DECOMPOSITION OF INTEGRATED HIGH-DENSITY IoT DATA FLOW
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Abstract
Topicality. The concept of fog computing made it possible to transfer part of the data processing and storage tasks from the cloud to fog nodes to reduce latency. But in batch processing of integrated data streams from IoT sensors, it is sometimes necessary to distribute the tasks of the batch between the fog and cloud layers. For this, it is necessary to decompose the formed package. But the existing methods of decomposition do not meet the requirements for efficiency in high-density IoT systems. The subject of study in the article are methods of decomposition of integrated data streams. The purpose of the article is to develop a method of decomposition of an integrated data stream in a dense high-density Internet of Things fog environment. This will reduce the processing time of operational transactions. The following results were obtained. The concept of decomposition of integrated information flows in the foggy layer was implemented to transition from the batch mode to the flow mode of task processing. Within the framework of the concept, a method of selecting elementary task flows from an integrated flow is proposed. An algorithm for decomposition of the integrated flow of tasks is proposed. Conclusion. A comparison of the proposed method of processing information flows in the foggy environment of high-density IoT with the existing approach is carried out. The results of the comparison showed that the proposed method is more suitable for deployment in conditions of limited network and computing resources. It is advisable to use it on nodes of fog computing systems with a high density of IoT sensors.
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