This paper is concerned with the implementation of EKF-SLAM (Extended Kalman Filter- Simultaneous Localization and Mapping) algorithm using a cloud computing architecture based on ROS (Robot Operating System). The localization and mapping is essential step to navigate a mobile robot in unknown environment. The implemented EKF-SLAM has used a landmark that sensed using IR Emitter sensor provided by the Kinect camera to update a map of the environment and simultaneously estimate the robot’s position and orientation within the map. The implementation was done using three parts. The first one was the TurleBot Mobile robot with the Kinect camera, which was simulated in Gazebo environment. The second part was the EKF-SLAM running under the MATLAB to generate the Map and Location data. The third part was the ROS Master node, which runs on the cloud to enable part one and two to communicate using topics. The scan data from Kinect camera and the location data from the odometer is transferred from the first part to the second part through ROS Master node after impaired with zero mean Gaussian noise . Then the second part performs EKF-SLAM and transmit the corrections to the first part through the ROS Master node as well.