Byzantine Agreement with Less Communication

The development of reliable distributed systems often relies on Byzantine Agreement (BA) [26]. In this problem, a set of correct processes aim to reach a common decision, despite the presence of malicious ones. BA has been around for four decades, yet practical use-cases for it in large-scale systems have emerged only in the last decade. One major application for BA is cryptocurrencies. For example, Bitcoin [30], the rst cryptocurrency, requires a large set of users to agree on the state of the blockchain. Since Bitcoin is a real currency with real value, the need to protect it against Byzantine users is crucial. Following Bitcoin, many other blockchains and FinTech platforms have emerged, e.g., [6,21,30,36]. Consequently, an efficient implementation, in terms of communication, has become one of the main foci of BA solutions.

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Monitoring and Controlling Large Scale Systems

Advances in Systems Analysis, Software Engineering, and High Performance Computing - Large-Scale Distributed Computing and Applications ◽

10.4018/978-1-61520-703-9.ch007 ◽

2010 ◽

pp. 141-167

Author(s):

Valentin Cristea ◽

Ciprian Dobre ◽

Corina Stratan ◽

Florin Pop

Keyword(s):

Distributed Systems ◽

Performance Management ◽

High Performance ◽

Large Scale ◽

Survey Study ◽

Large Scale Systems ◽

General Management ◽

Large Numbers ◽

Scalable Monitoring ◽

High Performance Computers

The architectural shift presented in the previous chapters towards high performance computers assembled from large numbers of commodity resources raises numerous design issues and assumptions pertaining to traceability, fault tolerance and scalability. Hence, one of the key challenges faced by high performance distributed systems is scalable monitoring of system state. The aim of this chapter is to realize a survey study of existing work and trends in distributed systems monitoring by introducing the involved concepts and requirements, techniques, models and related standardization activities. Monitoring can be defined as the process of dynamic collection, interpretation and presentation of information concerning the characteristics and status of resources of interest. It is needed for various purposes such as debugging, testing, program visualization and animation. It may also be used for general management activities, which have a more permanent and continuous nature (performance management, configuration management, fault management, security management, etc.). In this case the behavior of the system is observed and monitoring information is gathered. This information is used to make management decisions and perform the appropriate control actions on the system. Unlike monitoring which is generally a passive process, control actively changes the behavior of the managed system and it has to be considered and modeled separately. Monitoring proves to be an essential process to observe and improve the reliability and the performance of large-scale distributed systems.

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Beernet

Technological Innovations in Adaptive and Dependable Systems ◽

10.4018/978-1-4666-0255-7.ch017 ◽

2012 ◽

pp. 282-304

Author(s):

B. Mejías ◽

P. Van Roy

Keyword(s):

Distributed Systems ◽

Large Scale ◽

Single Point ◽

Peer To Peer ◽

Self Healing ◽

Decentralized System ◽

Large Scale Systems ◽

Self Organized ◽

Peer To Peer Networks ◽

Control And Synchronization

Distributed systems with a centralized architecture present the well known problems of single point of failure and single point of congestion; therefore, they do not scale. Decentralized systems, especially as peer-to-peer networks, are gaining popularity because they scale well, and do not need a server to work. However, their complexity is higher due to the lack of a single point of control and synchronization, and because consistent decentralized storage is difficult to maintain when data constantly evolves. Self-management is a way of handling this higher complexity. In this paper, the authors present a decentralized system built with a structured overlay network that is self-organized and self-healing, providing a transactional replicated storage for small or large scale systems.

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Fast Consensus of Networked Multiagent Systems with Two-Hop Network

Mathematical Problems in Engineering ◽

10.1155/2015/953464 ◽

2015 ◽

Vol 2015 ◽

pp. 1-7

Author(s):

Jinfeng Gao ◽

Bin Bu ◽

Lihui Feng ◽

Minming Gu

Keyword(s):

Distributed Control ◽

Multiagent Systems ◽

Large Scale ◽

The State ◽

Convergence Speed ◽

Consensus Protocol ◽

Large Scale Systems ◽

Numerical Example ◽

Communication Topology ◽

Networked Multiagent Systems

This paper studies the consensus convergence speed of multiagent systems (MASs) from two aspects including communication topology and the state of agents. Two-hop network is considered in the communication topology. A novel consensus protocol that includes the information of the states motions and their integrals is introduced. And the protocol has much faster convergence speed by choosing some appropriate weight values. The protocol can be applied to distributed control and large-scale systems. A numerical example is presented to illustrate the effectiveness and superiority of the proposed method.

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Human performance in monitoring and controlling hierarchical large scale systems

PsycEXTRA Dataset ◽

10.1037/e574112012-007 ◽

1983 ◽

Author(s):

Richard L. Henneman ◽

William B. Rouse

Keyword(s):

Large Scale ◽

Human Performance ◽

Large Scale Systems

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Is economic inequality a universal evil?

Voprosy Ekonomiki ◽

10.32609/0042-8736-2019-4-91-106 ◽

2019 ◽

pp. 91-106 ◽

Cited By ~ 2

Author(s):

Rostislav I. Kapeliushnikov

Keyword(s):

Quantitative Data ◽

Large Scale ◽

Economic Inequality ◽

The State ◽

Fair Play ◽

Left Wing ◽

Ordinary People ◽

The Public ◽

Discursive Power ◽

A Current

Using published estimates of inequality for two countries (Russia and USA) the paper demonstrates that inequality measuring still remains in the state of “statistical cacophony”. Under this condition, it seems at least untimely to pass categorical normative judgments and offer radical political advice for governments. Moreover, the mere practice to draw normative conclusions from quantitative data is ethically invalid since ordinary people (non-intellectuals) tend to evaluate wealth and incomes as admissible or inadmissible not on the basis of their size but basing on whether they were obtained under observance or violations of the rules of “fair play”. The paper concludes that a current large-scale ideological campaign of “struggle against inequality” has been unleashed by left-wing intellectuals in order to strengthen even more their discursive power over the public.

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