To incorporate other practical constraints like content delivery latency or energy efficiency in the optimization problem, the proposed approach can be extended by introducing additional constraints or objectives in the optimization framework. Here are some ways to adapt the approach:
Latency Constraints: Include constraints on the maximum allowable latency for content delivery, ensuring that recommended content is accessible within specified time limits. This can be achieved by incorporating latency-aware caching and recommendation strategies that prioritize content with lower delivery times.
Energy Efficiency Considerations: Integrate energy efficiency metrics into the optimization problem by optimizing caching and recommendation decisions to minimize energy consumption. This can involve selecting content that requires lower energy for retrieval or recommending content that reduces overall network energy usage.
Multi-Objective Optimization: Formulate the optimization problem as a multi-objective optimization task, considering trade-offs between cache hit rates, latency, energy efficiency, and other constraints. Utilize multi-objective optimization algorithms to find Pareto-optimal solutions that balance these competing objectives effectively.