A Hybrid Method for Energy Efficient Data Storage in the Internet Of Things

Abstract

In the Internet of Things (IoT), to increase the volume of stored data, distributed systems have replaced by centralized systems, and high volume data is divided into smaller sections and each section is stored in a data registration center. The design of the system should be such that even with a number of unavailable data centers, all information is still retrievable, therefore it is necessary to store multiple copies of the information in the system so that the initial information is not lost, despite the loss of part of the data registration center. In the distribution data storage, node energy balance and reduce the cost of access to data is a major problem between sensor nodes. Sensor node clustering is a viable solution to solve this problem. In this paper, a distributed data storage method using PSO and the K-means clustering mechanism organized by the binary decision tree C4.5 in the Internet of Things environment was proposed. As the simulation results show, the proposed method has been able to reach increasing availability, decreasing communication costs, and decreasing energy usage.