Ad Hoc Network Management Based On Quorum System

In recent years, with the development of computer network deeply into people's daily lives and works, people have reached a dependence on it more and more. Mobile ad hoc wireless networks also called MANET, roled as an important complement of traditional networks, have atracted much attention of researches in recent years. It has acted a insubstitute part in many applications. The mobile Ad Hoc wireless networks, as an important complement to traditional networks, attracting the attention of a large number of researchers, both in the military or commercial areas are playing an irreplaceable role. But the Ad Hoc network is a non-centered, multi-hop, self-organization of the equation communications network, network resource management to become one of the difficulties.The main work of this paper is to provide a improved adaptive on-demand-weighted (AOW) algorithm ,focus on stability and load balancing and to design a simulation platform.In this paper, we briefly introduct the mobile Ad Hoc networks, basic concepts, characteristics, key technologies and applications, and analysis of the current status of research at home and abroad. We expound main cluster algorithm for Ad Hoc Networks and its design requirements and measurement standards, and a number of classic algorithms. The clustering algorithms were compared. Then introduces the concept of Quorum systems, analyze its advantanges in network management. Then to find out the suitability of a Quorum systems constructed clustering algorithm. Finally, AOW and its improved algorithm QAOW to simulate the operation and comparative analysis, focusing on study of the two kinds of comparison of the distribution of weight. The results show that the improved algorithm in the number of cluster heads, as well as the survival time performance compared with the AOW greater improvement.The current for several Ad Hoc network simulation software is not integrated clustering algorithm. We use C + + language prepared by a simple simulation environment for the simulation experiments, the QAOW performance of the algorithm is analyzed and evaluated.