Mobile Prediction Idea Based Clustering Algorithm and Related Mathematical Quantitative Description

Autor: Tie Jun Shao, De Sheng Cao, Jing Wu, Zhen Guo Chen
Rok vydání: 2014
Předmět:
Zdroj: Advanced Materials Research. 981:494-497
ISSN: 1662-8985
DOI: 10.4028/www.scientific.net/amr.981.494
Popis: Mobile prediction idea refers to predicting link expiration time with relative velocity and relative position between different nodes. In ad hoc networks, mobile prediction idea is adopted in MSWCA, and cluster stability is measured by link expiration time. MSWCA only considers on intra-cluster stability, and neglects inter-cluster stability. Aiming at the above problem, MPICA (Mobile Prediction Idea based Clustering Algorithm) was proposed. Firstly, involved concepts were given with mathematical quantitative description. Secondly, the realization process of MPICA was described. Lastly, the complexity of MPICA was analyzed. MPICA considers intra-cluster and inter-cluster stability at the same time, which is in favor of improving cluster stability and reducing cluster maintenance overheads.
Databáze: OpenAIRE