首页> 外文会议>IEEE Region 10 Conference;TENCON 2012 >Data Aggregation and Data Fusion Techniques in WSN/SANET Topologies - A Critical Discussion -
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Data Aggregation and Data Fusion Techniques in WSN/SANET Topologies - A Critical Discussion -

机译:WSN / SANET拓扑中的数据聚合和数据融合技术 - 一个关键讨论 -

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WSN and SANET topologies generate huge amount of heterogeneous data, which has to be transmitted in a dynamically changing network infrastructure. Especially in the domain of wireless low-power applications, the energy-efficiency and the prioritisation of communication tasks is critical. Several research areas deal with this issue. They optimising the respective hardware components as well as the protocols within the PHY, MAC or network layer. But for an optimised media transport in the topology also the data management and the task scheduling on the application layer is essential. Here, the key challenge is to minimise the data amount without decreasing the information quality. Related research work in the field of data aggregation and data fusion offers interesting techniques for an efficient data handling. In this paper, we discuss usual ways for data aggregation, including the adapted communication process. We critically analyse the benefits in theory and compare these conceptual advantages with measured real-world results. The evaluation was done in two steps. The first one is based on simulation scenarios of typical WSN/SANET applications. In a second step, we implement a demonstrator platform for a respective real-world environment. The test bed configuration is similar to the simulation scenario and provides comparable data. Based on the results and the respective analysis, we propose feasible methods for optimising data aggregation techniques. We clarify, that these improvements are essential for an efficient usage in resource-limited, embedded sensor network environments.
机译:WSN和SANET拓扑产生大量的异构数据,必须在动态变化的网络基础架构中传输。特别是在无线低功耗应用领域,通信任务的能量效率和优先级至关重要。几个研究领域处理了这个问题。它们优化各个硬件组件以及PHY,MAC或网络层内的协议。但对于拓扑中的优化媒体传输,数据管理和应用层上的任务调度也是必不可少的。这里,关键挑战是最小化数据量而不降低信息质量。数据聚合和数据融合领域的相关研究工作提供了有趣的技术处理技术。在本文中,我们讨论了常规方法进行数据聚合,包括适应性的通信过程。我们批判地分析了理论上的好处,并比较了测量的现实世界结果的概念优势。评估是分两步完成的。第一个基于典型的WSN / SANET应用程序的仿真方案。在第二步中,我们为相应的真实环境实施了一个示威者平台。测试床配置类似于模拟场景并提供可比数据。基于结果和各自的分析,我们提出了用于优化数据聚集技术的可行方法。我们澄清,这些改进对于资源限制,嵌入式传感器网络环境中有效使用至关重要。

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