Towards a workload model for online social applications: ICPE 2013 work-in-progress paper

Popular online social applications hosted by social platforms serve, each, millions of interconnected users. Understanding the workloads of these applications is key in improving the management of their performance and costs. In this work, we analyse traces gathered over a period of thirty-one months for hundreds of Facebook applications. We characterize the popularity of applications, which describes how applications attract users, and the evolution pattern, which describes how the number of users changes over the lifetime of an application. We further model both application popularity and evolution, and validate our model statistically, by fitting five probability distributions to empirical data for each of the model variables. Among the results, we find that most applications reach their maximum number of users within a third of their lifetime, and that the lognormal distribution provides the best fit for the popularity distribution. © 2013 ACM