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首页> 外文会议>DASFAA 2010;International conference on database systems for advances applications;International workshop on graph data management: Techniques and application;GDM 2010;International workshop on benchmarking of database management systems and data-oriented web technologies;BenchmarX 2010;International workshop on managing data quality in collaborative information systems;MCIS 2010;Workshop on social networks and social media mining on the web;SNSMW 2010;Data-intensive eScience workshop;DIEW 2010;International workshop on ubiquitous data management;UDM 2010 >Providing Scalable Data Services in Ubiquitous Networks
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Providing Scalable Data Services in Ubiquitous Networks

机译：在无处不在的网络中提供可扩展的数据服务

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摘要

Topology is a fundamental part of a network that governs connectivity between nodes, the amount of data flow and the efficiency of data flow between nodes. In traditional networks, due to physical limitations, topology remains static for the course of the network operation. Ubiquitous data networks (UDNs), alternatively, are more adaptive and can be configured for changes in their topology. This flexibility in controlling their topology makes them very appealing and an attractive medium for supporting 'anywhere, any place' communication. However, it raises the problem of designing a dynamic topology. The dynamic topology design problem is of particular interest to application service providers who need to provide cost-effective data services on a ubiquitous network. In this paper we describe algorithms that decide when and how the topology should be reconfigured in response to a change in the data communication requirements of the network. In particular, we describe and compare a greedy algorithm, which is often used for topology reconfiguration, with a non-greedy algorithm based on metrical task systems. Experiments show the algorithm based on metrical task system has comparable performance to the greedy algorithm at a much lower reconfiguration cost.
机译：拓扑是网络的基本部分，它控制节点之间的连接性，数据流的数量以及节点之间的数据流的效率。在传统网络中，由于物理限制，拓扑在网络运行过程中保持静态。另外，无处不在的数据网络（UDN）更具适应性，可以针对其拓扑的更改进行配置。控制拓扑的灵活性使它们非常吸引人，并且是支持“随处可见”通信的诱人媒介。但是，这带来了设计动态拓扑的问题。对于需要在普适网络上提供具有成本效益的数据服务的应用程序服务提供商而言，动态拓扑设计问题尤为重要。在本文中，我们描述了一些算法，这些算法决定了何时以及如何根据网络数据通信需求的变化重新配置拓扑。特别是，我们描述并比较了常用于拓扑重新配置的贪心算法和基于度量任务系统的非贪心算法。实验表明，基于度量任务系统的算法与贪婪算法具有可比的性能，且重构成本较低。

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