A survey on subjecting electronic product code and non-ID objects to IP identification

TL;DR

This survey reviews methods for assigning IP identification to electronic product codes and non-ID objects in IoT, evaluating their advantages, disadvantages, and key metrics like scalability and cost.

Contribution

It provides a comprehensive comparison of existing IP identification techniques for IoT objects, highlighting key evaluation metrics and future research directions.

Findings

Different methods vary in computational overhead and scalability.

Evaluation metrics include adaptability and implementation cost.

The field remains active with ongoing research challenges.

Abstract

Over the last decade, both research on the Internet of Things (IoT) and real-world IoT applications have grown exponentially. The IoT provides us with smarter cities, intelligent homes, and generally more comfortable lives. However, the introduction of these devices has led to several new challenges that must be addressed. One of the critical challenges facing interacting with IoT devices is to address billions of devices (things) around the world, including computers, tablets, smartphones, wearable devices, sensors, and embedded computers, and so on. This article provides a survey on subjecting Electronic Product Code and non-ID objects to IP identification for IoT devices, including their advantages and disadvantages thereof. Different metrics are here proposed and used for evaluating these methods. In particular, the main methods are evaluated in terms of their: (i) computational overhead, (ii) scalability, (iii) adaptability, (iv) implementation cost, and (v) whether applicable to already ID-based objects and presented in tabular format. Finally, the article proves that this field of research will still be ongoing, but any new technique must favorably offer the mentioned five evaluative parameters.