Abstract
Internet of Things (IoT) is a new concept in the information and communication technology studies which indicates that any creature (human, animal, or object) can send and receive data through communication networks, such as the internet or intranet platform. Wireless sensors have limited energy resources due to the use of batteries to supply energy, and since it is usually not possible to replace the batteries of these sensors. In addition, the lifespan of the wireless sensor network is limited and short. Therefore, reducing the energy consumption of sensors in IoT networks for increasing network lifespan is one of the fundamental challenges and issues in these networks. In this paper, a routing protocol is proposed and simulated based on an ant colony optimization algorithm’s performance. The clustering is performed with a routing method based on energy level criteria, collision reduction, distance from the cluster-head to the destination, and neighborhood energy in the proposed method. The cluster head is selected based on the maximum residual energy, minimum distance with other clusters, and consumed energy. This energy is minimized to reach the base station. The node with more energy than the threshold is selected as the new cluster head. Then, four conditions are applied for routing: the shortest path, the leading path, the shortest distance to the source node and the destination node, and routing. Results show that after about 50 cycles of transferring information, only the average of 19.4% of the initial energy is consumed in the network nodes. Therefore, obtained results illustrate that the proposed method helps to retain the energy more than 40% comparing the available methods.
Highlights
The Internet connects all users, but this network’s structure is changing, and a new member is being added to the accumulation
This paper aims to present a routing method based on machine learning algorithms to reduce energy consumption and increase network life in the Internet of Things (IoT) system
This paper aims to use the efficient, ultra-innovative, and nature-inspired optimization algorithm called the ant colony optimization algorithm to route IoT and optimize energy consumption and network life
Summary
The Internet connects all users, but this network’s structure is changing, and a new member is being added to the accumulation. The Internet of Things is a network of physical objects embedded with electronic components [4], software [5], sensors [6], and connections [7]. They can provide more value and services by exchanging information (at unprecedented speeds and scales) with manufacturers, operators, or other devices. The primary intellectual basis of the ant algorithm is: “Among the obstacles and limitations in nature, ants always choose the most optimal way from different permutations to reach food.”. These elements are fundamentally different from real ants, which are: memory, artificial barriers, life in a discrete environment [31]
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