IMPROVED SERVERLESS EDGE BASED DATA ANALYTICS FRAMEWORK THROUGH AI
Keywords:
Edge Based Data Analytics, AI, ServerlessAbstract
This paper proposes a serverless framework for building and running AI applications on the edge. For the purpose of illustrating the difficulties associated with developing and running AI applications in edge cloud environments, we conduct an analysis of edge AI use cases. By incorporating ideas from artificial intelligence lifecycle management into the already existing serverless approach, we make it possible to easily construct AI workflow functions at the edge. We use a method called deviceless computing, which allows developers fine-grained control over resource restrictions while treating edge resources transparently like cluster resources. Furthermore, we showcase the present status of our prototype and highlight the shortcomings of the existing serverless function schedulers.
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Copyright (c) 2023 Rajashekhar Reddy Kethireddy, Nithin Reddy Desani (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
