In order to speed up image processing in visual servoing, the distributed computational power across networks and appropriate data transmission mechanisms are of particular interest. In this paper, a high sampling rate of visual feedback is achieved by distributed computation on a cloud image processing platform. For target tracking with a networked visual servo control system, a switching control law considering the varying feedback delay caused by image processing and data transmission is applied to improve the control performance. A sending rate scheduling strategy aiming at saving the network load is proposed based on the tracking error. Experiments on a 7 degree-of-freedom (DoF) manipulator are carried out to validate the proposed approach. The proposed approach shows a similar control performance as a system without sending rate scheduling, however, beneficially with largely reduced network load.