Intelligent Serverless Cloud Architecture for Software Development Optimization: Deep Learning–Driven WPM and TOPSIS Fusion with Hybrid Fuzzy and Particle Swarm Algorithms

Giorgos Nikolaos Christodoulou

doi:10.15662/IJRAI.2021.0405003

Authors

Giorgos Nikolaos Christodoulou Data Scientist, Greece Author

DOI:

https://doi.org/10.15662/IJRAI.2021.0405003

Keywords:

Serverless Cloud Computing, Software Development Optimization, Deep Learning, Weighted Product Method (WPM), TOPSIS, Particle Swarm Optimization (PSO), Hybrid Fuzzy Framework, AI-Driven Architecture, DevOps Automation, Intelligent Decision-Making, Cloud-Native Systems

Abstract

The evolution of cloud computing and serverless technologies has transformed software development, demanding intelligent frameworks that balance performance, scalability, and automation. This research proposes an Intelligent Serverless Cloud Architecture that integrates Deep Learning, the Weighted Product Method (WPM), and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) within a Hybrid Fuzzy and Particle Swarm Optimization (PSO) framework. The goal is to optimize software development processes through adaptive decision-making, automated resource allocation, and intelligent performance tuning.

The hybrid fuzzy logic layer enhances uncertainty handling in multi-criteria decision-making, enabling accurate evaluation of software design parameters under variable workloads. WPM and TOPSIS jointly rank alternative development strategies, while PSO algorithms refine optimization based on real-time learning feedback from cloud-deployed models. The deep learning module continuously improves the accuracy of performance predictions and anomaly detection, supporting self-adaptive serverless functions in dynamic cloud environments.

Experimental simulations conducted in a cloud-native environment demonstrate improved deployment efficiency, scalability, and cost-performance ratios compared to traditional DevOps models. This study contributes to advancing AI-driven software engineering by providing a unified, serverless optimization framework that fuses machine intelligence, fuzzy reasoning, and swarm-based decision analytics for next-generation software development automation.

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