A Stable Cloud Storage Algorithm for Online Interaction Effect Data based on HarmonyOS

At present, the skyrocketing amount of effective and redundant information makes the demand for storage more and more high, which provides an opportunity for the recent development of cloud storage and makes it one of the fastest accepted forms of cloud services. Under this background, this paper proposes a stable cloud storage algorithm for online interaction effect data based on the HarmonyOS. The designed model firstly optimizes the traditional Chord algorithm by introducing the genetic algorithm into the processing of data. The designed strategy allows the system to choose a relatively good path in each path selection, the system can choose a relatively good path. Then, the HarmonyOS is selected as the multi-core scenario and the online interaction effect data is selected as the sample application. Through the test, this study compares the performance of the original Scalable Chord routing protocol and the improved routing protocol in terms of resource location by using PeerSim. It can be seen that the designed model is robust.