Data Gathering from IoT Networks

Abstract

The Internet of Things (IoT) is a new paradigm where anything can be connected to Internet using heterogeneous networks; they have an unstable structure according to the constraint devices that are the main characteristic of this paradigm. Also, edge computing is becoming a fast base for most IoT devices, especially in smart cities. It is the ideal solution for providing devices with the connectivity needed to deliver low-latency services to end-users. However, selecting nodes that can participate in data gathering by edge computing or by other nodes must be efficient in terms of the performance of these constrained devices. To deal with these issues, we propose a clustering mechanism to group the nodes based on their capabilities using the k-means algorithm, and then the selection phase can be lanced to select the most capable node, where two phases are performed by the edge server. The simulation results demonstrate that our approach makes the execution time minimized and the network lifetime increased.