Two-Tier VoI Prioritization System on Requirement-Based Data Streaming toward IoT
Two-Tier VoI Prioritization System on Requirement-Based Data Streaming toward IoT
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DOI：
10.1155/2017/7892545
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发表时间：
2017
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影响因子：
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通讯作者：
Sunyanan Choochotkaew;Hirozumi Yamaguchi;T. Higashino
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文献类型：
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作者：
Sunyanan Choochotkaew;Hirozumi Yamaguchi;T. Higashino
在物联网世界中，人们在各种智能应用中利用来自传感器流的知识。感测设备的数量随着感测数据量的增加而沿着迅速增加。因此，本地网关的瓶颈问题引起了高度关注。一个示例场景是农村地区的智能老年人住宅，其中每个住宅安装数千个传感器，并且所有传感器都连接到资源有限且不稳定的2G/3G网络。由于有限的等待队列，瓶颈状态可能导致不可接受的延迟和重要数据的丢失。在现有解决方案的基础上，我们提出了一个两层优先级系统，以提高本地网关的信息质量，由VoI表示。所提出的系统已被设计为支持几个要求与几个相互冲突的标准共享感测流。我们的方法采用多标准决策分析技术来合并需求并评估VoI。我们介绍的框架，可以减少计算成本的预先计算。通过一个案例研究的建筑管理系统，我们已经表明，我们的合并算法可以提供0.995余弦相似度代表所有用户的需求和评估方法可以获得满意度值约3倍以上的天真策略的顶部列表数据。
Toward the world of Internet of Things, people utilize knowledge from sensor streams in various kinds of smart applications. The number of sensing devices is rapidly increasing along with the amount of sensing data. Consequently, a bottleneck problem at the local gateway has attracted high concern. An example scenario is smart elderly houses in rural areas where each house installs thousands of sensors and all connect to resource-limited and unstable 2G/3G networks. The bottleneck state can incur unacceptable latency and loss of significant data due to the limited waiting-queue. Orthogonally to the existing solutions, we propose a two-tier prioritization system to enhance information quality, indicated by VoI, at the local gateway. The proposed system has been designed to support several requirements with several conflicting criteria over shared sensing streams. Our approach adopts Multicriteria Decision Analysis technique to merge requirements and to assess the VoI. We introduce the framework that can reduce the computational cost by precalculation. Through a case study of building management systems, we have shown that our merge algorithm can provide 0.995 cosine-similarity for representing all user requirements and the evaluation approach can obtain satisfaction values around 3 times higher than the naive strategies for the top-list data.