Modeling the Scalability of Real-Time Online Interactive Applications on Clouds

We address the scalability of Real-Time Online Interactive Applications (ROIA) on Clouds. Popular examples of ROIA include, e.g., multi-player online computer games, simulation-based e-learning, and training in real-time virtual environments. Cloud computing allows to combine ROIA's high demands on QoE (Quality of Experience) with the requirement of efficient and economic utilization of computation and network resources. We propose a generic scalability model for ROIA on Clouds that monitors the application performance at runtime and predicts the benefit-cost ratio of load-balancing decisions: by weighting the potential benefits of particular load-balancing actions against their time and resources overhead, our model recommends whether and how often to redistribute workload or add/remove Cloud resources when the number of users changes. We describe how the scalability is modeled w.r.t. two kinds of resources - computation (CPU) and communication (network) - and how we combine these models together. We experimentally evaluate the quality of our combined model using a challenging multi-player shooter game as a use case.