Delay optimization scheduling algorithm in cognitive radio networks
Delay optimization scheduling algorithm in cognitive radio networks

In cognitive radio networks, delay scheduling optimization has attracted an increasing attention in recent years. Numerous researches have been performed on it with different scenarios. However, these approaches have either high computational complexity or relatively poor performance. Delay scheduling is a constraint optimization problem with non-deterministic polynomial (NP) hard feathers. In this paper, we proposed an immune algorithm-based suboptimal method to solve the problem. Suitable immune operators have been designed such as encoding, clone, mutation and selection. The simulation results show that the proposed algorithm yields near-optimal performance and operates with much lower computational complexity.
In cognitive radio networks, delay scheduling optimization has attracted an increasing attention in recent years. Numerous researches have been performed on it with different scenarios. However, these approaches have either high computational complexity or relatively poor performance. Delay scheduling is a constraint optimization problem with non-deterministic polynomial (NP) hard feathers. In this paper, we proposed an immune algorithm-based suboptimal method to solve the problem. Suitable immune operators have been designed such as encoding, clone, mutation and selection. The simulation results show that the proposed algorithm yields near-optimal performance and operates with much lower computational complexity.