Abstract
With the development of IoT, edge computing has been attracting attention in recent years. In edge computing, simple data processing, such as aggregation and filtering, can be performed at network edges to reduce the amount of data communication and distribute the processing load. In edge computing applications, it is important to guarantee low latency, high reliability, and fault tolerance. We are working on the solution of this problem in the context of environmental sensing applications. In this paper, we outline our approach. In the proposed method, the aggregate value of each device is calculated approximately and the fault tolerance is also guaranteed approximately even when the input data is missing due to sensor device failure or communication failure. In addition, the proposed method reduces the delay by outputting the processing result when the error guarantee satisfies the user’s requirement.
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Acknowledgement
This study is based on results obtained from a project, JPNP16007, commissioned by the New Energy and Industrial Technology Development Organization (NEDO). In addition, this work was supported partly by KAKENHI (16H01722, 20K19804, and 21H03555).
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Takao, D., Sugiura, K., Ishikawa, Y. (2022). Approximate Fault-Tolerant Data Stream Aggregation for Edge Computing. In: Sachdeva, S., Watanobe, Y., Bhalla, S. (eds) Big-Data-Analytics in Astronomy, Science, and Engineering. BDA 2021. Lecture Notes in Computer Science(), vol 13167. Springer, Cham. https://doi.org/10.1007/978-3-030-96600-3_17
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DOI: https://doi.org/10.1007/978-3-030-96600-3_17
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