Network Coding Link Optimization Problems Based On Genetic And Particle Swarm Algorithm

The network is more and more important in people’s lives. The requirements of the network performance、transmission rate、security are getting higher and higher. In order to improve the transmission rate and throughput capacity of the network, the concept of the network coding is proposed. The main idea of the network coding is a code in the network can not only transmit the input information, but also the input information is encoded and then transmitted. So that the network can reach the theoretical maximum multicast rate and improve the network performance with network coding. Otherwise the network coding plays a very important role in enhancing network robustness and safety. Not all the nodes need network coding in the network. For example the nodes which have only one input do not need network coding. And the network coding needs the nodes to finish the encoding and decoding operations, and it increases the overhead of the network. So the significance of the network coding link optimization which is to compute the nodes which must need the network coding in the network is very important to reduce the computational complexity of the network and save the network’s costs.The paper analyses the present situation of the network coding link optimization. We introduce the present and development process of the network coding link optimization. We research the algorithms of solving the network coding optimization. We study the main idea of the algorithms and the weak points. Based on the analysis, we improve the algorithm. And these lay a foundation for designing a new algorithm.The genetic algorithm and the particle swarm algorithm are separately applied to solve the combinatorial optimization problems. We do the in-depth research about the two algorithms, and combine the genetic algorithm and DPSO algorithm based on the discrete. We propose the genetic particle swarm optimization algorithm (GDPSO). GDPSO is applied to solve the network coding link optimization. The simulation results of the GDPSO verify the feasibility of the algorithm. The simulation results verify the convergence rate is faster of GDPSO than GA, and GDPSO can search the global optimal solution than GA.