A-DDPG: Attention Mechanism-based Deep Reinforcement Learning for NFV

The efficacy of Network Function Virtualization (NFV) depends critically on (1) where the virtual network functions (VNFs) are placed and (2) how the traffic is routed. Unfortunately, these aspects are not easily optimized, especially under time-varying network states with different quality of service (QoS) requirements. Given the importance of...

Optimization problems in correlated networks

Background Solving the shortest path and min-cut problems are key in achieving high-performance and robust communication networks. Those problems have often been studied in deterministic and uncorrelated networks both in their original formulations as well as in several constrained variants. However, in real-world networks, link weights (e.g.,...

Shortest paths in networks with correlated link weights

Availability-based path selection and network vulnerability assessment

Constrained maximum flow in stochastic networks

Availability-based path selection