Cold Start: Cost- and Latency-Optimized Serverless Orchestration via Multi-Modal Prediction and Confidence-Based Warming

Q: What does this research mean for the field?

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Dr. Alpana Adsul; Abhishek Doke; Nikhil Dhamdhere; Joanna Dharwadkar; Geetanjali Bejjalwar

doi:10.56975/ijcrt.v14i2.300742

January 1, 2026INTERNATIONAL JOURNAL OF CREATIVE RESEARCH THOUGHTSOpen Access

Cold Start: Cost- and Latency-Optimized Serverless Orchestration via Multi-Modal Prediction and Confidence-Based Warming

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Key Points

This research aims to optimize serverless orchestration by balancing cost and latency through innovative predictive techniques.
Developed multi-modal prediction algorithms to enhance serverless orchestration.
Implemented confidence-based warming strategies to reduce latency.
Analyzed cost implications of orchestrating serverless processes under various conditions.
Achieved significant reductions in latency compared to traditional methods.
Demonstrated cost savings while maintaining performance efficiency.
Validated effectiveness through multiple testing scenarios.

Implication

Research reveals cost and latency benefits of serverless orchestration using multi-modal prediction, highlighting efficiency improvements.

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Cite This Study

Adsul et al. (2026) studied this question.

synapsesocial.com/papers/69a2878e0a974eb0d3c034b5 https://doi.org/10.56975/ijcrt.v14i2.300742

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Cold Start: Cost- and Latency-Optimized Serverless Orchestration via Multi-Modal Prediction and Confidence-Based Warming

Key Points

Implication

Abstract

Discussion

Cite This Study

Cold Start: Cost- and Latency-Optimized Serverless Orchestration via Multi-Modal Prediction and Confidence-Based Warming

Key Points

Implication

Abstract

Discussion

Cite This Study

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