Chunyan Hou

Short-Term User Activity Prediction with Massive Mobile Broadband Data

With the increasing popularity of mobile Internet, it can bring great business value for Telecommunication (Telco) operators to provide users with better services in a timely manner. Understanding the change of mobile users activity can be a great help for operators to increase user experience and avoid the user churn. In this paper, we predict short-term user activity with massive Mobile Broadband (MBB) data. We conduct experiments with a large scale and real-world dataset of Telco operators, which includes MBB data of more than three million users. The experimental results show that gradient boosting decision tree is the effective model for the prediction. In addition, we show that the user activity is highly correlated with individual features. Features, which are associated with personal daily habits, tend to make people active the next day. In contract, features, which happen for specific purpose and are less related to the individual habits, can make people inactive the next day.

Reliability Analysis for Software Cluster Systems Based on Proportional Hazard Model

With the universal application of software cluster systems, their reliability is drawing more and more attention from academia to industry. A cluster system is a kind of software load-sharing system (LSS) whose reliability is significantly dependent on system software. Therefore, traditional reliability analysis methods for hardware LSSs are not applicable for cluster systems. In this paper, we develop a reliability analysis model for redundant cluster systems consisting of initial servers and cold standby servers used to replace failed ones. System reliability process is modeled with a state-based non-homogeneous Markov process (NHMH), where each state corresponds to a non-homogeneous Poisson processe (NHPP). NHPP arrival rate is expressed using Coxs proportional hazard model (PHM) in terms of cumulative and instantaneous workload of system software. In addition to redundant cluster systems without repair, the model also can be extended to analyze those with restart. The analysis results are meaningful to support cluster management and design decisions. Finally, the evaluation experiments show the potential of our model.

Reliability analysis of web server cluster systems based on proportional hazards model

With the universal application of web server clusters (WSCs), their reliability is drawing more and more attention from academia to industry. Many accelerated life testing (ALT) models have been proposed for hardware load-sharing systems (LSSs), which are not suitable for WSCs whose reliability is significantly dependent on system software. In contrast to hardware which runs all the time after a system launches, software performs only when it is called. This paper presents an approach for WSC reliability and degradation process analysis, which is modeled as a non-homogeneous Markov process (NHMH) composed of several non-homogeneous Poisson processes (NHPPs). The arrival rate of each NHPP corresponds to system software failure rate which is expressed using Coxs proportional hazards model (PHM) in terms of the cumulative and instantaneous load ofsoftware. The first refers to software cumulative execution time, and the latter denotes the rate at which user requests arrive. The result solved from NHMH is a time-varying reliability and degradation process over WSC lifetime. Finally, the evaluation experiment shows the potential of the approach.

An Enhanced TCP for Optimizing Channel Utilization in Dynamic Spectrum Access Networks

Dynamic Spectrum Access DSA network grows rapidly in recent years. It is proposed to solve the problem of reasonable utilization of wireless spectrum resources. DSA is a new spectrum sharing paradigm which takes advantage of spectrum holes to ease the spectrum shortage problem and improve the spectrum utilization. However, due to the frequent spectrum switch, the performance of TCP will degrade greatly in the DSA network, and thus the channel is unutilized. To tackle with this problem and improve high throughput performance, this paper proposes a protocol called TCP WSP based on the assumption that there will be a Wide Stationary Process WSP between two spectrum switches. Then the authors propose a mechanism to predict the spectrum switch and adjust the sending rate of TCP based on the prediction to optimize channel utilization in DSA networks. They implement our mechanism on NS2 simulator, and the results show that their mechanism can achieve high throughput performance.