Analysis of Application Layer Protocols in Internet of Things

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.

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 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) becomes the future of a global data field in which the embedded devices communicate with each other, exchange data and making decisions through the Internet. IoT could improve the quality of life in smart cities, but a massive amount of data from different smart devices could slow down or crash database systems. In addition, IoT data transfer to Cloud for monitoring information and generating feedback that will lead to high delay in infrastructure level. Fog Computing can help by offering services closer to edge devices. In this paper, we propose an efficient system architecture to mitigate the problem of delay. We provide performance analysis like response time, throughput and packet loss for MQTT (Message Queue Telemetry Transport) and HTTP (Hyper Text Transfer Protocol) protocols based on Cloud or Fog servers with large volume of data from emulated traffic generator working alongside one real sensor . We implement both protocols in the same architecture, with low cost embedded devices to local and Cloud servers with different platforms. The results show that HTTP response time is 12.1 and 4.76 times higher than MQTT Fog and Cloud based located in the same geographical area of the sensors respectively. The worst case in performance is observed when the Cloud is public and outside the country region. The results obtained for throughput shows that MQTT has the capability to carry the data with available bandwidth and lowest percentage of packet loss. We also prove that the proposed Fog architecture is an efficient way to reduce latency and enhance performance in Cloud based IoT.

The Internet of Things (IoT) is playing a key role in consumer and business environments. Due to the sensitivity of the information IoT devices collect and share, and the potential impact a data breach can have in people’s lives, securing communication and access to data in IoT has become a critical feature. Multiple application layer protocols are used nowadays in IoT, with the Constrained Application Protocol (CoAP) and the Message Queue Telemetry Transport (MQTT) being two of the most widely popular. In this paper, we propose a solution to increase the security of both CoAP and MQTT based on the distributed Usage Control (UCON) framework. The inclusion of UCON provides dynamic access control to the data shared using these protocols. This occurs by monitoring mutable attributes related to the local protocol nodes and also by sharing data values between remote nodes via the distributed instances of UCON. We present the architecture and the workflow of our approach together with a real implementation for performance evaluation purposes.

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 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

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 spread of the Internet of Things (IoT) has improved our daily life because it blends the physical and the virtual world. Thus, the IoT is device-to-device (D2D) communications that monitor changes in the environment and interacts with them. Also, it can be used from anywhere in the world due to the interconnected nature of the Internet. However, it could violate the privacy of individuals by revealing sensitive information collected by IoT devices about a user's online activities. Also, as the IoT is evolving quickly with new technologies, more privacy issues and abuse of the collected data will arise. Hence, we need to provide more secure communication protocols. In this paper, we will review the security and privacy problems in some IoT protocols. As well as reviewing the proposed solutions to certain problems. Lastly, we will discuss three of the most popular protocols used in the IoT, which are: data distribution service (DDS), message queue telemetry transport (MQTT), and long range wide-area network (LoRa Wan).

In recent years, there has been exponential growth in the Internet of Things (IoT) in various sectors, especially healthcare. The traditional healthcare sector has faced several challenges, such as poor health services, crowding and queuing at medical centers, and manual searches for or missing patient records; a smart health system is needed to overcome these challenges. This study presents the design and implementation of end-to-end IoT architecture, which is built by the integration of various open-source technologies. The pulse care system is implemented using Node.js and React.js, which offer features such as electronic health records (EHR), smart appointments, prescription documentation, and health monitoring. Additionally, various users (admin, patient, doctor, and pharmacist) communicate using a user-friendly graphical interface. In terms of a wearable device, it allows visualization of all the data generated by the sensors in real time (heart rate, body temperature, and blood oxygen). The ESP32 is used as a microcontroller that communicates via its built-in Wi-Fi with the MQTT Mosquitto broker. Standard IoT protocols, Message Queuing Telemetry Transport (MQTT) and Hypertext Transfer Protocol (HTTP), are used. The broker's performance is evaluated in terms of average latency at various QoS levels and with the increase in the number of concurrent users. The results of the experiment demonstrate how important it is to choose the appropriate QoS level based on the requirements of the application. Furthermore, the proposed system's data rate is roughly 3.07 kb/s, which is considered low and suitable for sending small data via any wireless method.

The proliferation of Internet of Things (IoT) devices in terrestrial environments necessitates efficient data transmission and management protocols to optimize network performance. This research paper presents a comprehensive study on the implementation of IoT networks in a terrestrial setting, focusing on the integration of LZW (Lempel-Ziv-Welch) compression with three prominent IoT protocols: CoAP (Constrained Application Protocol), M2M (machine-to-machine), and MQTT (Message Queuing Telemetry Transport). We did a thorough test of these protocols using the NetSim simulator. We looked at how well they worked in terms of throughput, en-to-end delay, and routing overhead, all of which are important for loT network efficiency. The point of our study is to find out what the pros and cons of these protocols are when they are combined with LZW compression in a terrestrial loT setting. The results of our analysis reveal significant variations in the performance of CoAP, M2M, and MQTT when subjected to data compression. Throughput efficiency, which directly impacts data transmission rates, is scrutinized alongside end-to-end delay, a critical factor in ensuring timely data delivery. Additionally, we explore the implications of protocol choice on routing overhead, a crucial metric for network resource utilization. This research contributes to the ongoing efforts to optimize IoT networks in terrestrial settings, offering valuable guidance to network architects and developers seeking to strike the right balance between protocol selection and data compression for improved IoT performance.

One of the challenges faced by today's Internet of Things (IoT) is to efficiently support machine-to-machine communication, given that the remote sensors and the gateway devices are connected through low bandwidth, unreliable, or intermittent wireless communication links. In this paper, we quantitatively compare the performance of IoT protocols, namely MQTT (Message Queuing Telemetry Transport), CoAP (Constrained Application Protocol), DDS (Data Distribution Service) and a custom UDP-based protocol in a medical setting. The performance of the protocols was evaluated using a network emulator, allowing us to emulate a low bandwidth, high system latency, and high packet loss wireless access network. This paper reports the observed performance of the protocols and arrives at the conclusion that although DDS results in higher bandwidth usage than MQTT, its superior performance with regard to data latency and reliability makes it an attractive choice for medical IoT applications and beyond.

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 the internet of things (IoT), there are resource-constrained and immense heterogeneous electronic gadgets worldwide. Till now, no single IoT application layer messaging protocol is the best, nor is anyone axiomatic for every requirement. This paper exhaustively summarizes information on the messaging protocols from the available previous research sources online. Our goal is to encapsulate a simple guideline so that users can choose an optimal messaging protocol quickly according to development requirements and specifications. For this purpose, we have reviewed the literature on six enabling and evolving application layer messaging protocols used for IoT systems namely, message queuing telemetry transport (MQTT), advanced message queuing protocol (AMQP), the constrained application protocol (CoAP), extensible messaging and presence protocol (XMPP), data distribution service (DDS), and simple text-oriented messaging protocol (STOMP) in terms of some interrelated metrics. Additionally, we represented a critical analysis of the application layer messaging protocols. This study will be helpful to readers with valuable insights and guide research scholars and developers in choosing optimal application layer messaging protocols based on development specifications and requirements.