In the current communication technology, optical technology has been applied to the network to obtain optical network technology. Among them, optical network technology is optical wavelength division multiplexing (WDM), which can play a larger transmission capacity under lower energy
consumption. Further breakthroughs in intelligent optical networks require improvements in routing issues. In this study, firstly, the optical network architecture is analyzed, including wavelength division multiplexing optical network and elastic optical network. Then, the routing problem
in optical networks is analyzed, and the main factors affecting the routing problem are extracted. On the basis of studying the energy consumption characteristics of data centers and WDM optical networks, and considering the characteristics of cloud service configuration, evolutionary game
theory and optical bypass theory are introduced to obtain an intelligent routing algorithm for cloud computing based on optical networks, and energy consumption tests are carried out on data transmission and processing. In order to reduce the overall energy consumption, the use of IP routers
is reduced, and the idle data servers are shut down. Then, it is found that the total energy consumption increases slowly at different times. The energy consumption of evolutionary game theory is compared. Compared with non-evolutionary game theory, the optimized intelligent routing algorithm
makes the energy consumption more stable, while reducing the use of servers can further reduce the good expenditure. The proposed algorithm is oriented to optical network, which solves the problem of low overall utilization of network resources and improves the service quality of cloud services.
A Study of Taxi Service Mode Choice Based on Evolutionary Game Theory
