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Today, modern healthcare systems rely on advanced computational technologies, including cloud-based systems, to gather and examine personal health data on a large scale. The use of advanced cloud services technologies, such as software as a service, application as a service, is challenging for end-users of cloud systems to protect sensitive data in their health applications. According to the importance of publishing data in the cloud, the information should be recorded and handled somehow so that any individuals' identity remains hidden. Therefore, one of the critical privacy challenges is protecting the quality of published data and privacy-preserving on the healthcare cloud simultaneously. The K-anonymity technology is one of the prevalent methods used for privacy-preserving. In this article, we suggest a novel approach based on the clustering process using the K-means++ method to achieve an optimal k-anonymity algorithm. Also, we use the normal distribution function to delete data that is less frequent, which can be improved the quality of anonymized data. Extensive experiments show the proposed method has been able to reduce information loss 1.5 times and execution time 3.5 times compared to AKA and GCCG algorithms. Also, it is highly scalable than others.

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Peer-to-peer (P2P) network is a distributed network in which nodes with similar capabilities exchange information with each other. Due to the nature of the P2P network distribution, numerous network message transformation is required to exchange the data between nodes over the network, which may increase access latency. Because of the high amount of the stored data in the P2P networks, the replication of data is very important. A large amount of data is handled using data replication to increase data access, reduce access latency, and increase data availability. This issue has an important role in the P2P networks, but there is no complete and systematic research in this field. Therefore, this paper aims to provide a comprehensive study of data replication mechanisms in the P2P networks. The 1027 papers have been identified and have been reduced to 213 main studies using the paper selection process. Moreover, in this paper, the major advances are reviewed in four main groups (structured, unstructured, super-peer, and hybrid networks), and the new challenges are also highlighted. Moreover, the open issues and guidelines for future studies are presented.

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