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检索条件"主题词=Consensus Algorithms"

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Enhancing Networks via Virtualized Network Functions

Enhancing Networks via Virtualized Network Functions

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作者： Zhang, Yang University of Minnesota

学位级别：Ph.D.

In an era of ubiquitous connectivity, various new applications, network protocols, and online services (e.g., cloud services, distributed machine learning, cryptocurrency) have been constantly creating, underpinning many of our daily activities. Emerging demands for networks have led to growing traffic volume and complexity of modern networks, which heavily rely on a wide spectrum of specialized network functions (e.g., Firewall, Load Balancer) for performance, security, etc. Although (virtual) network functions (VNFs) are widely deployed in networks, they are instantiated in an uncoordinated manner failing to meet growing demands of evolving networks. In this dissertation, we argue that networks equipped with VNFs can be designed in a fashion similar to how computer software is today programmed. By following the blueprint of joint design over VNFs, networks can be made more effective and efficient. We begin by presenting Durga, a system fusing wide area network (WAN) virtualization on gateway with local area network (LAN) virtualization technology. It seamlessly aggregates multiple WAN links into a (virtual) big pipe for better utilizing WAN links and also provides fast fail-over thus minimizing application performance degradation under WAN link failures. Without the support from LAN virtualization technology, existing solutions fail to provide high reliability and performance required by today’s enterprise applications. We then study a newly standardized protocol, Multipath TCP (MPTCP), adopted in Durga, showing the challenge of associating MPTCP subflows in network for the purpose of boosting throughput and enhancing security. Instead of designing a customized solution in every VNF to conquer this common challenge (making VNFs aware of MPTCP), we implement an online service named SAMPO to be readily integrated into VNFs. Following the same principle, we make an attempt to take consensus as a service in software-defined networks. We illustrate new network failure

关键词： Computer Networks consensus algorithms Network Function Virtualization Network Management Network Performance

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Autonomous 5G Smallcell Network Deployment and Optimization in Unlicensed Spectrum 2

Autonomous 5G Smallcell Network Deployment and Optimization ...

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IEEE 2nd 5G World Forum (5GWF)

作者： Sevindik, Volkan Smallcellcoin Inc Fairfax VA 22031 USA

ISBN: (纸本)9781728136271

This paper presents novel blockchain based autonomous 5G smallcell network deployment, and spectrum management technique. New consensus algorithms which are proof of signaling (PoSI), proof of load (PoLO), proof of user authentication (PoUA), proof of link (PoLI) are introduced. These novel algorithms are used to verify transactions in smallcell blockchain network. A new technique is proposed to manage spectrum grants in an unlicensed spectrum environment. All proposed techniques are used to automate network deployment, unlicensed spectrum management in order to decrease capital and operational expenditures (CapEx and OpEx) during and after 5G network deployment.

关键词： distributed ledger consensus algorithms blockchain smart contract 5G smallcell deployment optimization spectrum management unlicensed spectrum

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Appendable-block Blockchain Evaluation over Geographically-Distributed IoT Networks

Appendable-block Blockchain Evaluation over Geographically-D...

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IEEE International Black Sea Conference on Communications and Networking (IEEE BlackSeaCom)

作者： de Arruda, Eduardo H. P. Lunardi, Roben C. Nunes, Henry C. Zorzo, Avelino E. Michelin, Regio A. Pontifical Catholic Univ Rio Grande do Sul PUCRS Porto Alegre RS Brazil Fed Inst Rio Grande do Sul IFRS Porto Alegre RS Brazil Cyber Secur CRC CSCRC Sydney NSW Australia

ISBN: (纸本)9781728171272

In the last few years, different researchers presented proposals for using blockchain in the Internet of Things (IoT) environments. These proposals consider that IoT environments can be benefited from different blockchain characteristics, such as: resilience, distributed processing, integrity and non-repudiation of produced information. However, researchers faced some challenges to use blockchain in IoT, e.g., latency, hardware and energy constraints, and performance requirements. One of the prominent solutions is the appendable-block blockchain, which uses a hierarchical peer-to-peer (p2p) gateway-based architecture. Additionally, current proposals present simplified evaluation scenarios, usually performed in controlled environments, which do not include important network features, for example, latency. Consequently, a model to evaluate a geographically distributed environment, for example, in a situation in which health data have to be collected from different countries in a pandemic situation, can help to understand the behavior and possible flaws of blockchains. In order to evaluate appendable-block blockchains in a realistic scenario, this paper presents an analysis of different consensus algorithms in geographically distributed hosts, in which latency can impact the performance of main operations in a blockchain, such as block and transaction insertion.

关键词： Blockchain appendable-block performance evaluation consensus algorithms geo-distributed IoT

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Modular Blockchain Implementation in Intensive Medicine 11

Modular Blockchain Implementation in Intensive Medicine

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11th International Conference on Ambient Systems, Networks and Technologies (ANT) / 3rd International Conference on Emerging Data and Industry 4.0 (EDI)

作者： Guimaraes, Tiago Silva, Hugo Peixoto, Hugo Santos, Manuel Univ Minho Algoritmi Ctr Braga Portugal

Blockchain has its focus around sharing, distribution and encryption. Particularly, the newer blockchain implementations revolve around the implementation of smart-contracts, second-layer systems and permissioned blockchains. This type of potential has generated a lot of attention towards blockchain, thus making it a great candidate technology within healthcare. In this paper, the role of permissioned and permissionless blockchain and its possible implementations will be discussed and compared as well as the process in which a blockchain network agrees whether a transaction is valid or not, maintaining consistency in ledger synchronization, or in other words, consensus algorithms. Several should be considered as viable and many can be used by both permissioned and permissionless blockchain frameworks. As chosen as part of this implementation Practical Byzantine Fault Tolerance (Pbft) is presented and described. This paper presents a solution, as part of the Intelligence Decision Support Systems for Intensive Medicine (ICDS4IM) project, which objective is to increase veracity and value to data from vital sensors and monitors by assuring its immutability and oversee;and also privacy and accountability for inadequate data management. (C) 2020 The Authors. Published by Elsevier B.V.

关键词： Blockchain Healthcare consensus algorithms Pbft permissioned EHR

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Linear Convergence Rate for Distributed Optimization with the Alternating Direction Method of Multipliers 53

Linear Convergence Rate for Distributed Optimization with th...

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53rd IEEE Annual Conference on Decision and Control (CDC)

作者： Iutzeler, F. Bianchi, P. Ciblat, Ph. Hachem, W. Supelec Gif Sur Yvette France Telecom ParisTech CNRS LTCI Paris France

ISBN: (纸本)9781467360906

Consider the problem of distributed optimization where a network of N agents cooperate to solve a minimization problem of the form inf x Sigma(N)(n=1) integral n (x) where function integral(n) is convex and known only by agent n. The Alternating Direction Method of Multipliers (ADMM) has shown to be particularly efficient to solve this kind of problem. In this paper, we assume that there exists a unique minimum x, and that the functions f7,, are twice differentiable at x(star) and verify Sigma(N)(n=1) del(2) f(n) (x(star)) > 0 where the inequality is taken in the positive definite ordering. Under these assumptions, we prove the linear convergence of the distributed ADMM to the consensus over x(star) and derive a tight convergence rate. Finally, we give examples where one can derive the ADMM hype -parameter rho corresponding to the optimal rate.

关键词： Distributed optimization consensus algorithms Alternating Direction Method of Multipliers

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A STOCHASTIC COORDINATE DESCENT PRIMAL-DUAL ALGORITHM AND APPLICATIONS 24

A STOCHASTIC COORDINATE DESCENT PRIMAL-DUAL ALGORITHM AND AP...

引用

IEEE International Workshop on Machine Learning for Signal Processing (MLSP)

作者： Bianchi, Pascal Hachem, Walid Franck, Iutzeler Telecom Paris Tech Paris France CNRS LTCI Paris France Supelec Gif Sur Yvette France

ISBN: (纸本)9781479936946

First, we introduce a splitting algorithm to minimize a sum of three convex functions. The algorithm is of primal dual kind and is inspired by recent results of Vu and Condat. Second, we provide a randomized version of the algorithm based on the idea of coordinate descent. Finally, we address two applications of our method: (i) for stochastic minibatch optimization;and (ii) for distributed optimization.

关键词： Distributed Optimization Large-scale Learning Coordinate Descent consensus algorithms Primal-Dual Algorithm

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SEQUENTIAL ESTIMATION OF LINEAR MODELS IN DISTRIBUTED SETTINGS

SEQUENTIAL ESTIMATION OF LINEAR MODELS IN DISTRIBUTED SETTIN...

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21st European Signal Processing Conference (EUSIPCO)

作者： Wang, Yunlong Djuric, Petar M. SUNY Stony Brook Dept Elect & Comp Engn Stony Brook NY 11794 USA

ISBN: (纸本)9781479936878

In this paper, we consider the problem of distributed sequential estimation of time invariant parameters in a network of cooperative agents. We study a system where the agents quantify their respective beliefs in the unknown parameters by approximations of the posteriors of the parameters with multivariate Gaussians. At every time instant each agent carries out three operations, (a) it receives private measurements distorted by additive noise, (b) it exchanges information about its belief in the estimated parameters with its neighbors, and (c) it updates its belief with the new information. Since we consider distributed processing in the network, it is challenging to provide an optimal strategy where the agents update their believes using the Bayes' rule in every iteration. In this work, instead, we propose a method which does not process the data based on Bayes theory and yet allows the agents to reach asymptotically the optimal Bayesian belief held by a fictitious fusion center. We provide convergence analysis of the method and demonstrate its performance by simulations.

关键词： Distributed estimation Bayesian estimation consensus algorithms cooperative agents

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Network Coordinated Distributed Demand Management for Optimal Large-Scale Charging of PHEVs/PEVs

Network Coordinated Distributed Demand Management for Optima...

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General Meeting of the IEEE-Power-and-Energy-Society (PES)

作者： Asr, Navid Rahbari Chow, Mo-Yuen N Carolina State Univ Dept Elect & Comp Engn Raleigh NC 27695 USA

ISBN: (纸本)9781479913039

Designing efficient demand management policies for charging Plug-in Hybrid Electrical Vehicles (PHEVs) and Plug-in Electrical Vehicles (PEVs) is becoming a vital issue as increasing numbers of these vehicles are being introduced to the power grid. In order to avoid overloads and satisfy customer preferences in terms of the time and cost of charging, a distribution-level charging algorithm can be formulated to solve a constrained optimization problem. In this paper, we have developed a novel network distributed algorithm for optimal charging of PHEVs/PEVs within a consensus algorithm framework. In our design, the global optimal power allocation under all local and global constraints is reached by peer-to-peer coordination of charging stations. Therefore, the need for a central control unit is eliminated. In this way, the single node congestion is avoided when the size of the problem is increased, and the system gains robustness against single link/node failures.

关键词： Plug-in Hybrid Electric Vehicle (PHEV) Plug-in Electric Vehicle (PEV) Karush-Kuhn-Tucker (KKT) Conditions consensus algorithms Decentralized Control

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DIFFUSIVE PARTICLE FILTERING FOR DISTRIBUTED MULTISENSOR ESTIMATION 41

DIFFUSIVE PARTICLE FILTERING FOR DISTRIBUTED MULTISENSOR EST...

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41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Mohammadi, Arash Asif, Amir Concordia Univ Concordia Inst Informat Syst Engn Montreal PQ Canada Concordia Univ Elect & Comp Engn Montreal PQ H3J 1P8 Canada

ISBN: (纸本)9781479999880

The paper proposes an on-line distributed implementation of the particle filter (DPF) for applications, where the sensing and consensus time scales are the same. We are motivated by state estimation problems in large, geographically-distributed agent/sensor networks, where bandwidth constraints limit the number of information transfers between neighbouring nodes. As an alternative to consensus strategies often used by the DPF, we propose a diffusive framework to eliminate the need of running the consensus step. In our Monte Carlo simulations, the proposed diffusion based DPF (D/DPF) outperforms the state-of-the-art consensus based DPF approaches in environments with limited bandwidth or/and intermittent connectivity.

关键词： consensus algorithms Distributed particle filters Diffusion algorithms Target tracking Intermittent connectivity

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On Opportunistic Selection of Common Randomness and LLR generation for Algebraic Group Secret-Key Generation 93

On Opportunistic Selection of Common Randomness and LLR gene...

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IEEE 93rd Vehicular Technology Conference (VTC-Spring)

作者： Joshi, Rohit Harshan, J. Indian Inst Technol Delhi Bharti Sch Telecom Technol & Management Delhi India Indian Inst Technol Delhi Dept Elect Engn Delhi India

ISBN: (纸本)9781728189642

It is well known that physical-layer key generation methods enable wireless devices to harvest symmetric keys by accessing the randomness offered by the wireless channels. Although two-user key generation is well understood, group secret-key (GSK) generation, wherein more than two nodes in a network generate secret-keys, still poses open problems. Recently, Manish Rao et al., have proposed the Algebraic Symmetrically Quantized GSK (A-SQGSK) protocol for a network of three nodes wherein the nodes share quantized versions of the channel realizations over algebraic rings, and then harvest a GSK. Although A-SQGSK protocol guarantees confidentiality of common randomness to an eavesdropper, we observe that the key-rate of the protocol is poor since only one channel in the network is used to harvest GSK. Identifying this limitation, in this paper, we propose an opportunistic selection method wherein more than one wireless channel is used to harvest GSKs without compromising the confidentiality feature, thereby resulting in remarkable improvements in the key-rate. Furthermore, we also propose a log-likelihood ratio (LLR) generation method for the common randomness observed at various nodes, so that the softvalues are applied to execute LDPC codes based reconciliation to reduce the bit mismatches among the nodes.

关键词： Wireless security physical-layer key generation group secret-key common randomness consensus algorithms

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