Title : 
Position Prediction Social-Relationship-Based on Multi-order Markov Model
         
        
            Author : 
Yue Zou;Sanfeng Zhang
         
        
            Author_Institution : 
Coll. of Software Eng., Southeast Univ., Nanjing, China
         
        
        
        
        
            Abstract : 
Opportunistic network mobile user-nodes location prediction can help to collect the data, improve the dynamic network and help to decrease the problems which include the delay, low success rate, high storage space energy consume and so on, which are the results of the blindness in the process of delivery. In this paper, a mobile node location prediction algorithm base on the Multi-Order Markov prediction model as the initial forecast, and then use social-relationship which is closely linked to the node to optimize the algorithm. Experimental results show that the proposed algorithm is better than the single Multi-Order Markov model.
         
        
            Keywords : 
"Markov processes","Prediction algorithms","Routing","Predictive models","Hidden Markov models","Whales","Delays"
         
        
        
            Conference_Titel : 
Advanced Cloud and Big Data, 2015 Third International Conference on
         
        
            Print_ISBN : 
978-1-4673-8537-4
         
        
        
            DOI : 
10.1109/CBD.2015.16