TARGETED QUANTUM SEARCH: REDUCES THE TIME AND COST FOR SEARCHING FOR OBJECTS IN MULTIPLE-SERVER PEER-TO-PEER NETWORKS

摘要

In a number of Internet applications, we need to search for objects to download them. This includes peer-to-peer (P2P) file sharing, grid computing and content distribution networks. Here the single object will be searched for in multiple servers. There are many searching algorithms in existence today for this purpose based on the concept of classical physics and classical algorithms. The principles of quantum mechanics can be used to build and analyze a quantum computer and its algorithms. Quantum searching is such an algorithm. In this paper we are proposing a search method based on the quantum physics and quantum algorithms. Our method, the targeted quantum search is found to be more cost effective than any other classical searching algorithms like linear and two-way linear, simulated annealing, including broadcast based searching. Our targeted quantum search method is analyzed and simulated to show the best results.