One of the most expecting IoT services is using multiple autonomous mobile robots. Drone and robots on nurse care whose services are expected to become widespread. For these robots, it is essential to create a map of the surroundings using Simultaneous Localization and Mapping (SLAM) technology. SLAM has a high processing load. Therefore, the high-performance edge servers will be placed close to the robot to support the computation. SLAM implementations typically consist of multiple software processes such as distance estimation and mapping. From this, it is considered that using a many-core processor for the edge server that can efficiently support SLAM for multiple robots. However, the effectiveness of using many-core processors for the IoT edge servers is not clear. Therefore, this study investigates the use of a many-core processor when SLAM is the target IoT application. To build a general-purpose mechanism for utilizing a many-core processor, we need a measurement system inside the ROS (Robot Operating System) which is the base middleware for SLAM, in order to measure the processing activity where the ROS components are asynchronously executed. Therefore, we developed a mechanism that makes it possible to accurately measure the execution of the components on ROS, and overcome the problem to allocate the many-core CPU for each ROS component execution properly. As a result, furthermore by considering the cache and properly allocating the ROS node to the processor, the execution performance was improved by up to 7.5%.