Comparative Analysis of Indexing Schemes Used in Cloud Computing Data Management

Summary

In recent years, IoT networks are producing a huge amount of data as the number of sensors, actuators, and IoT enabled devices are increasing day‐by‐day. Different techniques have been suggested by the researchers that segregate the source data into its various subsets. The efficiency of the search technique fully depends upon the exponential growth of the data on the IoT enabled networks. This chapter presents a comparative analysis of various indexing data structures used in cloud computing for data management. To evaluate the performance of the existing indexing structures, different experiments have been carried out. The existing techniques are compared based on different parameters such as quality of index, performance of exact search, efficiency of the similarity search, and data partitioning rate. The results obtained from the comparative analysis illustrate that different existing indexing data structures perform well on different parameters and also present their deficiencies on certain parameters. After the comparative analysis, it is concluded that more efficient indexing structures can be developed to increase the quality of data indexing used over the IoT networks. The improvement in indexing techniques can efficiently handle the rapidly‐growing techniques of IoT networks.