Proactive planning of bandwidth resource using simulation-based what-if predictions for Web services in the cloud

Resource planning is becoming an increasingly important and timely problem for cloud users. As more Web services are moved to the cloud, minimizing network usage is often a key driver of cost control. Most existing approaches focus on resources such as CPU, memory, and disk I/O. In particular, CPU receives the most attention from researchers, but the bandwidth is somehow neglected. It is challenging to predict the network throughput of modern Web services, due to the factors of diverse and complex response, evolving Web services, and complex network transportation. In this paper, we propose a methodology of what-if analysis, named Log2Sim, to plan the bandwidth resource of Web services. Log2Sim uses a lightweight workload model to describe user behavior, an automated mining approach to obtain characteristics of workloads and responses from massive Web logs, and traffic-aware simulations to predict the impact on the bandwidth consumption and the response time in changing contexts. We use a real-life Web system and a classic benchmark to evaluate Log2Sim in multiple scenarios. The evaluation result shows that Log2Sim has good performance in the prediction of bandwidth consumption. The average relative error is 2% for the benchmark and 8% for the real-life system. As for the response time, Log2Sim cannot produce accurate predictions for every single service request, but the simulation results always show similar trends on average response time with the increase of workloads in different changing contexts. It can provide sufficient information for the system administrator in proactive bandwidth planning.