A novel model to improve network performance. Issue 2 (3rd April 2018)

• Record Type: Journal Article
• Authors: Li, Guodong; Liu, Qian; Bai, Shuo
• Is Part Of: International journal of computers and applications. Volume 40:Issue 2(2018)
• Page Start: 82
• Page End: 87
• Publication Date: 2018-04-03
• Subjects: Hidden Markov model -- inner model -- time delay -- prediction; Computers -- Periodicals; Computer software -- Periodicals; Computer networks -- Periodicals; Multimedia systems -- Periodicals; Internet -- Periodicals; World Wide Web -- Periodicals; Minicomputers -- Periodicals; Microcomputers -- Periodicals; 004.05
• DOI: 10.1080/1206212X.2017.1395107
• Languages: English
• ISSNs: 1206-212X

Abstract

Abstract: With the growing use of the Internet, as a wildly used tool, Internet has faced many resistances as an unreliable transmission medium. The core problem is time-varying delay in information transmission process. To solve this problem, we use the hidden Markov model (HMM) as a method of analysis first. We propose that the network model and hidden states are defined as the network's situations. To train the HMM quickly, we use k-means clustering to obtain a more efficient starting value for determining hidden states, and we use Bayesian information criterion values to measure the model's performance. Following this, an inner model is put forward based on the latent Dirichlet allocation. The inner model can be used to describe the essential associations among the network's situations and delay transformation. Generally, we use Network Simulator (ns-2) to run the simulation, with changes made to the TCP based on the HMM and the inner model. By more accurately predicting the performance of network situation factors, such as link utilization, the time delay and network noise can be reduced.