Modeling of Online Service Availability Perceived by Web Users

While the Internet and the World-Wide-Web (WWW)-based online services expand at an unprecedented pace, the Web users are still experiencing a high level of unavailability. Paralleling the effort of identifying the failure-recovery behaviors of the underlying supporting infrastructure, attention has also been paid to Web users’ behaviors. However, a link between the two research directions seems to be missing. In this paper, we propose to use Markov regenerative process (MRGP) models to study the availability of Internet-based services perceived by a Web user, which capture the interactions between the service facility and the user. The use of sophisticated MRGP models rather than traditional continuous-time Markov chain (CTMC) models is due to the fact that the model of Web user behavior involves non-exponential distributions. The necessity of MRGP modeling is also evidenced by the comparisons with the corresponding CTMC models, which show that the CTMC models tend to overestimate user-perceived service unavailabilities by 26% to 125%. We study two different online service scenarios: (1) single-user-singlehost (Model-1) and (2) single-user-multiple-host (Model-2). Results from the models provide useful implications to both service providers and online end-users. It is found that user-perceived service unavailability depends not only on the infrastructure’s failure-recovery characteristics but also, more importantly, on the user’s behavior. Also, for a service provider, to improve users’ satisfaction, inventing a fast recovery mechanism is more effective than striving for a more reliable platform given the platform availability is the same.