Performance analysis of IoT networks in terrestrial environment utilizing LZW data compression technique

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 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.

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 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.

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.

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.

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.

Service discovery is one of the key requirements to realize the vision of the Internet of Things (IoT). Constrained application protocol (CoAP) is a well-accepted model that utilizes both centralized and distributed service discovery methods for lightweight and constrained IoT networks. Since CoAP is in its early stage of adoption for the IoT networks, it is important to select an efficient method for the service discovery requirement. In this paper, we implement both centralized and distributed models of the CoAP based service discovery techniques. We have used Contiki OS and Cooja simulator to build the experimental setup for our prototype systems. Our detailed empirical analysis finds the gaps in general CoAP based service discovery techniques to recommend further improvement scopes.

Recently, IETF (Internet Engineering Task Force) presented CoAP (Constrained Application Protocol) for the communication between sensor and actuator nodes in a constrained environment such as small amount of memory and low power. IETF CoAP protocol can convert easily, and can use to monitor or control infrastructure utilities through low-power sensor and actuator networks in IoT (Internet of Things) and M2M (Machine-to-Machine) environment. IETF CoAP protocol provides the special requirements of this constrained environment, especially considering energy, automation, and other IoT applications. In this paper, we design and implement a node registration and discovering based CoAP in IoT environment. The node is a CoAP node which is designed for working in constrained environment. For node registration in IoT, we used CoRE RD (Resource Directory) functionalities to register CoAP node’s information which works in IoT environment.

Constrained Application Protocol (CoAP) and Message Queue Telemetry Transport (MQTT) are two IoT application layer protocols that are seeing increased attention and industry deployment. CoAP uses a request-response model and runs over UDP, while MQTT follows a publish-subscribe model running over TCP. For more constrained IoT devices, MQTTSensor Networks (MQTT-SN) provides a UDP-based transport between the sensor and an MQTT-SN gateway, while using TCP between that gateway and the MQTT broker. Quick UDP Internet Connections (QUIC) is a new protocol and although not originally designed for IoT devices, some design features such as reduced connection establishment time may be useful in an IoT environment. Each of these protocols seeks optimizations in features and implementation complexity based on application domains rather than having the full flexibility and adaptability of traditional transport protocols such as TCP. We investigate and analyze four protocols, namely, CoAP, MQTT, MQTT-SN and QUIC, to understand the overhead of obtaining data from an IoT device at a sink to potentially disseminate this data downstream. These constrained IoT devices often operate under challenging, varying network conditions, and it is important to understand the limitations of the protocols in such conditions. Thus, we evaluate the performance of these protocols under varying loss, delay and disruption conditions to identify the most effective environment for their operation and understand the limitations of their dynamic range. Results show that with non-confirmable CoAP a more adaptive wait timer is required; and a more streamlined QUIC protocol may be a potential alternative IoT protocol.

Energy-efficient dynamic homomorphic security scheme for fog computing in IoT networks

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.

Internet of Things (IoT) plays an increasingly significant role in our daily activities, connecting physical objects around us into digital services. In other words, IoT is the driving force behind home automation, smart cities, modern health systems, and advanced manufacturing. This also increases the likelihood of cyber threats against IoT devices and services. Attackers may attempt to exploit vulnerabilities in application protocols, including Domain Name System (DNS), Hyper Text Transfer Protocol (HTTP) and Message Queue Telemetry Transport (MQTT) that interact directly with backend database systems and client-server applications to store data of IoT services. Successful exploitation of one or more of these protocols can result in data leakage and security breaches. In this paper, an ensemble intrusion detection technique is proposed to mitigate malicious events, in particular botnet attacks against DNS, HTTP, and MQTT protocols utilized in IoT networks. New statistical flow features are generated from the protocols based on an analysis of their potential properties. Then, an AdaBoost ensemble learning method is developed using three machine learning techniques, namely decision tree, Naive Bayes (NB), and artificial neural network, to evaluate the effect of these features and detect malicious events effectively. The UNSW-NB15 and NIMS botnet datasets with simulated IoT sensors' data are used to extract the proposed features and evaluate the ensemble technique. The experimental results show that the proposed features have the potential characteristics of normal and malicious activity using the correntropy and correlation coefficient measures. Moreover, the proposed ensemble technique provides a higher detection rate and a lower false positive rate compared with each classification technique included in the framework and three other state-of-the-art techniques.