An Approach to Network Service Placement using Intelligent Search Strategies over Branch-and-Bound

Network Function Virtualization (NFV) has been a significant shift from traditional dedicated hardware devices towards reusable software modules running over lightweight virtualized environments. While it brings many promising opportunities, it introduces several unprecedented complexities that need further considerations. Efficient placement of services is essential for achieving NFV expectations. We propose a highly reliable solution for systematically placing network services, touching the optimal results while maintaining the scalability, making it suitable for online scenarios with strict time constraints. We organized our solution as a Branch and Bound search structure, which leverages Artificial Intelligence (AI) search strategies (Especially A-Star) to address the placement problem, following the popular objective of Service Acceptance (SA). Extensive empirical analysis has been carried out and the results confirm significant improvements.