Search

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 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. [ABSTRACT FROM AUTHOR]

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-toend 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. [ABSTRACT FROM AUTHOR]

In the of the Internet of Things (IoT) realm, congestion is considered a serious issue affecting network throughput due to the requirement of multiple nodes for message exchange. With free-space optical communications, which can help send a message wirelessly, congestion control mechanisms nowadays depend upon the carrier sense of multiple access with collision avoidance (CSMA/CA), using the so-called Backoff Algorithm (BA). These algorithms, including Binary Exponential Backoff (BEB), Enhanced Fibonacci Backoff (EFB), Estimation-Based Backoff (EBA), and Backoff Interval Isolation (BII), have been introduced to facilitate congestion control mechanisms. Implementing such algorithms, however, might not deliver the greatest performance for Constrained Application Protocol (CoAP) which typically operates under limited resources. Therefore, the present study aims to introduce a new backoff algorithm, Triangular Number Sequence Backoff (TNSB), and to compare its performance with that of the aforementioned algorithms under the Transmission Control Protocol (TCP) and the Cooja network simulator. Statistical analysis involves ANOVA (F-test) and post hoc multiple comparison tests. The study shows that its performance is not significantly different from the others at the low congestion level. At the middle and the high congestion levels, it yields the highest throughput with the shortest settling time, while the packet loss rate and the response time are satisfactory.

In the of the Internet of Things (IoT) realm, congestion is considered a serious issue affecting network throughput due to the requirement of multiple nodes for message exchange. With free-space optical communications, which can help send a message wirelessly, congestion control mechanisms nowadays depend upon the carrier sense of multiple access with collision avoidance (CSMA/CA), using the so-called Backoff Algorithm (BA). These algorithms, including Binary Exponential Backoff (BEB), Enhanced Fibonacci Backoff (EFB), Estimation-Based Backoff (EBA), and Backoff Interval Isolation (BII), have been introduced to facilitate congestion control mechanisms. Implementing such algorithms, however, might not deliver the greatest performance for Constrained Application Protocol (CoAP) which typically operates under limited resources. Therefore, the present study aims to introduce a new backoff algorithm, Triangular Number Sequence Backoff (TNSB), and to compare its performance with that of the aforementioned algorithms under the Transmission Control Protocol (TCP) and the Cooja network simulator. Statistical analysis involves ANOVA (F-test) and post hoc multiple comparison tests. The study shows that its performance is not significantly different from the others at the low congestion level. At the middle and the high congestion levels, it yields the highest throughput with the shortest settling time, while the packet loss rate and the response time are satisfactory. [ABSTRACT FROM AUTHOR]

The constrained application protocol (CoAP) is an application layer protocol in IoT, with underlying support for congestion control mechanism. It minimizes the frequent retransmissions, but does not optimize the throughput or adapt dynamic conditions. However, designing an efficient congestion control mechanism over the IoT poses new challenges because of its resource constraint nature. In this context, this article presents a new Intelligent congestion control algorithm (iCoCoA) for constraint devices, motivated by the success of the deep reinforcement learning in various applications. The iCoCoA learns from the various network features to decide the best Retransmission Timeout to mitigate the congestion in the dynamic environments. It also optimizes the throughput, energy, and unnecessary frequent retransmissions compared with the existing models. iCoCoA is developed and tested on the Cooja simulator and compared it with the standard protocols such as CoAP, CoCoA, and CoCoA+ in continuous and burst traffic conditions. The proposed iCoCoA mitigates congestion, outperforms 4–15% in throughput, 3–10% better packet delivery ratio, and 7–16% energy-efficiency with reduced number of retransmissions. [ABSTRACT FROM AUTHOR]

Cloud computing is a massive amount of dynamic ad distributed resources that are delivered on request to clients over the Internet. Typical centralized cloud computing models may have difficulty dealing with challenges caused by IoT applications, such as network failure, latency, and capacity constraints. One of the introduced methods to solve these challenges is fog computing which makes the cloud closer to IoT devices. A system for dynamic congestion management brokerage is presented in this paper. With this proposed system, the IoT quality of service (QoS) requirements as defined by the service-level agreement (SLA) can be met as the massive amount of cloud requests come from the fog broker layer. In addition, a forwarding policy is introduced which helps the cloud service broker to select and forward the high-priority requests to the appropriate cloud resources from fog brokers and cloud users. This proposed idea is influenced by the weighted fair queuing (WFQ) Cisco queuing mechanism to simplify the management and control of the congestion that may possibly take place at the cloud service broker side. The system proposed in this paper is evaluated using iFogSim and CloudSim tools, and the results demonstrate that it improves IoT (QoS) compliance, while also avoiding cloud SLA violations. [ABSTRACT FROM AUTHOR]

In Internet of Things (IoT) networks, congestion is growing with the increasing number of devices, and a large amount of collected data must be transferred. Congestion control is one of the most significant challenges for such networks. The Constrained Application Protocol (CoAP) has been adopted for the IoT to satisfy the demand for smart applications. However, CoAP uses a basic congestion control algorithm that operates only when congestion occurs. Thus, the basic CoAP and most similar loss-based congestion control schemes have remaining issues for burst data transfer in dynamic network environments. This paper proposes a novel rate-based congestion control scheme using fuzzy control for CoAP, called FuzzyCoAP. We use the round-trip time gradient and bottleneck bandwidth gradient as inputs for FuzzyCoAP to infer the degree of congestion. FuzzyCoAP uses this indicator to predict early congestion and adjusts the sending rate to avoid congestion. FuzzyCoAP uses the congestion degree to update the variable RTO for retransmissions. On the other hand, FuzzyCoAP dynamically checks for the available bandwidth to gain high performance for burst data transfer. Various simulation experiments have demonstrated the feasibility of the FuzzyCoAP in different traffic scenarios. We compared the proposed scheme with representative loss-based CoAP schemes, that is, the basic CoAP. The simulation results proved that FuzzyCoAP provides high performance in terms of delay, throughput, loss rate, and retransmissions compared with the basic CoAP.

IoT is emerging as a massive web of heterogeneous networks estimated to interconnect over 41 billion devices by 2025, generating around 79 zettabytes of data. The heterogeneous network shall bring in a plethora of digital services leveraging cloud and communication technologies to drive smart city applications. As users access these services remotely in a ubiquitous environment over public channels, it becomes imperative to secure their communication. Both entity and message authentication emerge as a critical security primitive to thwart unauthorized access and prevent the falsification of messages. While researchers have given due attention to achieving mutual authentication between the subscriber (remote user) and gateway node (broker), the mutual authentication between the gateway node and an IoT sensor node is left to be desired. It could be done at the peril of a rogue or a shadow IoT device unauthorizedly joining an IoT-based network. Some of the widely used IoT-specific application layer protocols like constrained application protocol (COAP) and message queue telemetry transport (MQTT) protocol are not inherently equipped with adequate security safeguards. They, therefore, rely on underlying transport layer security protocols, which are highly computationally intensive. To address this issue, this paper proposes a three-factor authentication framework suitable for IoT-driven critical applications based upon identity, password and a digital signature scheme. The framework employs publish-subscribe pattern leveraging elliptical curve cryptography (ECC) and computationally low hash chains. The formal and informal security analysis shows that the framework is resistant to different types of cryptographic attacks. Furthermore, the automated validation performed with the Scyther tool verifies that there are no cryptographic attacks found on any of the claims stated in the proposed framework. Finally, a comparison of the framework security features, computational, and communication overheads is carried out with other existing protocols. [ABSTRACT FROM AUTHOR]

Cloud computing is a massive amount of dynamic ad distributed resources that are delivered on request to clients over the Internet. Typical centralized cloud computing models may have difficulty dealing with challenges caused by IoT applications, such as network failure, latency, and capacity constraints. One of the introduced methods to solve these challenges is fog computing which makes the cloud closer to IoT devices. A system for dynamic congestion management brokerage is presented in this paper. With this proposed system, the IoT quality of service (QoS) requirements as defined by the service-level agreement (SLA) can be met as the massive amount of cloud requests come from the fog broker layer. In addition, a forwarding policy is introduced which helps the cloud service broker to select and forward the high-priority requests to the appropriate cloud resources from fog brokers and cloud users. This proposed idea is influenced by the weighted fair queuing (WFQ) Cisco queuing mechanism to simplify the management and control of the congestion that may possibly take place at the cloud service broker side. The system proposed in this paper is evaluated using iFogSim and CloudSim tools, and the results demonstrate that it improves IoT (QoS) compliance, while also avoiding cloud SLA violations.

The ecosystem for an Internet of Things (IoT) generally comprises endpoint clients, network devices, and cloud servers. Thus, data transfers within the network present multiple security concerns. The recent boom in IoT applications has accelerated the need for a network infrastructure that provides timely and safe information exchange services. A shortcoming of many existing networks is the use of static key authentication. To enable the use of automatic key update mechanisms in IoT devices and enhance security in lightweight machine-to-machine (M2M) communications, we propose a key update mechanism, namely, double OTP (D-OTP), which combines both one-time password (OTP) and one-time pad to achieve an IoT ecosystem with theoretically unbreakable security. The proposed D-OTP was implemented into the Constrained Application Protocol (CoAP) through the commonly used libcoap library. The experimental results revealed that an additional 8.93% latency overhead was required to obtain an unbreakable guarantee of data transfers in 100 CoAP communication sessions.

The ecosystem for an Internet of Things (IoT) generally comprises endpoint clients, network devices, and cloud servers. Thus, data transfers within the network present multiple security concerns. The recent boom in IoT applications has accelerated the need for a network infrastructure that provides timely and safe information exchange services. A shortcoming of many existing networks is the use of static key authentication. To enable the use of automatic key update mechanisms in IoT devices and enhance security in lightweight machine-to-machine (M2M) communications, we propose a key update mechanism, namely, double OTP (D-OTP), which combines both one-time password (OTP) and one-time pad to achieve an IoT ecosystem with theoretically unbreakable security. The proposed D-OTP was implemented into the Constrained Application Protocol (CoAP) through the commonly used libcoap library. The experimental results revealed that an additional 8.93% latency overhead was required to obtain an unbreakable guarantee of data transfers in 100 CoAP communication sessions. [ABSTRACT FROM AUTHOR]