An Improved Evolutionary Algorithm for Effective Optimized Network Design Using Tabu Search

Network nodes to estimate and characterize the impact of traffic engineering and load balancing over centralized and decentralized networks. This considers the network maximum utilization with load balancing over different nodes and links. In order to improve the network utilization and performance, the source node analyzes the paths and its Tabu search flow splitting process. To overcome traffic allocation problem the system performs every transmissions analysis and experiment over each link. Each link must be estimated and relayed with that set of conditions and rules. In proposed system used in efficiently for evolutionary algorithm using tabu search. It presented methods for each network node to probabilistically characterize the local impact of a dynamic traffic allocation and for data sources to incorporate this information into the routing algorithm using a different protocol which is CA-FSP (cost aware- flow splitting protocol).