An Improved Energy-Aware Clustering Method for the Regional Queries in the Internet of Things

Abstract

We will offer a method to improve energy efficient consumption for processing queries on the Internet of Things. We focused on an energy efficient hierarchical clustering index tree such that we can facilitate time-correlated region queries in the I.O.T (Internet of Things). We try to improve clustering and make a change on its proposed index tree. We try to do this by optimizing the query processing. We improve clustering to increase the accuracy of the Internet of Things and prevent the network from disconnecting. In the article that we have chosen, there is a heterogeneous cluster which means there exists a large data difference in the two ends of a cluster. Also, it often happens that the same information is sent to the base station by two overlapping clusters; therefore, we save energy by eliminating duplicated data.

A Proposed Fuzzy Logic Approach for Conserving the Energy of Data Transmission in the Temperature Monitoring Systems of the Internet of Things

“…The third type of example is the natural disaster monitoring system that detects earthquakes or volcanic eruptions. If a disaster occurs, all normal recorded measured data before and during the disaster located in the surrounding area must be properly transmitted on time to take actions, such as alert, evacuation, or even search and rescue operations [6]. As a result, these critical data transmissions should not be hampered by a lack of energy resources in the applications, and energy consumption must be properly managed during the data transmission process.…”