An Improved Search Algorithm Based on Path Compression for Complex Network

With the rapid development of science technology and explosively increasing of network´s complication, complex network as an emerging research hotspot has attracted more and more scientists´ attention. Meanwhile, search strategy as a main research method in complex network plays a more and more important role on study of complex network, and it has great practical significance and research value. So many classical search algorithms have been proposed according to network´s specialty, such as breadth-first search (BFS), random walk (RW), and high degree seeking (HDS). Unfortunately, a flawless solution for all kinds of models in complex network has not been presented so far due to the above algorithms are only suitable for some special circumstances. For improving the search efficiency, this paper appears an improved strategy which has a hybrid merit combining both high efficiency and low consumption. This strategy augments a compressed process to save useful path´s information, so we can use the stored data in the search process to effectively reduce search step and query flow. In the simulation, the proposed algorithm will be compared with HDS in the models of complex network which have diverse type or different size. The result of simulation was used to illustrate the efficient performance of this strategy and demonstrate that the proposed search algorithm can produce a better fruit than others.