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

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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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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decentralized mining social network communities with agents

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MATHEMATICAL AND COMPUTER MODELLING 2013年第11-12期57卷 2998-3008页

作者： Huang, Jing Yang, Bo Jin, Di Yang, Yi Jilin Univ Coll Comp Sci & Technol Changchun 130012 Peoples R China Jilin Univ Minist Educ Key Lab Symbol Computat & Knowledge Engn Changchun 130012 Peoples R China Tianjin Univ Coll Comp Sci & Technol Tianjin Peoples R China

Network community mining algorithms aim at efficiently and effectively discovering all such communities from a given network. Many related methods have been proposed and applied to different areas including social network analysis, gene network analysis and web clustering engines. Most of the existing methods for mining communities are centralized. In this paper, we present a multi-agent based decentralized algorithm, in which a group of autonomous agents work together to mine a network through a proposed self-aggregation and self-organization mechanism. Thanks to its decentralized feature, our method is potentially suitable for dealing with distributed networks, whose global structures are hard to obtain due to their geographical distributions, decentralized controls or huge sizes. The effectiveness of our method has been tested against different benchmark networks. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Social network Community mining Multi-agent system decentralized algorithm

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Auction-Based Mechanism for Dynamic and Efficient Resource Allocation

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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2018年第1期48卷 34-49页

作者： Zou, Suli Ma, Zhongjing Liu, Xiangdong Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China

We study how to efficiently allocate the infinitesimal divisible resource under auction mechanism in a dynamic way. We propose a Vickrey-Clarke-Groves-type auction mechanism with a 2-D bid which specifies a per unit price and a maximum of the demand. Due to the absence of enough information related to the infinite dimensional valuations of individual players in a single-bid strategy, it is challenging to implement the efficient Nash equilibrium (NE) in a dynamic way. In this paper, we introduce a pair of parameters related to players' valuations, and design a decentralized dynamic process assisted with this pair of values, such that at each iteration, a single player updates its best bid under a constrained set of demand. Under the proposed auction mechanism, we show the incentive compatibility, efficiency, and uniqueness of the NE. Furthermore, our method is guaranteed to converge to the efficient NE, and it presents the enhanced convergence performance compared with those methods proposed in the literature. Case studies are given to demonstrate the results developed in this paper.

关键词： Auction convergence decentralized algorithm efficiency Nash equilibrium (NE) resource allocation

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A decentralized method for initial populations of genetic algorithms

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JOURNAL OF SUPERCOMPUTING 2023年第9期79卷 10232-10251页

作者： Roshani, Reza Motameni, Homayon Mohamadi, Hosein Islamic Azad Univ Dept Comp Engn Sari Branch Sari Iran Islamic Azad Univ Dept Comp Engn Azadshar Branch Azadshar Iran

Today, evolutionary algorithms are widely used in a variety of fields for problem solving and optimization purposes. The genetic algorithms (GA) entail a number of primary stages which have been optimized many times to date;one of these stages involves the generation of the initial population. Generating a suitable and diverse initial population can prevent the early convergence of the problem and greatly contributes to problem-solving abilities and speed. The proposed method in this study involves generating an initial population in a decentralized manner between a number of processing nods which are generated as subpopulations before being integrated. Carrying out this procedure using the conditions present in any processors increases diversity in the population. The presented method is used based on estimating the parameters of software reliability growth model (SRGMs). Finally, it is shown that the proposed model managed to achieve population diversity, enhanced accuracy, and increased performance.

关键词： Genetic algorithms Initial population Population diversity decentralized algorithm Random generation SRGM

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A decentralized Electricity Market Scheme Enabling Demand Response Deployment

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IEEE TRANSACTIONS ON POWER SYSTEMS 2018年第4期33卷 4218-4227页

作者： Bahrami, Shahab Amini, M. Hadi Shafie-khah, Miadreza Catalao, Joao P. S. Univ British Columbia Dept Elect & Comp Engn Vancouver BC V6T 1Z4 Canada Carnegie Mellon Univ Dept Elect & Comp Engn Pittsburgh PA 15213 USA Sun Yat Sen Univ Sch Elect & Informat Technol Guangzhou 510275 Guangdong Peoples R China Univ Beira Interior C MAST P-6201001 Covilha Portugal Univ Porto INESC TEC P-4200465 Porto Portugal Univ Porto Fac Engn P-4200465 Porto Portugal Univ Lisbon Inst Super Tecn INESC ID P-1049001 Lisbon Portugal

In smart grid, demand response (DR) programs can be deployed to encourage electricity consumers towards scheduling their controllable demands to off-peak periods. Motivating the consumers to participate in a DR program is a challenging task, as they experience a confidential discomfort cost by modifying their load demand from the desirable pattern to the scheduled pattern. Meanwhile, to balance the load and generation, the independent system operator (ISO) requires to motivate the suppliers towards modifying their generation profiles to follow the changes in the load demands. Additionally, to protect the entities' privacy, the ISO needs to apply an effective well-designed pricing scheme. In this paper, we focus on proposing a decentralized DR framework considering the operating constraints of the grid. In our proposed framework, each individual entity responds to the control signals called conjectured prices from the ISO to modify its demand or generation profile with the locally-available information. We formulate the centralized problem of the ISO that jointly minimizes the suppliers' generation cost and the consumers' discomfort cost. We also discuss how the ISO determines the conjectured prices to motivate the entities toward an operating point that coincides with the solution to the centralized problem. The performance of the proposed algorithm is evaluated on a modified IEEE 14-bus in reducing the suppliers' and consumers' cost, as well as the transmission lines congestion.

关键词： Demand response discomfort cost power flow problem decentralized algorithm

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Cooperative energy management of a community of smart-buildings: A Blockchain approach

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2020年第0期117卷 105643-000页

作者： Van Cutsem, Olivier Dac, David Ho Boudou, Pol Kayal, Maher Ecole Polytech Fed Lausanne Dept Elect Engn STI CH-1005 Lausanne Switzerland

Demand Response (DR) is progressively moving from a centralized, unidirectional structure to a set of advanced decentralized mechanisms that better balance distributed supply and demand. This paper presents a decentralized cooperative DR framework to manage the daily energy exchanges within a community of Smart-Buildings, in the presence of local Renewable Energy Sources (RES). The proposed algorithm taps into the flexibility of the participants to let them decide of a day-ahead community power profile, and subsequently ensures the forecast tracking during the next day. In practice, the algorithm is fully decentralized by the Blockchain technology, that enables a trusted communication medium among the participants and enforces autonomous monitoring and billing via Smart-Contracts. With such an energy management framework, participating Smart-Buildings can together aim at a common objective, such as carbon-free resources usage or aggregated grid services, without depending on a centralized aggregator/utility. Simulations on realistic Swiss building models demonstrate that nearly all the renewable production resources could be harnessed locally through the presented framework, compared to selfish individual optimization. Under a quadratic cost of grid electricity, the considered community profile could dramatically be flattened, hence avoiding costly peaks at the grid interface. A scalability analysis shows that, considering the current public Ethereum Blockchain, the framework could handle a community size of up to 100 Smart-Buildings.

关键词： Cooperative energy management Smart-buildings Smart-community Blockchain Demand response Smart-contract Linear optimization decentralized algorithm

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Minimal-time complex consensus for multi-agent systems with time delay

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IET CONTROL THEORY AND APPLICATIONS 2022年第12期16卷 1182-1193页

作者： Zou, Chao Yu, Li Yang, Simon Ou, Linlin Zhejiang Univ Technol Coll Informat & Engn Hangzhou 310023 Peoples R China Univ Guelph Sch Engn Guelph ON Canada

This paper studies the minimum time consensus problem for discrete-time multi-agent systems with complex Laplacian delay networks such that each agent can find its complex consensus value in a minimum number of steps using its local observations. The stability analysis is first provided and the convergence condition is derived for complex weighted networks with time delays. Specifically, the delayed multi-agent system is modeled by employing the augmented graph representation. Via adding virtual agents in the augmented systems, the complex consensus is obtained in the networks with bounded time delay if the communication topology digraph of the system has a spanning tree. A decentralized algorithm is proposed for the minimal-time computation of complex consensus based on the information from the robot itself without relying on the external environment. The algorithm hinges on the minimal polynomial of the matrix concerning the augmented graph. Furthermore, the rearrangement of the virtual agents in the augmented system provides an upper bound for the number of agents required to compute the consensus value. Simulation examples demonstrate the effectiveness of our results. The advantage of this approach is that it can be easily deployed on a group of agents to rapidly achieve a complex consensus setting within any delayed networks.

关键词： minimal polynomial distributed algorithms augmented system mobile robots bounded time delay minimum time consensus problem delayed multiagent system augmented graph representation multi-robot systems computational complexity communication topology digraph minimal-time computation decentralized algorithm convergence minimal-time complex consensus stability analysis time delays complex weighted networks discrete time systems convergence condition polynomials complex consensus setting discrete-time multiagent systems virtual agents directed graphs multi-agent systems trees (mathematics) delays complex Laplacian delay networks complex consensus value spanning tree

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Secure localization with phantom node detection

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AD HOC NETWORKS 2008年第7期6卷 1031-1050页

作者： Hwang, Joengmin He, Tian Kim, Yongdae Univ Minnesota Dept Comp Sci & Engn Minneapolis MN 55455 USA

In an adversarial environment, various kinds of attacks become possible if malicious nodes could claim fake locations that are different from their physical locations. In this paper, we propose a secure localization mechanism that detects existence of these nodes, termed as phantom nodes, without relying on any trusted entities, ail approach significantly different from the existing ones. The proposed mechanism enjoys a set of nice features. First, it does not have my central point of attack. All nodes play the role of verifier, by generating local map, i.e. a view constructed based on ranging information from its neighbors. Second, this distributed and localized construction results in strong robustness against adversaries: even when the number of phantom nodes is greater than that of honest nodes, we can filter out most of the phantom nodes. Our analytical results as well as simulations under realistic noisy settings demonstrate that the proposed mechanism is effective in the presence of a large number of phantom nodes. (C) 2007 Elsevier B.V. All rights reserved.

关键词： Sensor networks Localization Secure localization Location verification Speculative algorithm decentralized algorithm

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Privacy Protection decentralized Economic Dispatch Over Directed Networks With Accurate Convergence

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IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE 2023年第6期7卷 1702-1716页

作者： Lu, Qingguo Deng, Shaojiang Li, Huaqing Huang, Tingwen Chongqing Univ Coll Comp Sci Chongqing 400044 Peoples R China Southwest Univ Coll Elect & Informat Engn Chongqing 400715 Peoples R China Texas A&M Univ Qatar Sci Program Doha 23874 Qatar

decentralized algorithms to solve the economic dispatch problem (EDP) in smart grids have been a significant focus within engineering research due to their advantages in scalability, robustness, and flexibility. Its purpose is to optimize the generation power of each generator to jointly achieve the minimal total generation cost on the premise of satisfying the total demand and generation capacity. Recently, the emergence of data security and the requirement for complex computing have led to a resurgence of activity in this area. To address EDP while considering the issues of private security and computation efficiency, we propose a novel privacy-protected decentralized random sleep algorithm over an unbalanced directed network. On the one hand, the proposed algorithm can effectively protect sensitive information by adding conditional noises in the state exchange. On the other hand, it can also promote computation efficiency over an unbalanced directed network by incorporating the random sleep strategy into the decentralized inexact gradient method with the gradient rescaling technique. It is proved that the proposed algorithm is able to achieve the optimal solution of the EDP. Furthermore, we also provide theoretical proof to guarantee the convergence and privacy properties of the proposed algorithm. Finally, two simulation examples of EDP in smart grids are provided to demonstrate the effectiveness of the proposed algorithm.

关键词： Economic dispatch decentralized algorithm privacy protection directed network random sleep strategy

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