Ant Colony Optimization (ACO) is a popular research field these years. Ants choose paths where pheromone
concentration is higher and modify the environment they visited. However, in the context of multi-service in multi-level
and multi-domain optical network, the capacity of inter-domain links is limited. Congestion may be occurred at
inter-domain links. In this paper, ant colony optimization algorithm based on load balancing is proposed. Ants follow
paths not just depend on pheromone alone, we also take available resources on the link as a factor too. Simulations show
the proposed method could reduce the traffic blocking probability, and realize load balancing within the network.
The process of computing routes that network traffic must follow throughout network has become much more complex
in recent years. PCE (Path Computational Element) technology is emerging and gaining importance under the
circumstances. In this paper, PCE architecture is outlined, and the impact of PCEs allocation decisions is discussed
briefly. To track the problem of locating PCEs, an integer linear programming (ILP) model is presented to find the
optimal PCEs allocation solution in multi-domain optical networks. The objective is to minimize average amount of time
for sending a message to all nodes in the topology, i.e. message flooding cost. Then, two heuristics, LSPLP and TSPLP,
are developed based on this model. Numerical results show that compared with traditional allocation strategies, the
proposed algorithms can reduce the message flooding cost efficiently.