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21st International Conference on Telecommunications (ICT)

作者： Wei, Yanheng Wang, Junyi Gong, Zhishuai Guilin Univ Elect Technol Guangxi Expt Ctr Informat Sci Guilin 541004 Peoples R China Guilin Univ Elect Technol Key Lab Cognit Radio & Informat Proc Guilin 541004 Peoples R China

ISBN: (纸本)9781479951413

Overlay multicast is an efficient communication scheme for multipoint communication applications. This paper focuses on the transmission isolation and unbalanced load allocation problems of multi-rate multimedia transmission over embedded overlay topology where multicast receivers in the same session request service at different rates commensurate with their requirements. We propose a novel data distribution scheme by adopting gossip algorithm to overcome the transmission isolation problem via implementing cross-layer data transmission. More leaf members are involved in the data distribution process to share load stress for cluster leaders leading to more balanced data distribution structure. Simulation results show that gossip-based protocol, without transmission isolation, can reasonably build and maintain a more balanced overlay topology than the traditional multicast protocol.

关键词： layered overlay multicast overlay network gossip algorithm load-balancing

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GoDisco: Selective gossip Based Dissemination of Information in Social Community Based Overlays

GoDisco: Selective Gossip Based Dissemination of Information...

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12th International Conference on Distributed Computing and Networking

作者： Datta, Anwitaman Sharma, Rajesh Nanyang Technol Univ Sch Comp Engn Singapore Singapore

ISBN: (纸本)9783642176784

We propose and investigate a gossip based, social principles and behavior inspired decentralized mechanism (Go Disco) to disseminate information in online social community networks, using exclusively social links and exploiting semantic context to keep the dissemination process selective to relevant nodes. Such a designed dissemination scheme using gossiping over a egocentric social network is unique and is arguably a concept whose time has arrived, emulating word of mouth behavior and can have interesting applications like probabilistic publish/subscribe, decentralized recommendation and contextual advertisement systems, to name a few. Simulation based experiments show that despite using only local knowledge and contacts, the system has good global coverage and behavior.

关键词： gossip algorithm community networks selective dissemination social network egocentric

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Distributed Particle Filter using Pairwise K-Selective gossip for Cognitive Radio Positioning 19

Distributed Particle Filter using Pairwise K-Selective Gossi...

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19th International Symposium on Wireless Personal Multimedia Communications (WPMC)

作者： Zhao, Yubin Li, Xiaofan Zhang, Sha Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen 518055 Peoples R China Shenzhen Yaoyuan Technol Limited Shenzhen 518055 Peoples R China Shenzhen Inst Radio Testing & Tech Shenzhen 518000 Peoples R China

ISBN: (纸本)9784904020098

The cognitive radio positioning system requires a distributed localization algorithm, since the secondary uses (SUs) can not communication with primary users (PUs) directly. The localization algorithm should also be robust to the topology changes of SUs due to the opportunistic access nature. In this paper, we propose a distributed particle filtering method to locate the PU's position. The ranging measurement of PU is obtained through the extended sensing strategy (ESS). The particles for each node is generated locally and transmitted via a K-selective gossip algorithm. Our algorithm is implemented without a topology management scheme and the communication overhead is lower than other distributed particle filter schemes. Simulations demonstrate that the estimation performance of our algorithm is accurate and approach to the centralized scheme with low communication cost.

关键词： cognitive radio network extended sensing strategy distributed particle filter gossip algorithm

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A gossip-based TDOA Distributed Localization algorithm for Wireless Sensor Networks

A Gossip-based TDOA Distributed Localization Algorithm for W...

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International Symposium on Instrumentation and Measurement, Sensor Network and Automation

作者： Wen Cui Shaochuan Wu Yuze Wang Yuanxu Shan School of Electronics and Information Engineering Harbin Institute of Technology Harbin China

ISBN: (纸本)9781479927173

Distributed localization has been established as a key problem in wireless sensor networks and many localization algorithms have been proposed in this area. In this paper, a novel distributed TDOA passive localization method based on gossip algorithms is proposed, which can obviously improve the performance of the previous algorithms. According to our numerical results, adding the gossip mechanism into the TDOA localization frame not only significantly improves the positioning accuracy, but also contributes to the situation that all the beacon nodes acquire the same coordinates of the target sensor node which we call it reaches a distributed average consensus for all the beacon nodes. This is sometimes very useful for special applications such as military precision strike and illegal radio station positioning. We compared the newly designed localization algorithms with the classical Taylorseries estimation algorithm for TDOA localization, and the numerical results are also provided to prove the effectiveness and advantage of our novel algorithm.

关键词： gossip algorithm TDOA localization wireless sensor networks Taylor-series estimation

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Cooperative and Parallel Fog Discovery and Pareto Optimal Fog Commerce Bargaining

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IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS 2022年第4期9卷 1112-1121页

作者： Sim, Kwang Mong University of Ottawa ON Canada

While fog resource discovery involves propagating resource requests to a huge number of fog nodes, fog commerce refers to the activity of buying and selling fog resources. This work devises: 1) the KM-gossip algorithm for bolstering fog discovery and 2) a bargaining mechanism for pricing fog resources. The KM-gossip algorithm is a generalization of the gossip algorithm. It uses K broker agents (BAs) to cooperatively ``gossip'' requests among themselves, and in parallel, each BA relays the requests to M fog nodes. While computational complexity analysis validates that the KM-gossip algorithm has logarithmic time complexity (i.e., it is computationally efficient), empirical results show that it significantly outperforms the existing gossip and flooding algorithms. Supplementing and complementing previous empirical results, game-theoretic analysis in this work validates that the bargaining mechanism generates Pareto optimal (economically efficient) solutions. The solutions also satisfy the famous Nash's axioms that prescribe highly desirable properties of bargaining solutions.

关键词： Barium Edge computing Relays Pareto optimization Cloud computing Business Time complexity Bargaining theory computational complexity analysis distributed intelligent systems gossip algorithm

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Average consensus on general strongly connected digraphs

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AUTOMATICA 2012年第11期48卷 2750-2761页

作者： Cai, Kai Ishii, Hideaki Univ Toronto Dept Elect & Comp Engn Toronto ON M5S 3G4 Canada Tokyo Inst Technol Dept Computat Intelligence & Syst Sci Midori Ku Yokohama Kanagawa 2268502 Japan

We study the average consensus problem of multi-agent systems for general network topologies with unidirectional information flow. We propose two linear distributed algorithms, deterministic and gossip, respectively for the cases where the inter-agent communication is synchronous and asynchronous. In both cases, the developed algorithms guarantee state averaging on arbitrary strongly connected digraphs;in particular, this graphical condition does not require that the network be balanced or symmetric, thereby extending previous results in the literature. The key novelty of our approach is to augment an additional variable for each agent, called "surplus", whose function is to locally record individual state updates. For convergence analysis, we employ graph-theoretic and nonnegative matrix tools, plus the eigenvalue perturbation theory playing a crucial role. (c) 2012 Elsevier Ltd. All rights reserved.

关键词： Multi-agent consensus Surplus-based averaging gossip algorithm Directed graph Eigenvalue perturbation

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A robust distributed system incremental cost estimation algorithm for smart grid economic dispatch with communications information losses

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JOURNAL OF NETWORK AND COMPUTER APPLICATIONS 2016年 59卷 315-324页

作者： Zhang, Yuan Rahbari-Asr, Navid Chow, Mo-Yuen N Carolina State Univ Dept Elect & Comp Engn Raleigh NC 27606 USA

With an increasing number of controllable distributed energy resources deployed and integrated into the power system, how to economically manage these distributed resources will become a challenge for the future smart grid. To solve the issue, consensus based distributed economic dispatch algorithms have been introduced in the literature as computationally scalable approaches. However, in real-world applications with imperfect communications networks, the performance of consensus-based economic dispatch algorithms degrades when information losses occur. In this paper, a robust distributed system incremental cost estimation (RICE) algorithm is introduced to solve the Economic Dispatch Problem (EDP) in a smart grid environment in a distributed way considering communications information losses. Unlike the existing consensus-based algorithms to solve EDP, RICE algorithm has two updating layers running in parallel in each distributed controller: one layer uses the gossip updating rule to estimate the system's average power mismatch, while the other layer uses the consensus updating rule to update the system Incremental Cost (IC) estimation. In this approach, the vulnerability of consensus-based algorithms to communications information losses is eliminated. The convergence and optimality of the algorithm are guaranteed as long as the undirected communications topology among local controllers is connected. Several case studies are presented to illustrate the performance of the proposed algorithm, and show the robustness under different information loss scenarios with different communications topologies. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Consensus algorithm Distributed energy management Economic dispatch gossip algorithm Multi-agent system Information loss

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Distributed Economic Dispatch Under Random Time-Varying Digraph

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2024年第9期20卷 11139-11148页

作者： Wang, Rui Li, Qi Liu, Huimin Qufu Normal Univ Sch Math Sci Qufu 273165 Peoples R China Qilu Univ Technol Shandong Acad Sci Inst Automat Jinan 250316 Peoples R China

The transmission losses exist in power systems, and the communication network of smart grids is not fixed and reliable because of the intermittency of distributed renewable generations, packet loss, and uncertainty. Taking the issues into consideration in this work, we presented a distributed economic dispatch algorithm to address them. Assumed that the communication is random time-varying in the communication network and we proposed a distributed algorithm for the economic dispatch with B coefficient-based transmission losses. Instead of using simulation results to illustrate the effectiveness of the algorithm, the convergence and optimality of the designed algorithm are studied in this article. Furthermore, we show that the convergent speed is determined by the second largest eigenvalue (in modulus). Several simulation and comparison studies are given to show the effectiveness and superiority of the algorithm.

关键词： Propagation losses Smart grids Convergence Communication networks Optimization Distributed algorithms Generators Distributed economic dispatch (DED) gossip algorithm smart grid time-varying digraph transmission losses

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Neural Networks-Aided Insider Attack Detection for the Average Consensus algorithm

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IEEE ACCESS 2020年 8卷 51871-51883页

作者： Li, Gangqiang Wu, Sissi Xiaoxiao Zhang, Shengli Li, Qiang Shenzhen Univ Coll Elect & Informat Engn Shenzhen 518060 Peoples R China Peng Cheng Lab Shenzhen 518055 Peoples R China UESTC Sch Informat & Commun Engn Chengdu 611731 Peoples R China

To support the big-data processing needs of large-scale deployments of smart devices, there is significant interest in moving from cloud-computing to multi-agent (fog-computing) models, given these algorithms scalability and self-healing properties with respect to nodes and link failures. However, these algorithms are often based on the average consensus primitive, which is, unfortunately, vulnerable to data injection attacks. Recognizing this challenge, this work proposes three novel methods for detecting and localizing adversarial nodes using neural network (NN) models. The methods proposed are based on fully distributed algorithms, wherein each node locally updates its local states by exchanging information with its neighbors without supervision. Compared to the state-of-the-art, the proposed approach leverages the automatic learning characteristics of NN to reduce the dependence on pre-designed models and human expertise in complex internal attack scenarios. Simulation results show that the NN-based methods can significantly improve the attacker detection and localization performance.

关键词： Artificial neural networks Peer-to-peer computing Protocols Cloud computing Intrusion detection Simulation gossip algorithm average consensus neural network (NN) insider attack detection and localization

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A combined hardware-software approach for acoustic sensor network synchronization

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SIGNAL PROCESSING 2015年 107卷 171-184页

作者： Schmalenstroeer, Joerg Jebramcik, Patrick Haeb-Umbach, Reinhold Univ Paderborn Dept Commun Engn Paderborn Germany

In this paper we present an approach for synchronizing a wireless acoustic sensor network using a two-stage procedure. First the clock frequency and phase differences between pairs of nodes are estimated employing a two-way message exchange protocol. The estimates are further improved in a Kalman filter with a dedicated observation error model. In the second stage network-wide synchronization is achieved by means of a gossiping algorithm which estimates the average clock frequency and phase of the sensor nodes. These averages are viewed as frequency and phase of a virtual master clock, to which the clocks of the sensor nodes have to be adjusted. The amount of adjustment is computed in a specific control loop. While these steps are done in software, the actual sampling rate correction is carried out in hardware by using an adjustable frequency synthesizer. Experimental results obtained from hardware devices and software simulations of large scale networks are presented. (C) 2014 Elsevier B.V. All rights reserved.

关键词： gossip algorithm Clock skew Sensor network

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