KnowMe: A Module to Improve the Efficiency of Resource Allocation in Data Center Networks

In recent years, a new paradigm called network-application integration (NAI) has been introduced which enables applications to express their requirements to the network. By applying NAI in data center networks (DCNs), the DCN controller can better serve applications. We refer to this as data center network-application integration (DC-NAI). However, a critical issue in DC-NAI is how applications use the assigned resources. Selfish applications may under-utilize or over-utilize the assigned resources which can negatively impact the existing applications. To overcome this challenge, in this paper, we propose a DCN controller add-on module called KnowMe that takes the applications’ behavior into consideration and improves the efficiency of the resource allocation. The KnowMe module is composed of two components: the resource utilization prediction and the resource assignment learning. The first component predicts the future applications’ resource usage by looking at their previous resource usage behavior. The second component makes decisions about the applications’ resource requests considering the current network status. Simulation results confirm the efficiency of our proposed module and its ability to mitigate the selfish behavior of applications. The results show that under network resource limitation, the selfish applications in KnowMe-enabled DCNs experience 40% higher resource request rejection rate comparing to the well-behaved applications.