Review: Energy Optimization Techniques Based on Swarm Intelligence for Internet of Things

Abstract

The Internet of Things is an advanced technology phenomenon commonly utilized in diverse fields like those of smart cities, smart air traffic, smart workplace, etc. Well into the industry the renewed interest in communicating everything to the Internet has so far not gone undetected. According to sensor-embedded IoT equipment, another new actor for whom the goal seems to be to track that control devices at home remotely is almost always complicated. Another of the main problems that must be tackled is the primary catalyst for collecting enormous large amounts of data and handling such massive amounts of data sets. Despite enhanced traffic volume and self-interested natured IoT appliances, handling their resources wisely is a desperate necessity. It would be appropriate to incorporate IoT within AI-based approaches like those of swarm intelligence which equally assign energy ratios to either the relatively small electronic devices. Swarm Intelligence (SI) seems to be the systemic change between humans, as well as virtual, autonomous, self-organized processes. This work addresses some overview of conventional energy optimization methods for IoT focusing on Swarm Intelligence.

Keywords: Energy optimization, particle swarm optimization, Internet of things, Swarm optimization, ant colony optimization, bee colony optimization algorithm.