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Cross-Layer MAC Protocol for Unbiased Average Consensus Under Random Interference

IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS 2019年第2期5卷 320-333页

作者： Asensio-Marco, Cesar Alonso-Roman, Daniel Beferull-Lozano, Baltasar Univ Agder Dept Informat & Commun Technol N-4879 Grimstad Norway CSIC UVEG I2SysBio Valencia 46980 Spain Inst Tecnol Informat Valencia 46022 Spain

Wireless Sensor Networks have been revealed as a powerful technology to solve many different problems through sensor nodes cooperation. One important cooperative process is the so-called average gossip algorithm, which constitutes a building block to perform many inference tasks in an efficient and distributed manner. From the theoretical designs proposed in most previous work, this algorithm requires instantaneous symmetric links in order to reach average consensus. However, in a realistic scenario wireless communications are subject to interferences and other environmental factors, which results in random instantaneous topologies that are, in general, asymmetric. Consequently, the estimation of the average obtained by the gossip algorithm is a random variable, which its realizations may significantly differ from the average value. In the present paper, we first derive a sufficient conditions for any MAC protocol to guarantee that the expected value of the obtained consensus random variable is the average of the initial values (unbiased estimator), while the variance of the estimator is minimum. Then, we propose a cross-layer and distributed link scheduling protocol based on carrier sense, which besides avoiding collisions, ensures both an unbiased estimation and close to minimum variance values. Extensive numerical results are presented to show the validity and efficiency of the proposed approach.

关键词： gossip algorithm MAC protocol cross-layer design asymmetric communications WSN

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Reducing classifier overconfidence against adversaries through graph algorithms

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MACHINE LEARNING 2023年第7期112卷 2619-2651页

作者： Teixeira, Leonardo Jalaian, Brian Ribeiro, Bruno Purdue Univ Dept Comp Sci W Lafayette IN 47907 USA US Army Res Lab Adelphi MD USA

In this work we show that deep learning classifiers tend to become overconfident in their answers under adversarial attacks, even when the classifier is optimized to survive such attacks. Our work draws upon stochastic geometry and graph algorithms to propose a general framework to replace the last fully connected layer and softmax output. This framework (a) can be applied to any classifier and (b) significantly reduces the classifier's overconfidence in its output without much of an impact on its accuracy when compared to original adversarially-trained classifiers. Its relative effectiveness increases as the attacker becomes more powerful. Our use of graph algorithms in adversarial learning is new and of independent interest. Finally, we show the advantages of this last-layer softmax replacement over image tasks under common adversarial attacks.

关键词： Adversarial robustness Overconfidence gossip algorithm

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A biology-inspired model for the automatic dissemination of information in P2P networks

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MULTIAGENT AND GRID SYSTEMS 2007年第1期3卷 87-104页

作者： Gueret, C. Monmarche, N. Slimane, M. Univ Tours Lab Informat 64Ave Jean Portalis F-37200 Tours France

The Personal Intelligent Agents Framework (PIAF) is a framework developped in the context of research on smart web browsers. Compared to a classical browser, this smart browser should help the user to find and share information using the Internet network. This paper presents algorithms used in PIAF for the selective dissemination of information in a P2P network. They use ideas from epidemic systems and are based on an artificial ant colony model. The main contribution made to the domain of selective information diffusion is the use of estimated profiles defined by pheromone trails associated to connections between peers.

关键词： P2P network gossip algorithm artificial ants

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Opinion Formation over Signed gossip Networks

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SICE Journal of Control, Measurement, and System Integration 2017年第3期10卷 266-273页

作者： Linh Thi Hoai Nguyen Takayuki Wada Izumi Masubuchi Toru Asai Yasumasa Fujisaki Graduate School of Information Science and Technology Osaka University Graduate School of System Informatics Kobe University Graduate School of Engineering Nagoya University

Opinion formation is investigated over signed gossip networks, where asymptotic and transient opinion behaviors are analyzed in detail. The network is modeled by a connected signed graph, where each edge of the graph has positive or negative weight, i.e., these edges represent friendly or hostile relationship. Interactions each of which occurs between two persons chosen randomly follow an asynchronous procedure. Then it is shown that their opinions always converge in mean square and converge almost surely. A convergence time is defined as the smallest time such that it takes for the values of nodes to get within a given neighborhood of the consensus value with high probability, regardless of initial state. An upper bound and a lower bound of the convergence time of the gossip algorithm are given in terms of a structure of the given network.

关键词： convergence time gossip algorithm opinion dynamics signed graph social networks

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A Parallel Distributed algorithm for the Power SVD Method 22

A Parallel Distributed Algorithm for the Power SVD Method

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22nd IEEE International Workshop on Signal Processing Advances in Wireless Communications (IEEE SPAWC)

作者： Li, Haying Wu, Sissi Xiaoxiao Li, Qiang Scaglione, Anna Shenzhen Univ Coll Elec & Info Eng Shenzhen Peoples R China UESTC Sch Info & Comm Eng Chengdu Peoples R China Arizona State Univ Sch Elect Comp & Energy Engn Tempe AZ USA

ISBN: (纸本)9781665428514

In this work, we study how to implement a distributed algorithm for the power method in a parallel manner. As the existing distributed power method is usually sequentially updating the eigenvectors, it exhibits two obvious disadvantages: 1) when it calculates the hth eigenvector, it needs to wait for the results of previous (h - 1) eigenvectors, which causes a delay in acquiring all the eigenvalues;2) when calculating each eigenvector, it needs a certain cost of information exchange within the neighboring nodes for every power iteration, which could be unbearable when the number of eigenvectors or the number of nodes is large. This motivates us to propose a parallel distributed power method, which simultaneously calculates all the eigenvectors at each power iteration to ensure that more information could be exchanged in one shaking-hand of communication. We are particularly interested in the distributed power method for both an eigenvalue decomposition (EVD) and a singular value decomposition (SVD), wherein the distributed process is proceed based on a gossip algorithm. It can be shown that, under the same condition, the communication cost of the gossip-based parallel method is only 1/H times of that for the sequential counterpart, where H is the number of eigenvectors we want to compute, while the convergence time and error performance of the proposed parallel method are both comparable to those of its sequential counterpart.

关键词： The power method distributed users parallel updating gossip algorithm

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Distributed Field Estimation algorithms in Vehicular Sensor Networks

Distributed Field Estimation Algorithms in Vehicular Sensor ...

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73rd IEEE Vehicular Technology Conference (VTC Spring)

作者： Schabus, Dietmar Zemen, Thomas Pucher, Michael Telecommun Res Ctr Vienna FTW Vienna Austria

ISBN: (纸本)9781424483310

This paper deals with cooperative reconstruction of environmental variables (e.g., temperature) along a road by a vehicular sensor network using wireless communication. Vehicles take repeated measurements and approximate the environment using a set of basis functions. We investigate the applicability and performance of popular averaging techniques (gossiping and consensus propagation) on the basis coefficients, and propose a simpler approach to avoid divergence problems. We have developed a graphical simulation environment to study the behavior of different algorithms in this scenario and we show simulation results which support our simplified approach.

关键词： wireless sensor network mobile sensors gossip algorithm consensus propagation

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A new solution for resisting gray hole attack in mobile ad-hoc networks

A new solution for resisting gray hole attack in mobile ad-h...

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2nd International Conference on Communications and Networking in China

作者： Chen Wei Long Xiang Bai Yuebin Gao Xiaopeng Beihang Univ Sch Comp Sci Beijing Peoples R China

ISBN: (纸本)9781424410088

Mobile Ad Hoc Networks are vulnerable to various types of Denial of Service (DoS) attacks for the absence of fixed network infrastructure. The Gray Hole attack is a type of DoS attacks. In this attack, an adversary silently drops some or all of the data packets sent to it for further forwarding even when no congestion occurs. In this paper, a new solution against the Gray Hole attack is proposed. The proposal is consisted of two related algorithms: the key management algorithm based on gossip protocol and the detection algorithm based on aggregate signatures. The simulation results using ns-2 show that in a moderately changing network, most of the malicious nodes could be detected, the routing packet overhead was low, and the packet delivery rate has been improved.

关键词： ad hoc networks DoS gossip algorithm aggregate signature ns-2

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When Infinite Flow is Sufficient for Ergodicity 49

When Infinite Flow is Sufficient for Ergodicity

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49th IEEE Conference on Decision and Control (CDC)

作者： Touri, Behrouz Nedic, Angelia Univ Illinois Dept Ind & Enterprise Syst Engn Urbana IL 61801 USA

ISBN: (纸本)9781424477463

We consider the consensus and ergodicity for a random linear discrete-time system driven by stochastic matrices. We focus on independent models with certain properties, and we study the ergodicity and consensus of such random models through a novel property, termed infinite flow property. Our key result is the establishment that for a class of independent random models, this property is a necessary and sufficient condition for ergodicity. Using this result, we show that the ergodicity of these models and the ergodicity of their expected models are the same. The result provides us with new tools for studying various aspects of dynamic networks and beyond. We demonstrate the potential use of our key result through several different applications. In particular, we apply it to provide a generalization of the randomized gossip algorithm and to study a consensus over a dynamic network with link failures. Also, we use the result to investigate necessary and sufficient conditions for the ergodicity of an equal-neighbor average algorithm on Erdos-Renyi random graphs. Finally, we demonstrate that our result can be employed to provide an alternative proof of the second Borel-Cantelli lemma.

关键词： Ergodicity product of random stochastic matrices linear random model gossip algorithm link failure Borel-Cantelli lemma

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Who is the fairest of them all?

Who is the fairest of them all?

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50th Annual Allerton Conference on Communication, Control, and Computing (Allerton)

作者： Borkar, Vivek S. Makhijani, Rahul M. Indian Inst Technol Dept Elect Engn Mumbai 400076 Maharashtra India

We present a gossip algorithm for distributed computation of the Perron-Frobenius eigenvector of a non-negative matrix. Potential applications to ranking schemes are given.

ISBN: (纸本)9781467345392;9781467345378

We present a gossip algorithm for distributed computation of the Perron-Frobenius eigenvector of a non-negative matrix. Potential applications to ranking schemes are given.

关键词： gossip algorithm Perron-Frobenius eigenvector stochastic approximation ranking

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Distributed Compression and the Blind Zone Recognition 12

Distributed Compression and the Blind Zone Recognition

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12th International Wireless Communications & Mobile Computing Conference (IWCMC)

作者： Wu, Shaochuan Pan, Siqi Ma, Kangjian Wei, Yuming Harbin Inst Technol Sch Elect & Informat Engn Harbin Peoples R China

ISBN: (纸本)9781509003044

Wireless sensor network (WSN) technology provides support infrastructure to solve blind zone coverage. Previous studies mainly focus on deployment and management of sensor nodes for enhancing signal coverage on a specific zone. But few of them are on coordinating several nodes to recognize blind zone. Moreover, it is a great challenge how to extract, transmit and process information energy efficiently in a decentralized way. In this paper, we propose a distributed algorithm for convenient and efficient blind zone recognition based on the early work on the unbiased broadcast gossip algorithm (UBGA) and the compressed sensing. Using UBGA, a faster consensus algorithm, the system can simultaneously compute the compressed data based on compressed sensing technique and disseminate them throughout the network. From these compressed data one can reconstruct the original data with approximate accuracy by querying any sensor values using the gradient projection strategy. Simulation results illustrate that our solution, proposed in this paper, can effectively recognize blind zone.

关键词： Distributed Compression Blind Zone Recognition gossip algorithm

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