Efficient opportunistic sensing using mobile collaborative platform MOSDEN

P. Jayaraman, Charith Perera, Dimitrios Georgakopoulos, A. Zaslavsky
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引用次数: 68

Abstract

Mobile devices are rapidly becoming the primary computing device in people's lives. Application delivery platforms like Google Play, Apple App Store have transformed mobile phones into intelligent computing devices by the means of applications that can be downloaded and installed instantly. Many of these applications take advantage of the plethora of sensors installed on the mobile device to deliver enhanced user experience. The sensors on the smartphone provide the opportunity to develop innovative mobile opportunistic sensing applications in many sectors including healthcare, environmental monitoring and transportation. In this paper, we present a collaborative mobile sensing framework namely Mobile Sensor Data EngiNe (MOSDEN) that can operate on smartphones capturing and sharing sensed data between multiple distributed applications and users. MOSDEN follows a component-based design philosophy promoting reuse for easy and quick opportunistic sensing application deployments. MOSDEN separates the application-specific processing from the sensing, storing and sharing. MOSDEN is scalable and requires minimal development effort from the application developer. We have implemented our framework on Android-based mobile platforms and evaluate its performance to validate the feasibility and efficiency of MOSDEN to operate collaboratively in mobile opportunistic sensing applications. Experimental outcomes and lessons learnt conclude the paper.
使用移动协作平台MOSDEN的高效机会感测
移动设备正迅速成为人们生活中的主要计算设备。Google Play、Apple App Store等应用交付平台通过即时下载和安装的应用程序,将手机变成了智能计算设备。这些应用程序中的许多都利用安装在移动设备上的大量传感器来提供增强的用户体验。智能手机上的传感器为在医疗保健、环境监测和运输等许多领域开发创新的移动机会传感应用提供了机会。在本文中,我们提出了一个协作式移动传感框架,即移动传感器数据引擎(MOSDEN),它可以在智能手机上运行,在多个分布式应用程序和用户之间捕获和共享感知数据。MOSDEN遵循基于组件的设计理念,促进重用,以实现轻松快速的机会感测应用部署。MOSDEN将特定应用程序的处理从传感、存储和共享中分离出来。MOSDEN是可扩展的,需要应用程序开发人员最少的开发工作。我们已经在基于android的移动平台上实施了我们的框架,并评估了其性能,以验证MOSDEN在移动机会感测应用中协同运行的可行性和效率。实验结果和经验教训总结了本文。
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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