A Multicast Search Scheme Based on Bipartite Graph Matching Model

Abstract

This paper proposes an efficient multicast search scheme based on bipartite graph matching model, aiming at one of the most important problems in the multicast service, how can the wireless network track and locate the mobile uses in the idle state, under the tight bandwidth and delay constraints,. By quantifying the location uncertainty of mobile users with Shannon's entropy, the scheme adopts the LZ78 compression algorithm to design location update scheme and predict the location probability, in order to reduce the cost of location update. The multicast search system need to guarantee the maximum total probability that each user resides at the assigned paging area, for the purpose of an optimal performance on both expected paging delay and paging cost. Therefore, the bigraph-based multicast paging scheme (BMPS) firstly builds the bipartite graph model of multicast search problem, through converting the location probability into weight of the edge. BMPS decides the optimal allocation between the mobile users and location areas, which is mainly achieved by the maximum weight perfect matching in bipartite graph, while modifying the weights dynamically. Simulation results show that BMPS yields a low search delay as well as a low search cost, and reduces the impact of user collision.

Latent geometry of bipartite networks

“…Understanding the organizing principles determining the structure and evolution of real bipartite networks can lead to significant advances in many challenging problems including community detection [65][66][67][68][69][70][71][72], understanding signaling pathways in gene regulatory networks [73], multicast search [74], and construction of efficient recommender systems [75][76][77][78].…”