Abstract: This research tackles resource management in OpenWhisk-based serverless applications for the Internet of Things (IoT) by introducing a novel approach to container retention optimization. We leverage the capabilities of AWS Forecast, specifically its DeepAR+ and Prophet algorithms, to dynamically forecast workload patterns. This real-time forecast empowers us to make adaptive adjustments to container retention durations. By optimizing retention times, we can effectively mitigate cold start latency, the primary reason behind sluggish response times in IoT serverless environments. Our approach outperforms conventional preloading and chaining techniques by significantly increasing resource utilization efficiency. Since OpenWhisk is an open-source platform, our methodology was able to achieve a cost reduction. By integrating it with Amazon Forecast's built-in algorithms, we surpassed traditional cache cold start strategies. These findings strongly support the viability of dynamic container retention optimization for IoT serverless deployments. Evaluations conducted on the OpenWhisk platform demonstrate substantial benefits. We observed a remarkable 67% reduction in cold start latency, translating to expedited response times and a demonstrably enhanced end-user application experience. These findings convincingly validate the efficacy of AWS Forecast in optimizing container retention for IoT serverless deployments by capitalizing on its deep learning (DeepAR+) and interpretable forecasting (Prophet) abilities. This research lays a solid foundation for future studies on optimizing container management across various DevOps practices and container orchestration platforms, contributing to the advancement of efficient and responsive serverless architectures.

Ganeshan Mahalingam and Rajesh Appusamy. “Forecast for Container Retention in IoT Serverless Applications on OpenWhisk”. International Journal of Advanced Computer Science and Applications (IJACSA) 15.7 (2024). http://dx.doi.org/10.14569/IJACSA.2024.01507119

@article{Mahalingam2024,
title = {Forecast for Container Retention in IoT Serverless Applications on OpenWhisk},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.01507119},
url = {http://dx.doi.org/10.14569/IJACSA.2024.01507119},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {7},
author = {Ganeshan Mahalingam and Rajesh Appusamy}
}