RETRACTED: Cost-optimized data placement strategy for social network with security awareness in edge-cloud computing environment

With the development of the Internet of Things and the emergence of various computing paradigms, the use of social networks has become more diverse and data has exploded, making users more sensitive to the access delay of various new media when using social media. To meet the demand of massive data processing and users' access delay, edge-cloud computing-a new computing paradigm combining cloud computing and edge computing- starts to provide users with data storage and processing services. The popularity and convenience of smart devices, with hundreds of millions of users using social networking apps on their smart devices, has led to an explosion in the amount of data generated by the devices. However, in the edge-cloud environment, there is no trust mechanism between multilayer resource nodes. How to maintain the load balance of data storage to ensure the system performance becomes increasingly important. To solve the above problems, based on GP algorithm, a secure data placement model of edge-cloud computing is proposed under the constraints of ensuring user access delay and load balance. In this paper, real datasets are used for simulation experiments, and the experimental results show that the proposed algorithm has good performance.