A Generic Large Scale Simulator for Ubiquitous Computing

Miquel Martin, P. Nurmi
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引用次数: 73

Abstract

The complexity associated to gathering and processing contextual data makes testing mobile context-aware applications and services difficult. Furthermore, the lack of standard data sets and simulation tools makes the evaluation of machine learning algorithms in context-aware settings an even harder task. To ease the situation, we introduce a generic simulator that has been designed with the above mentioned purposes in mind. The simulator has also proven to be a good demonstration tool for mobile services and applications that are aimed at groups. The simulator is highly customizable and it can output context information of individual entities both through an interactive GUI and as data streams consisting of comma separated values. To support a wide range of tasks and scenarios, we have separated the three main information sources: behavior of agents, the scenario being simulated and the used context variable. The simulator has been implemented using Java, and the data streams have been made available through a Web service interface
泛在计算的通用大规模模拟器
与收集和处理上下文数据相关的复杂性使得测试移动上下文感知应用程序和服务变得困难。此外,缺乏标准数据集和模拟工具使得在上下文感知设置中评估机器学习算法变得更加困难。为了缓解这种情况,我们引入了一个通用的模拟器,它是根据上述目的设计的。该模拟器还被证明是针对群体的移动服务和应用程序的良好演示工具。模拟器是高度可定制的,它可以通过交互式GUI输出单个实体的上下文信息,也可以作为由逗号分隔值组成的数据流输出。为了支持广泛的任务和场景,我们分离了三个主要信息源:代理的行为、被模拟的场景和使用的上下文变量。模拟器已使用Java实现,数据流已通过Web服务接口提供
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