The Application of Multi-Objective Optimization in Software Architectural Decision-Making for Cloud-Native Services
Keywords:
Multi-objective optimization, cloud-native services, software architecture, decision making, trade-offs, Pareto optimizationAbstract
Cloud-native services demand software architectures that balance competing objectives, such as performance, cost, and scalability. Multi-objective optimization (MOO) provides a systematic approach to addressing these trade-offs by leveraging algorithms that identify optimal solutions. This paper explores the role of MOO in software architectural decision making for cloud-native services, focusing on methodologies, practical implementations, and challenges. Future trends in applying MOO to evolving cloud technologies are also discussed.
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