Distributed UCON in CoAP and MQTT Protocols

Internet of Things (IoT) is a prominent paradigm applied to several areas ranging from medicine to industrial networks. It aims at connecting to the Internet of million of daily used objects. Important challenges in this area consist in to propose mechanisms and protocols that meet security, device interoperability, quality of service and energy-efficiency requirements. Particularly, the Message Queue Telemetry Transport (MQTT) protocol has been prospected in order to provide efficient communication at the application layer for the IoT. This survey aims to present the fundamentals, tools and future directions related to MQTT protocol and its variation tailored for sensor networks, called MQTT-SN. We discuss such protocols comparing to other current IoT application layer protocols, such as Constrained Application Protocol (CoAP). Additionally, we present tools so as to support practical experimentation and simulation. Particularly, we carry out pactical experiments to observe the communication delay between MQTT and CoAP. Finally, the open issues and challenges in this area are examined.

The Internet of Things (IoT) is a framework of interconnected computing devices mechanical and digital machines, internationally identifiable physical objects (or things) or people that are have unique identity and the ability to transfer data over a network without human-to-human or human-to-computer interaction., their combination with the Internet, and their representation in the digital world. The accessibility and availability of cheap components of IoT devices enables a extensive range of applications and provide smart environments. These devices perform actuating and sensing tasks and identified through unique addresses. The IoT devices are connected to the Internet and expected to use the Constrained Application Protocol (CoAP) at the application layer as a main web transfer protocol. Message Queuing Telemetry Transport (MQTT) does not enforce the use of a particular security approach for its applications, but instead leaves that to the application designer. Therefore, IoT solutions can be based on application context and specific security requirements. MQTT is a Client Server publish/subscribe messaging transport protocol. It is lightweight, open, uncomplicated, and designed to make implementation more easier. These characteristics of MQTT make it perfect for use in most of the situations, including communication in Machine to Machine (M2M) and Internet of Things (IoT). In IOT there is major use of Wireless Sensor Networks (WSN) which connects virtual world to physical world. In this paper focus is given to application layer of IOT. In application layer two important protocols are MQTT and CoAP. Security mechanism is proposed in the paper for these protocols.

The Internet of Things (IoT) is growing rapidly as more and more household appliances, sensors and actuators are connected to the internet and communicate with each other. Because these IoT devices usually have only limited processing and communication capabilities, an efficient communication protocol is required to reduce the protocol overhead. The Message Queue Telemetry Transport (MQTT) protocol provides such properties. MQTT is a publish/subscribe protocol, where each client can subscribe to a message topic in order to receive all messages published under that topic. The payload of a message (i.e., the content) can be encrypted to hide private information. However, to forward messages, the topic of a message needs to be read by the broker and thus cannot be encrypted and might reveal private information. This paper presents methods to avoid this problem. It features and evaluates a one-time password approach to provide a fully obfuscated communication method for MQTT topics. Thereby, the user tracking and the generation of profiles is prevented.

Online monitoring for sliver quality is an important part of the drawing process. This paper presents a high-speed drawing frame monitoring system based on Internet of Things (IoT) using Message Queuing Telemetry Transport (MQTT) protocol, which consists of drawing frame IoT terminal equipment, the cloud server and PC or mobile terminal equipments. Drawing frame IoT terminal equipment takes Cortex-A7 and Cortex-M4 of series of i.MX7 as its control cores. The A7 processor publishes IoT data as a communication gateway while the M4 processor collects sensor data and executes local on-line detection program. Two processors run Linux and FreeRTOS as operating system respectively, and the data exchange between them adopt rpmsg pattern. The communication gateway using MQTT publishes data of the IoT terminal to the cloud server for remoting monitoring and intelligent diagnosis, when the local on-line detection system aims at acquiring real-time status of the sliver on drawing frame. Users can check the real-time status of the drawing frame at the subscription end of IoT and on the computer or mobile phone end by subscribing message by theme. Experiments show that the system operates with reliability, and is good compatible with other devices because of the modular design. The adoption of this system can promote the digitization and the intelligentialize of the drawing frame.

The need for embedded devices to be able to exchange information with each other and with data centers is essential for the advent of the Internet of Things (IoT). Several existing communication protocols are designed for small devices including the message-queue telemetry transport (MQTT) protocol or the constrained application protocol (CoAP). However, most of the existing implementations are convenient for computers or smart phones but do not consider the strict constraints and limitations with regard resource usage, portability and configuration. In this paper, we report on an industrial research and development project which focuses on the design, implementation, testing and deployment of a MQTT module. The goal of this project is to develop this module for platforms having minimal RAM, flash code memory and processing power. This software module should be fully compliant with the MQTT protocol specification, portable, and inter-operable with other software stacks. In this paper, we present our approach based on abstraction layers to the design of the MQTT module and we discuss the compliance of the implementation with the requirements set including the MISRA static analysis requirements.

Design and implementation of an open-Source IoT and blockchain-based peer-to-peer energy trading platform using ESP32-S2, Node-Red and, MQTT protocol

Energy systems are now incorporating Internet of Things technology to make better monitoring and management of energy possible. This research study analyzes the design and implementation of a secure and smart monitoring network for hybrid energy systems using two of the most widely known Internet of Things protocols and AI, MQTT (Message Queuing Telemetry Transport) and CoAP (Constrained Application Protocol). Traditional energy monitoring has latency issues, low scalability. This paper discusses an enhancement over this with MQTT and CoAP, aiming at increasing overall performance and scalability within hybrid energy frameworks. Methodologies are developed to implement the application with IoT sensors and to collect data from MQTT and CoAP protocols for further processing in the Python programming language. To demonstrate these improvements in efficiency and reliability, the results are compared against those obtained from traditional systems. This work investigates how Internet of Things (IoT) and AI can be deployed in hybrid energy systems with advanced communication protocols to enhance observability as well as control. A total of many enhancements have been added to this system: latency by 35% has been minimized, data transmission efficiency of 96.87%, a reliability increase of 28%, 25% enhancement in scalability, and 20% reduction in energy consumption.

Ensuring the well-being of livestock and maximizing agricultural output both need vigilant monitoring. Biometric sensing in cattle is the focus of this article, which offers a thorough solution based on Multi-Sensor Fusion (MSF) connected to the Internet of Things (IoT). The technology uses a number of physiological sensors to record the animal's vitals in real-time a comprehensive overview of its health. With the help of the IoT architecture, sensors may easily connect to one another and share data remotely. Improved data exchange efficiency, reduced latency, and dependable device-to-device communication are all results of using the Message Queuing Telemetry Transport (MQTT) protocol. The suggested system integrates data from many sensors to provide more reliable health insights. Constant monitoring of vital signs (heart rate, temperature, and activity levels) enables prompt identification of abnormalities or indications of distress. The combination of data from several sensors allows for a more detailed assessment of the animal's health, which in turn allows for preventative measures and individualized treatment. The MQTT protocol, data may be sent in real-time to a central server or cloud platform, simplifying the flow of information. This data may be examined to provide valuable insights that can be used by vets and farmers to make timely decisions.

The proliferation of the Internet of Things (IoT) has introduced significant challenges in protocol selection for resource-constrained devices operating in smart healthcare, industrial automation, and agricultural monitoring. While lightweight protocols like Message Queuing Telemetry Transport (MQTT) and Constrained Application Protocol (CoAP) are designed for low-power Wide Area Networks, the ubiquity of Hypertext Transfer Protocol (HTTP) persists despite its substantial overhead. This research provides a multi-dimensional performance evaluation of MQTT, CoAP, and HTTP using the NS-3 discrete-event simulator. The study uniquely benchmarks these protocols across nine performance metrics, including Average Latency, Network Jitter, CPU Energy Usage, and Network Footprint, under varying iteration loads (50 and 500) to simulate both nominal and high-stress IoT environments. Our empirical analysis demonstrates that while CoAP provides the highest throughput and lowest resource consumption, MQTT offers superior reliability in persistent monitoring scenarios. Notably, the evaluation reveals a critical scalability threshold for HTTP, where high-stress iterations lead to a complete communication collapse (0% PDR) due to TCP-induced network saturation. By correlating system-level impact (CPU usage) with network-level stability (Jitter), this paper proposes an application-specific decision framework. The findings serve as a technical roadmap for optimizing next-generation IoT deployments based on specific latency and energy requirements.

The Message Queuing Telemetry Transport (MQTT) protocol is one of the most extended protocols on the Internet of Things (IoT). However, this protocol does not implement a strong security scheme by default, which does not allow a secure authentication mechanism between participants in the communication. Furthermore, we cannot trust the confidentiality and integrity of data. Lightweight IoT devices send more and more sensible data in areas of Smart Building, Smart City, Smart House, Smart Car, Connected Car, Health Care, Smart Retail, Industrial IoT (IIoT), etc. This makes the security challenges in the protocols used in the IoT particularly important. The standard of MQTT protocol strongly recommends implement it over Transport Layer Security (TLS) instead of plain TCP. Nonetheless, this option is not possible in most lightweight devices that make up the IoT ecosystem. Quite often, the constrained resources of IoT devices prevent the use of secure asymmetric cryptography algorithms implemented by themselves. In this article, we propose making a security schema in MQTT protocol using Cryptographic Smart Cards, for both challenges, the authentication schema and the trusted data confidentiality and data integrity. We carry out this security schema without modifying the standard protocol messages. And finally, we present a time results experiment using an example implementation model with JavaCard library.

Edge computing is proposed to solve the problem of centralized cloud computing caused by a large number of IoT (Internet of Things) devices. The IoT protocols need to be modified according to the edge computing paradigm, where the edge computing devices for analyzing IoT data are distributed to the edge networks. The MQTT (Message Queuing Telemetry Transport) protocol, as a data distribution protocol widely adopted in many international IoT standards, is suitable for cloud computing because it uses a centralized broker to effectively collect and transmit data. However, the standard MQTT may suffer from serious traffic congestion problem on the broker, causing long transfer delays if there are massive IoT devices connected to the broker. In addition, the big data exchange between the IoT devices and the broker decreases network capability of the edge networks. The authors in this paper propose a novel MQTT with a multicast mechanism to minimize data transfer delay and network usage for the massive IoT communications. The proposed MQTT reduces data transfer delays by establishing bidirectional SDN (Software Defined Networking) multicast trees between the publishers and the subscribers by means of bypassing the centralized broker. As a result, it can reduce transmission delay by 65% and network usage by 58% compared with the standard MQTT.

The fast growth of the Internet of Things (IoT) has made this technology one of the most promising paradigms of recent years. Wireless Sensor Networks (WSNs) are one of the most important challenges of the Internet of things. These networks are made up of devices with limited processing power, memory, and energy. The constrained nature of WSNs makes it necessary to have specific restricted protocols to work in these environments. In this paper, we present an energy consumption and network traffic study of the main IoT application layer protocols, the Constrained Application Protocol (CoAP), and the version of Message Queue Telemetry Transport (MQTT) for sensor networks (MQTT_SN). The simulations presented evaluate the performance of these protocols with different network configurations.

In this paper we compare the performance of three application layer protocols, that are Constrained Application Protocol (CoAP), WebSocket and Message Queuing Telemetry Transport (MQTT), in an Internet of Things (IoT) scenario. The three protocols have been implemented on the same low cost and low complexity hardware platform, suitable for IoT applications. The performance, in terms of protocol efficiency, strictly related to the overhead, and average Round Trip Time (RTT), were experimentally evaluated. In the considered scenario an IoT device was transmitting data to a server and waiting for replies. IEEE 802.11.b/g/n air interface was used for the communication between the IoT device and an Access Point (AP), connected to the final server. Two different settings have been considered: a local area network (LAN) configuration, where the AP and the server were in the same LAN; and a more realistic IoT configuration, where the AP was connected to a remote server via the Internet. Furthermore, in the IoT configuration, two types of Internet connection are considered: a connection established through a home router and another via cellular network. Results show that CoAP achieves the highest protocol efficiency and the lowest average RTT, closely followed by WebSocket. The performance of MQTT protocol strongly depend on the Quality of Service (QoS) profile. Changing the environment, from a LAN network to a realistic IoT scenario, does not significantly impact the protocol efficiency, but has a considerable influence on the average RTT, which increases by a factor of 2 or 3, depending on the protocol. Finally, we give some insights on the impact of routing through a cellular network on the system performance.

Ensuring the security of networks is a significant hurdle in the rollout of the Internet of Things (IoT). A widely used protocol in the IoT ecosystem is message queuing telemetry transport (MQTT), which is based on the published-subscribe model. IoT manufacturers are expected to expand their usage of the MQTT protocol, which is expected to increase the number of cyber security threats against the protocol. IoT settings are crucial to overcoming scalability and computing resource issues and minimizing the characteristics needed for categorization. Machine learning (ML) is extensively used in traffic categorization and intrusion detection. This study proposes a ML-based network traffic detection model (MLNTDM) to enhance IoT application layer attack detection. The proposed architecture for the MQTT protocol is evaluated based on its effectiveness in detecting malicious attacks and how these affect various MQTT brokers. This study focuses on low-power-consuming ML algorithms for detecting IoT botnet offenses and identifying typical attacks and their responses. With this framework, each network flow provides information that can help identify the source of generated traffic and network assaults. Results from our approach, as shown in the experiment, prove more accuracy.

Uninterruptible power supply (UPS) monitoring system using message queuing telemetry transport (MQTT) protocol is a solution to solve UPS monitoring issues in a large infrastructure. This paper discusses the proof of the small size of message data by using the MQTT protocol on IoT-based communications. Based on IoT concept, the system described in this paper used Arduino microcontroller connected to the Internet via an Ethernet shield. The system used MQTT as a communication protocol that was designed for a lightweight communication. This system was intended to display UPS monitoring data in real-time on a web page stored on raspberry pi which roles as a web server, MQTT broker, MQTT subscriber and database. UPS parameter could be monitored using a web-based application. There were some differences in data obtained from sensor with the measurement results of measuring instruments specified for each parameter: the difference of input voltage was equal to 0.20%, while differences of output voltage, output power and output current reached 1.34%, 0.17% and 20%, respectively.