Network characteristics emerging from agent interactions in balanced distributed system.

Q1 Mathematics

Computational Social Networks Pub Date : 2015-01-01 Epub Date: 2015-07-15 DOI:10.1186/s40649-015-0019-2

Mahdi Abed Salman, Cyrille Bertelle, Eric Sanlaville

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引用次数: 2

Abstract

A distributed computing system behaves like a complex network, the interactions between nodes being essential information exchanges and migrations of jobs or services to execute. These actions are performed by software agents, which behave like the members of social networks, cooperating and competing to obtain knowledge and services. The load balancing consists in distributing the load evenly between system nodes. It aims at enhancing the resource usage. A load balancing strategy specifies scenarios for the cooperation. Its efficiency depends on quantity, accuracy, and distribution of available information. Nevertheless, the distribution of information on the nodes, together with the initial network structure, may create different logical network structures. In this paper, different load balancing strategies are tested on different network structures using a simulation. The four tested strategies are able to distribute evenly the load so that the system reaches a steady state (the mean response time of the jobs is constant), but it is shown that a given strategy indeed behaves differently according to structural parameters and information spreading. Such a study, devoted to distributed computing systems (DCSs), can be useful to understand and drive the behavior of other complex systems.

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平衡分布式系统中agent交互产生的网络特征。

分布式计算系统的行为就像一个复杂的网络，节点之间的交互是要执行的作业或服务的基本信息交换和迁移。这些行为是由软件代理执行的，它们的行为就像社会网络的成员，通过合作和竞争来获得知识和服务。负载均衡是指在系统各节点之间均匀分配负载。它旨在提高资源的利用率。负载平衡策略指定了协作的场景。它的效率取决于可用信息的数量、准确性和分布。然而，信息在节点上的分布，加上初始的网络结构，可能会产生不同的逻辑网络结构。本文通过仿真，在不同的网络结构上测试了不同的负载均衡策略。四种测试策略均能均匀分配负载，使系统达到稳态(作业的平均响应时间恒定)，但结果表明，给定的策略确实会根据结构参数和信息传播而表现出不同的行为。这种专门研究分布式计算系统(dcs)的研究对于理解和驱动其他复杂系统的行为非常有用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Computational Social Networks Mathematics-Modeling and Simulation

自引率

0.00%

发文量

审稿时长

13 weeks

期刊介绍： Computational Social Networks showcases refereed papers dealing with all mathematical, computational and applied aspects of social computing. The objective of this journal is to advance and promote the theoretical foundation, mathematical aspects, and applications of social computing. Submissions are welcome which focus on common principles, algorithms and tools that govern network structures/topologies, network functionalities, security and privacy, network behaviors, information diffusions and influence, social recommendation systems which are applicable to all types of social networks and social media. Topics include (but are not limited to) the following: -Social network design and architecture -Mathematical modeling and analysis -Real-world complex networks -Information retrieval in social contexts, political analysts -Network structure analysis -Network dynamics optimization -Complex network robustness and vulnerability -Information diffusion models and analysis -Security and privacy -Searching in complex networks -Efficient algorithms -Network behaviors -Trust and reputation -Social Influence -Social Recommendation -Social media analysis -Big data analysis on online social networks This journal publishes rigorously refereed papers dealing with all mathematical, computational and applied aspects of social computing. The journal also includes reviews of appropriate books as special issues on hot topics.