Towards an efficient big data management schema for IoT

Abstract

Internet of things (IoT) is an essential technology in our life; the importance of IoT is yearly increasing because of the excellent usage value. IoT management can help stakeholders in analyzing and making the right decisions based on previous historical sensed data. However, some challenges emerge while using the IoT that will be more complicated in the future. Data management is one of the significant challenges that is facing IoT technology. The growth of the number of sensors will increase the generated data (Big Data). In a few years, the problem of analyzing, processing, and storing such data will become a highly complex process. Due to the mentioned challenges, in this paper, we propose a new schema to efficiently store the structured IoT data to improve the performance of analyzing and retrieving the data. The main idea about the proposed schema is performed in the data preprocessing step by grouping the data into different levels without losing any single value (lossless compression). We evaluate our proposed schema using eight other datasets in terms of storage size and processing time; our results show that the proposed schema outperforms the traditional storing method for all datasets.