FlowGram: Resource Allocation for Network Flow Measurement in Clouds

Network measurement is essential for cloud tenants in their virtual network management. However, existing measurement systems exhibit suboptimal resource efficiency while accommodating an increasing number of tenants with limited switch resources. To address this issue, this paper proposes FlowGram, a measurement framework to provide flow frequency estimation services for cloud tenants. FlowGram provides a user-friendly interface for tenants and automatically adjusts the memory allocation to meet the tenants' demands. In the data plane, FlowGram employs sketches on programmable switches to perform the measurement. In the control plane, FlowGram utilizes a precise error model of sketches and an efficient memory allocation algorithm that ensures the measurement errors are within the specified error bounds. We prototype FlowGram on programmable switches and commodity servers and conduct comprehensive experiments. Experiment results demonstrate that FlowGram outperforms the state-of-the-art system, achieving a 14 % higher task satisfaction rate while utilizing the same amount of resources.