M2M Protocols: An Overview on LwM2M and XMPP Machine-to-Machine Protocols in IoT Context

In this paper we will present a comprehensive comparison of two used Machine-to-Machine (M2M) communication protocols in the Internet of Things (IoT) scenarios: the Lightweight Machine-to-Machine (LwM2M) and the Extensible Messaging and Presence Protocol (XMPP). The discussion will cover their technical overviews, working mechanisms, and comparisons based on several factors such as protocol reliability, security (authentication and encryption), features, pros and cons, message overhead and transmission efficiency, packet size, and connection establishments. The LwM2M protocol is a fast IoT protocol developed by the Open Mobile Alliance (OMA). It is operated with the Constrained Application Protocol (CoAP) and is greatly famous for being utilized in device management and IoT data communication. Some advantages of LwM2M include providing higher efficiency, easy and stable data transfer, and low power consumption, which is beneficial in long-term and complicated IoT applications, thus making it a good candidate for different industries. On the other hand, the XMPP is a flexible, lightweight protocol that can handle CPU-constrained systems. It is primarily used in messaging and was not developed mainly for IoT applicationsLwM2M and XMPP have different purposes, structures, data processing times, transport, features, and IoT systems architecture. As for security, both protocols have high robust security features. Choosing between LwM2M and XMPP for a specific IoT project needs to be studied based on the requirements of the project to achieve the required aims precisely, as many factors must be taken into consideration when deciding which protocol to use.

Authors

Institutions

Publication Details

Published
2024-09-20
DOI
https://doi.org/10.1109/icis61260.2024.10778343
Citations
2
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.70

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

M2M Protocols: An Overview on LwM2M and XMPP Machine-to-Machine Protocols in IoT Context

Ala’ Khalifeh, Maysam Alkwiefi
2 citations
IoT and Edge/Fog Computing
0.70
article

M2M Protocols: An Overview on LwM2M and XMPP Machine-to-Machine Protocols in IoT Context

Ala’ Khalifeh, Maysam Alkwiefi
article en
2 citations

Abstract

In this paper we will present a comprehensive comparison of two used Machine-to-Machine (M2M) communication protocols in the Internet of Things (IoT) scenarios: the Lightweight Machine-to-Machine (LwM2M) and the Extensible Messaging and Presence Protocol (XMPP). The discussion will cover their technical overviews, working mechanisms, and comparisons based on several factors such as protocol reliability, security (authentication and encryption), features, pros and cons, message overhead and transmission efficiency, packet size, and connection establishments. The LwM2M protocol is a fast IoT protocol developed by the Open Mobile Alliance (OMA). It is operated with the Constrained Application Protocol (CoAP) and is greatly famous for being utilized in device management and IoT data communication. Some advantages of LwM2M include providing higher efficiency, easy and stable data transfer, and low power consumption, which is beneficial in long-term and complicated IoT applications, thus making it a good candidate for different industries. On the other hand, the XMPP is a flexible, lightweight protocol that can handle CPU-constrained systems. It is primarily used in messaging and was not developed mainly for IoT applicationsLwM2M and XMPP have different purposes, structures, data processing times, transport, features, and IoT systems architecture. As for security, both protocols have high robust security features. Choosing between LwM2M and XMPP for a specific IoT project needs to be studied based on the requirements of the project to achieve the required aims precisely, as many factors must be taken into consideration when deciding which protocol to use.

Jade University of Applied Sciences (DE), German Jordanian University (JO)
Gyeongju University
Openalex Percentile: Top 26%
IoT and Edge/Fog Computing
0.70
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.