system has multiple interference temperature constraints to control interference. We present a decentralized algorithm to allocate transmission powers to the users. The algorithm takes into account the externality generated to the other users by the transmission of each user, satisfies the informational constraints of the system, overcomes the inefficiency of pricing mechanisms and guarantees convergence to globally optimal power allocations.

关键词： decentralized algorithm externalities interference interference temperature constraint mechanism design microeconomics power allocation wireless network

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A decentralized energy-based diffusion algorithm to increase the lifetime of MANETs

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COMPUTER NETWORKS 2010年第16期54卷 2887-2898页

作者： Bahi, Jacques M. Salomon, Michel Univ Franche Comte Comp Sci Lab LIFC IUT Belfort Montbeliard F-90016 Belfort France

In this paper, we introduce a novel approach to improve overall lifetime in mobile ad hoc networks. Given the energy constraint on each node, this problem is formulated as an energy-controlled load balancing problem. Thus, our approach is quite different from usual energy-efficient routing or topology control methods. The proposed algorithm is fully distributed and ensures that each node will cooperate in proportion to its remaining energy, increasing the network lifetime. The relevance of the algorithm is evaluated through both theoretical analysis and simulations. (C) 2010 Elsevier B.V. All rights reserved.

关键词： Mobile ad hoc networks Lifetime decentralized algorithm Diffusion

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A decentralized smoothing quadratic regularization algorithm for composite consensus optimization with non-Lipschitz singularities

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NUMERICAL algorithmS 2024年第1期96卷 369-396页

作者： Wang, Hong Shenzhen Technol Univ Coll Big Data & Internet Dept Math 3002 Lantian Rd Shenzhen 518118 Guangdong Peoples R China

Distributed algorithms are receiving renewed attention across multiple disciplines due to the dramatically increasing demand of big data processing. We consider a class of consensus optimization problems over a static network system of multiple agents, where each of local cost functions is a sum of a smooth function and a non-Lipschitz regularization term. This kind of problems is widely found in scientific and engineering areas such as machine learning and data analysis. Inspired by Bian and Chen (SIAM J. Opt. 23(3), 1718-1741 2017), we propose a decentralized smoothing quadratic regularization algorithm (abbreviated as D-SQRA) for solving the composite consensus problem with non-Lipschitz singularities. To some extent, D-SQRA can be seen as an extension in the decentralized setup of the smoothing quadratic regularization algorithm (SQRA) proposed in (SIAM J. Opt. 23(3), 1718-1741 2017). Our main contribution is to show that D-SQRA can inherit the theoretical properties of its centralized counterpart, i.e., SQRA, in both sides of convergence and worst-case iteration complexity to achieve an & epsilon;\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$\epsilon $$\end{document} scaled stationary point. We also present some numerical examples on sparse sensing problems based on synthetic and real datasets to corroborate the effectiveness of the proposed decentralized algorithm.

关键词： Distributed optimization decentralized algorithm Non-Lipschitz singularities Nonsmooth nonconvex optimization

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A Simple decentralized Timeslot Synchronization algorithm for Large-Scale Wireless IoT Networks 16

A Simple Decentralized Timeslot Synchronization Algorithm fo...

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16th Annual Conference on Wireless On-demand Network Systems and Services (WONS)

作者： Pabbisetty, Gurusanthosh Mori, Hiroki Toshiba Co Ltd Wireless Syst Lab Corp Res & Dev Ctr Informat & Commun Platform Labs Tokyo Japan

ISBN: (纸本)9783903176355

Rapid growth in use of wireless IoT sensors to realize smart lighting / homes / factories would add a precious asset to the existing infrastructure i.e. numerous wireless devices, which are used to transfer sensed parameters. Various applications (such as indoor localization) could be realized with this asset if it is possible to collect wireless parameters such as RSSI among all IoT sensors. An efficient way is to use token-based TDMA mechanisms where every sensor gets a transmission opportunity in the assigned timeslot. But, synchronizing timeslots to identify transmission instant in a large-scale sensor network is a challenging task. In this paper, we propose a simple decentralized timeslot synchronization algorithm that could realize any TDMA based RSSI accumulation protocol in an ultra-efficient way compared to conventional schemes and evaluated using an event based simulator developed in Matlab.

关键词： decentralized algorithm Large-scale IoT RSSI data accumulation Token-based TDMA

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decentralized Diffusion-Controlled algorithm for Community Detection: Initialization and Resolution Study

Decentralized Diffusion-Controlled Algorithm for Community D...

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作者： ADRIAN RAMIREZ DEL RIO KTH ROYAL INSTITUTE OF TECHNOLOGY

学位级别：硕士

Community detection in graphs has been an important research topic for many fields. The aim of community detection is to extract from graphs those groups of nodes that present more connections between them than with the rest of the network. Detecting such groups at different scales can help understanding the global behaviour of the system. However, recent studies have shown that real- world graphs follow power-law distributions for degree and community sizes. Specifically, these graphs present many small communities but just a few large ones. This unbalanced community size distribution poses a great challenge for community detection algorithms. Most of the existing methods are based on global approaches that require information about the network to be processed as a whole. Thus, those techniques can not be applied when the graph is too big to fit into one single machine, or in distributed setting when the graph is partitioned among multiple machines. To solve this limitations, a completely decentralized community detection algorithm is presented. It is based on diffusion, following a vertex-centric approach that allows each node to decide the diffusion rates based on local information. It adds as well a mechanism for controlling the diffusion speed through a customizable function. We evaluate the algorithm with a variety of graphs with different levels of imbalance and community structures. Our algorithm is able to detect (almost) perfectly the communities when the imbalance between community sizes is not extreme. We show as well how the sizes of the detected communities can be controlled by the diffusion strategy, allowing for better detection of finer or coarser resolutions in hierarchical graphs. The algorithm is also compared to other two well-known existing methods, achieving similar results in most of the cases though with a higher computation time.

关键词： community detection unbalanced communities adaptive diffusion decentralized algorithm

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decentralized detection for B5G massive MIMO: When local computation meets iterative algorithm

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PHYSICAL COMMUNICATION 2022年 51卷

作者： Yang, Qiyu Yan, Jiayi Zhang, Xia Zhang, Hekun Guangdong Univ Technol Sch Automat Guangzhou 510006 Peoples R China South China Agr Univ Coll Elect Engn Coll Artificial Intelligence Guangzhou 510642 Peoples R China China Mobile Grp Guangdong Co Ltd Guangzhou Branch Guangzhou Guangdong Peoples R China

Massive multiple-input multiple-output (MIMO) is a key enabler for 5G and beyond. For signal detection of massive MIMO, computing resources available at the network edge were underexplored in most existing algorithms. For this reason, the paper proposes a new detection algorithm, termed inner-looping decentralized generalized expectation consistent for signal recovery (iDeGEC-SR), which leverages an extra (inner) loop of message passing added to the DeGEC-SR and makes better exploration of the local computing resources. As demonstrated by theoretical analysis and Monte Carlo simulations, the algorithm outperforms state-of-the-art techniques like GEC-SR (in terms of computational complexity), GAMP and DeGEC-SR (in terms of estimation accuracy), considerably. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Massive MIMO decentralized algorithm Message passing Mean square error

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Request-Response and Censoring-Based Energy-Efficient decentralized Change-Point Detection With IoT Applications

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IEEE INTERNET OF THINGS JOURNAL 2021年第8期8卷 6771-6788页

作者： Gu, Yuantao Jiao, Yuchen Xu, Xingyu Yu, Quan Tsinghua Univ Beijing Natl Res Ctr Informat Sci & Technol Beijing 100084 Peoples R China Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China Peng Cheng Lab Shenzhen 518066 Peoples R China

Change-point detection (CPD) from streaming data is a fundamental problem in statistical signal processing and has wide applications in wireless sensor networks and the Internet of Things (IoT), such as environmental monitoring and physical activity detection. In various detection schemes, decentralized detection without fusion center is becoming increasingly popular for IoT applications since it enjoys the benefit of strong robustness and security. However, it faces the big challenge of high energy consumption. In this work, we propose an energy-efficient decentralized CPD algorithm called request-response and censoring-based cumulative sum. Specifically, we design a novel communication strategy based on request-response and censoring scheme, which could help the sensors extract useful information from the neighbor sets with a low amount of communication. Furthermore, to provide a guideline on selecting the parameters involved in our algorithm, we theoretically analyze the performance of the proposed algorithm under a simplification for the most interesting cases, in terms of two standard criteria average running length (ARL) and expected detection delay (EDD). Numerical simulations are conducted to verify the effectiveness of the proposed algorithm. Moreover, we test the feasibility of the proposed algorithm in the physical activity CPD task. The experimental results on the real-world data set demonstrate its high energy efficiency and small detection delay.

关键词： Sensors Wireless sensor networks Task analysis Hidden Markov models Internet of Things Data models Delays Censoring change-point detection (CPD) cumulative sum (CUSUM) decentralized algorithm request– response

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DPoS: decentralized, Privacy-Preserving, and Low-Complexity Online Slicing for Multi-Tenant Networks

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2022年第12期21卷 4296-4309页

作者： Zhao, Hailiang Deng, Shuiguang Liu, Zijie Xiang, Zhengzhe Yin, Jianwei Dustdar, Schahram Zomaya, Albert Y. Zhejiang Univ Coll Comp Sci & Technol Hangzhou 310058 Zhejiang Peoples R China Zhejiang Univ City Coll Hangzhou 310015 Zhejiang Peoples R China TU Wien Distributed Syst Grp A-1040 Vienna Austria Univ Sydney Sch Comp Sci Sydney NSW 2006 Australia

Network slicing is the key to enable virtualized resource sharing among vertical industries in the era of 5G communication. Efficient resource allocation is of vital importance to realize network slicing in real-world business scenarios. To deal with the high algorithm complexity, privacy leakage, and unrealistic offline setting of current network slicing algorithms, in this paper we propose a fully decentralized and low-complexity online algorithm, DPoS, for multi-resource slicing. We first formulate the problem as a global social welfare maximization problem. Next, we design the online algorithm DPoS based on the primal-dual approach and posted price mechanism. In DPoS, each tenant is incentivized to make its own decision based on its true preferences without disclosing any private information to the mobile virtual network operator and other tenants. We provide a rigorous theoretical analysis to show that DPoS has the optimal competitive ratio when the cost function of each resource is linear. Extensive simulation experiments are conducted to evaluate the performance of DPoS. The results show that DPoS can not only achieve close-to-offline-optimal performance, but also have low algorithmic overheads.

关键词： Network slicing Business Indium phosphide III-V semiconductor materials Computer architecture Quality of service Privacy Network slicing decentralized algorithm posted price mechanism privacy preserving multi-tenant networks

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Location-based spectrum allocation and partitioning scheme for cross-tier interference mitigation in macro-femtocell networks

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COMPUTER NETWORKS 2013年第15期57卷 2869-2879页

作者： Ryoo, Sunheui Joo, Changhee Bahk, Saewoong Seoul Natl Univ INMC Sch Elect Engn & Comp Sci Seoul South Korea UNIST Sch Elect & Comp Engn Ulsan South Korea

In this paper, we address the cross-tier interference problem in a two-tier network which consists of overlaid femtocells within a macrocell range. In the considered network, macro and femto base stations are assumed with the capabilities of power control and beamforming, differently from user terminals. Under such environments, we devise a decentralized solution where each femtocell determines whether to use shared spectrum or partitioned spectrum, considering users' location information. Introducing two simple distance thresholds, we can optimally partition the spectrum and allocate them without detailed channel information. Simulation results demonstrate that our decentralized scheme achieves comparable performance to the centralized one with low overhead and feedback delay. (c) 2012 Elsevier B.V. All rights reserved.

关键词： Femtocell Cross-tier interference mitigation Beamforming Spectrum allocation Location-based decentralized algorithm

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Centralized and decentralized Active User Detection and Channel Estimation in mMTC

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IEEE TRANSACTIONS ON COMMUNICATIONS 2022年第3期70卷 1759-1776页

作者： Rajoriya, Anupama Rukhsana, Syed Budhiraja, Rohit IIT Kanpur Dept Elect Engn Kanpur 208016 Uttar Pradesh India

We consider the problem of estimating channel and detecting active users in the uplink of a massive machine type communication (mMTC) network. We propose a centralized coupled prior based sparse Bayesian learning (cCP-SBL) algorithm that exploits the sporadic user activity and variable-sized block mMTC channel sparsity in the virtual angular domain. To achieve this objective, we first design a generalized coupled hierarchical Gaussian prior which captures this variable-sized block sparsity. We then derive its sub-optimal precision hyperparameter updates using majorization minimization framework. We next design a decentralized CP-SBL (dCP-SBL) algorithm for the emerging base station architectures with multiple processing units. The dCP-SBL algorithm converts the centralized hyperparameter cCP-SBL updates to an equivalent optimization problem, and solves it decentrally using asynchronous alternating direction method of multipliers. We also theoretically analyze the convergence of the dCP-SBL algorithm. We show using extensive numerical investigations that the i) proposed cCP- and dCP-SBL algorithms outperform several existing state-of-the-art designs;and ii) dCP-SBL algorithm is robust to processing unit failures and has a lower time complexity than the cCP-SBL algorithm.

关键词： Signal processing algorithms Channel estimation Bayes methods Sparse matrices Heuristic algorithms Convergence Optimization decentralized algorithm majorization minimization sparse Bayesian learning (SBL)

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