Document Type : Research Article
Abstract
Data services provided by many public clouds - files, queues, tables - high performance,
streaming friendly cardio services not yet included. Considering the data constantly coming in from the 1.4
million smart meters in homes, there is an urgent need to constantly analyze it to identify the maximum
power consumption that is coming in the smart power grid and to inform the utility to respond by
increasing or decreasing the additional power sources. Load. Measures to reduce demand. The IoT
Workflow Framework, which supports this data model variation, including streaming data, structured
archives and files, currently lacks the ability to perform reliable and measurable work on elastic computing
platforms such as the cloud. In this paper, we address this by proposing a scientific workflow framework
that supports the various data models required for these emerging scientific applications and assesses its
performance and reliability on desktop and cloud platforms.
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