Grid computing has been widely adopted for intensive high performance computing. Since grid resources are distributed over complex large-scale infrastructures, understanding grid site data traffic behaviour is important for efficient resource utilisation, performance optimisation, and the design of future grid sites as well as traffic-aware grid applications. In this paper, we study and analyse the traffic generated at a grid site in the Large Hadron Collider (LHC) Computing Grid (LCG). We find that most of the generated traffic is TCP-based and that a small set of grid applications generate significant amounts of the data. Upon analysing the different traffic metrics, we also find that the traffic exhibits long-range dependence and self-similarity. We also investigate packet-level metrics such as throughput, packet rate, round trip time (RTT) and packet loss. Our study establishes that these metrics can be well represented by Gaussian mixture models. The findings we present in this paper will enable accurate grid site traffic monitoring and potentially on-the-fly traffic modelling and prediction. It will also lead to a better understanding of grid site’s traffic behaviour and contribute to more efficient grid site planning, traffic management, data transmission protocol optimisation, and data-aware grid application design.Grid computing has been widely adopted for intensive high performance computing. Since grid resources are distributed over complex large-scale infrastructures, understanding grid site data traffic behaviour is important for efficient resource utilisation, performance optimisation, and the design of future grid sites as well as traffic-aware grid applications. In this paper, we study and analyse the traffic generated at a grid site in the Large Hadron Collider (LHC) Computing Grid (LCG). We find that most of the generated traffic is TCP-based and that a small set of grid applications generate significant amounts of the data. Upon analysing the different traffic metrics, we also find that the traffic exhibits long-range dependence and self-similarity. We also investigate packet-level metrics such as throughput, packet rate, round trip time (RTT) and packet loss. Our study establishes that these metrics can be well represented by Gaussian mixture models. The findings we present in this paper will enable accurate grid site traffic monitoring and potentially on-the-fly traffic modelling and prediction. It will also lead to a better understanding of grid site’s traffic behaviour and contribute to more efficient grid site planning, traffic management, data transmission protocol optimisation, and data-aware grid application design.