algorithm based on the cloud computing platform, the parallel computing capacity of a high-performance clustering system of cloud computing is used for solving the problem that mass data need to be processed in clustering, and therefore a relation of the data can be rapidly and efficiently dug ...
Cloud computing is attached to the network, and through distributed computing and storage, it can realize efficient computing of big data. Figure 1 shows the development process of cloud computing. As a result, it would be of significant real-world implications to explore big data clustering ...
There are many different clustering algorithms as there are multiple ways to define a cluster. Different approaches will work well for different types of models depending on the size of the input data, the dimensionality of the data, the rigidity of the categories and the number of clusters with...
Shekhar, S., Evans, M.R., Gunturi, V., Yang, K.: Spatial big-data challenges intersecting mobility and cloud computing. In: ACM international workshop on data engineering for wireless and mobile access, pp. 1–6 (2012) Sibson, R.: Slink: an optimally efficient algorithm for the single...
In the era of “big data” huge data sets usually cannot be stored on a single server any longer. Cloud storage (where data are stored in a cloud infrastructure) offers the advantage of flexibly adapting the amount of used storage based on the growing or shrinking storage demands of the da...
The clustering of data can be done based on various models [58] that differ by their organization and the kind of relationship between them, as shown in Fig. 3.20. All the clustering algorithms focus on the 4Vs (volume, variety, velocity, value) of big data characteristics. The selection ...
Ahn H, Chang T-W (2019) A similarity-based hierarchical clustering method for manufacturing process models. Sustainability 11:2560 Google Scholar Alelyani S, Tang J, Liu H (2013) Feature selection for clustering: a review. In: Data clustering: algorithms and applications. Chapman and Hal, Lond...
To prevent the disclosure of the private data, BGV is utilized to encrypt the raw objects before uploading them on cloud. BGV is one of the most efficient fully homomorphic encryption schemes and it has obtained the successful application in cloud computing and deep computation models [5]. ...
data, protocol data, or time series forecasting models, among other methods, to evaluate the performance of Cloud resources and the amount of time it takes to perform tasks in different resources [52,53,54]. This data is used by the resource supply component and the scheduling component to ...
Consensus Big Data Clustering for Bayesian Mixture Models 2023, Algorithms A Novel Hybrid High-Dimensional PSO Clustering Algorithm Based on the Cloud Model and Entropy 2023, Applied Sciences (Switzerland) A New Method for Improving the Fairness of Multi-Robot Task Allocation by Balancing the Distribut...