用于自动视频监控系统的移动自组织云

Minseok Jang, Myong-Soon Park, Sayed Chhattan Shah
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引用次数: 4

摘要

部署在移动环境中的移动自动视频监控系统用于监控和分析多种情况,并实时采取必要的行动。这些系统包括配备大量传感器的各种移动节点,并涉及复杂图像和视频处理算法的应用。这些算法的执行需要大量的计算和存储资源。要解决这个问题,传统的方法是将收集到的数据发送到通过基于基础设施的系统(如蜂窝网络)访问的云上的应用程序。该方法存在传输能耗高、通信延迟等问题。此外,这种方法不能用于没有现有通信基础设施的情况。本文重点介绍了一种最新的方法,其中通过移动自组织网络连接的多个移动设备组合在一起,创建一个称为移动自组织云的虚拟超级计算节点,然后用于支持自动视频监控应用程序的执行。为了满足自动化视频监控应用的实时性要求,提出了一种任务分配方案。与现有方案相比,提出的方案侧重于限期任务和能源效率。
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A mobile ad hoc cloud for automated video surveillance system
Mobile automated video surveillance systems deployed in mobile environments are used to monitor and analyze numerous situations and take necessary actions in real time. These systems include various mobile nodes equipped with numerous sensors and involve application of sophisticated image and video processing algorithms. The execution of these algorithms requires a vast amount of computing and storage resources. To address the issue a traditional approach is to send collected data to an application on a cloud accessible through an infrastructure-based system such as cellular network. This approach has several issues such as high transmission energy consumption and communication latency. In addition, this approach cannot be used in situations where pre-existing communication infrastructure is not available. This paper focuses on a recent approach in which multiple mobile devices interconnected through a mobile ad hoc network are combined to create a virtual supercomputing node called a mobile ad hoc cloud which is then used to support execution of automated video surveillance application. In order to fulfil real-time requirements associated with automated video surveillance application, a task allocation scheme has been proposed. Compared to existing schemes, proposed scheme focuses on deadline-oriented tasks and energy efficiency.
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