MQTT Broker Performance Comparison between AWS, Microsoft Azure and Google Cloud Platform

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.

Due to the rapid growth of the Internet of Things (IoT), researchers have demonstrated various IoT solutions, which are used to interconnect a wide range of IoT devices through the Internet. However, IoT stumbled into vertical silos; the available solutions provide specific IoT infrastructure, devices, protocols, data formats and models. This diversity and heterogeneity lead to interoperability issues. Heterogeneity happens at all IoT layers, especially at the application layer; devices often adopt mutually incompatible application-layer communication protocols to connect devices to IoT services. Furthermore, in order to integrate semantics to raw data, each system uses its one domain-specific ontology to make data more understandable and interpretable by adding semantic annotations. Working in isolation reduces the interoperability among IoT devices and systems, things across domains need to internetwork and collaborate to provide high level IoT services. Therefore, to alleviate the problem of both communication protocol interoperability and semantic interoperability across vertical silos of systems at the application layer, this paper proposes a semantic gateway (SGIoT) that acts as a bridge between heterogeneous sink nodes at the physical level and IoT services. SGIoT enables interconnectivity between communication protocols such as CoAP and MQTT regardless of their communication model, meanwhile it enables semantics integration throu gh cross-domain ontology (CDOnto) for semantic annotation, in order to provide interpretation of messages among IoT applications across domains. Our approach focuses on modularity and extensibility.

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).

DDoS attacks often happen in cloud servers and cause a devastating problem. However, an increasing number of Internet of Things (IoT) devices makes us not ignore the influence of large-scale DDoS attacks from IoT devices. In this paper, we propose a machine learning-based on a multi-layer IoT DDoS attack detection system, including IoT devices, IoT gateways, SDN switches, and cloud servers. Firstly, we build eight smart poles with various sensors on our campus and collect sensor data as our datasets through wireless networks or wired networks. Next, we extract the features based on DDoS attack types. The feature selection can result in high accuracy DDoS attack detection in the real IoT environment. The experimental results show that our multi-layer DDoS detection system can accurately detect DDoS attacks. And the SDN controller can block venomous devices effectively according to blacklists from the results of our IoT DDoS attacks detection system.

Delivering information from Internet of Things (IoT) devices to a cloud server possesses several security issues, e.g. information eavesdropping, modification, and theft. Therefore, communication between IoT devices and the cloud server should be protected by encryption methods. However, there are few encryption techniques options that are suitable for the need for lightweight communication as demanded by the IoT devices. Due to these circumstances, the NSA launched an encryption algorithm for IoT named Simon and Speck, which are maximally efficient while still providing the advertised level of security, as determined by the key size. This study aims to test and compare the Simon-Speck and AES encryption algorithms and their effect on networking performance on IoT devices. The parameters in this test are delay, throughput, the efficiency of memory usage from the encryption algorithm, and the value of the avalanche effect. Experimental results show that the Speck algorithm outperforms the Simon and the AES algorithms in terms of communication delay and memory usage. Regarding the avalanche effect values, the Simon algorithm possesses the highest avalanche effect value on average against the Speck and the AES algorithms.

A review of the security vulnerabilities and countermeasures in the Internet of Things solutions: A bright future for the Blockchain

The Internet of Things (IoT) has had a considerable influence on our daily lives by enabling enhanced connection of devices, systems, and services that extends beyond machine-to-machine interactions and encompasses a wide range of protocols, domains, and applications. However, despite privacy concerns shown by IoT users, little has been done to reduce and protect individual information exposure. It is extremely difficult to mitigate IoT devices from reidentification threats which is why it is still a major challenge for IoT users to securely protect their information. The trust controls how we regulate privacy in our IoT platforms in the same way that it governs personal relationships. As IoT devices become increasingly linked, more data is shared across individuals, businesses, governments, and ecosystems. Technologies, sensors, machines, data, and cloud connections all rely largely on trust relationships that have been formed. With the rapid growth of additional types of IoT devices that are being introduced, it, therefore, expands privacy concerns and is difficult to develop trust with an IoT system or device without the option to regulate information privacy settings. Privacy has always been a barrier for many devices as they race for the early adoption of IoT technologies. Several Internet of Things devices or systems will continue to pose privacy threats. As a result, the main objective of this study was to examine the individual understanding of privacy and to promote information privacy protection awareness not only to IoT users but also to organizations that use IoT devices or platforms to run their day-to-day business operations. Furthermore, the objective extends to compare user knowledge and concerns about IoT privacy, as well as to identify any common attitudes and variances. However, in terms of enhancing individuals’ knowledge, an artifact was developed to educate and enhance information privacy awareness among IoT users. A pre- and postquestionnaire was generated to test and validate user knowledge regarding information privacy protection in IoT. The study was conducted using a quantitative research method. Findings indicate that IoT users’ awareness of information privacy protection turned out to be average, suggesting a need for education and awareness. Several participants stated that information privacy protection awareness is required within the community to educate, raise awareness, eliminate human error, and enable individuals to be conscious of their privacy when surfing the Internet.

The Internet of Things (IoT) devices is able to communicate with another IoT devices in heterogeneous environments. They are also able to create a network by their own using wireless capabilities without a centralized approach. This network is called wireless mobile ad hoc network (MANET). The MANET facilitate IoT devices to communicate with each other in an infrastructure less network of the Internet of Things environment. The IoT devices can dynamically join, create connection and exchange information among them. The role of cloud in this framework is to store and process the data by IoT devices. The communication Security has been raised as one of the most critical issues of cloud computing where resolving such an issue would result in a constant growth in the use and popularity of cloud. Our purpose of this study is to create a framework for providing the communication in an integrated framework of Cloud and MANET among IoT devices. Our main contribution links a new study that integrates cloud computing to the MANET and provides communication to the internet of things. This study can be used in the framework of the Internet of Things in future.

A paradigm that combines cloud computing and the Internet of Things (IoT) allows for more impressive services to be provided to users while addressing storage and computational resource issues in the IoT environments. This cloud-based IoT environment has been used in various industries, including public services, for quite some time, and has been researched in academia. However, various security issues can arise during the communication between IoT devices and cloud servers, because communication between devices occurs in open channels. Moreover, issues such as theft of a user's IoT device or extraction of key parameters from the user's device in a remote location can arise. Researchers interested in these issues have proposed lightweight mutual authentication key agreement protocols that are safe and suitable for IoT environments. Recently, a lightweight authentication scheme between IoT devices and cloud servers has been presented. However, we found out their scheme had various security vulnerabilities, vulnerable to insider, impersonation, verification table leakage, and privileged insider attacks, and did not provide users with untraceability. To address these flaws, we propose a provably secure lightweight authentication scheme. The proposed scheme uses the user's biometric information and the cloud server's secret key to prevent the exposure of key parameters. Additionally, it ensures low computational costs for providing users with real-time and fast services using only exclusive OR operations and hash functions in the IoT environments. To analyze the safety of the proposed scheme, we use informal security analysis, Burrows-Abadi-Needham (BAN) logic and a Real-or-Random (RoR) model. The analysis results confirm that our scheme is secure against insider attacks, impersonation attacks, stolen verifier attacks, and so on; furthermore, it provides additional security elements. Simultaneously, it has been verified to possess enhanced communication costs, and total bit size has been shortened to 3776 bits, which is improved by almost 6% compared to Wu et al.'s scheme. Therefore, we demonstrate that the proposed scheme is suitable for cloud-based IoT environments.

The Internet of Things (IoT) has witnessed remarkable growth, leading to the emergence of numerous applications and services. However, energy efficiency remains a critical concern in IoT networks due to the resource-constrained nature of many IoT devices. Energy-efficient routing protocols play a pivotal role in mitigating this challenge, optimizing energy consumption, and extending the operational lifetime of IoT deployments. This survey paper aims to provide a holistic understanding of the state-of-the-art approaches, their characteristics, strengths, limitations, and performance metrics. The survey encompasses a wide range of energy-efficient routing protocols proposed in the literature, including traditional routing protocols adapted for IoT scenarios and protocols specifically tailored for energy optimization. We discuss the impact of different network characteristics on the performance of energy-efficient routing protocols, such as network size, node density, mobility, and heterogeneity. Through this systematic survey, we aim to provide researchers, engineers, and practitioners with a comprehensive overview of energy-efficient routing protocols for IoT networks. The survey findings can serve as a valuable reference for protocol selection, performance evaluation, and the development of novel energy-efficient routing strategies in future IoT deployments.

ABSTRACTIn recent years, the emerging development of Internet of things (IoT) has created new opportunities for IoT service provider, device manufacturer and customer (end user). In agriculture, employing IoT can help reducing manpower as well as standardizing agricultural processes, thus increasing the benefit for customer who does agricultural business. Beside the opportunities, there are also issues while doing maintenance for an agricultural IoT system. One of them is how to automate the process to detect faults of IoT devices in a large deployment area. While previous studies focus on investigating algorithms as well as theoretical model to detect faults for specific IoT devices, automatically expanding of IoT management process for detecting faults of sensor/actuator has not been investigated yet. To achieve this, we should be able to deal with the relationship between IoT device manufacturer, service provider and customer. In this study, we conceptualize the knowledge of IoT devices, management process and fault detection requirement. To realize this model, we introduce a runtime system to expand the IoT management process for detecting sensor/actuator faults which is able to provide the above features. We do several experiments to show the effectiveness and usefulness of the proposed solution.

With the rapid development of the Internet of Things (IoT) and communication technology, deep neural network (DNN) applications, such as medical imaging, speech transcription, handwritten text recognition, have been widely used in IoT devices. However, due to resource constraints on these devices, e.g., limited memory capacity, weak computing capacity, and low battery capacity, IoT devices cannot support complicated DNN operation effectively and, thus, fail to fulfill the requirements of Quality of Service of mobile users. One promising approach is to migrate the DNN model to a remote cloud server to reduce the computing burden on IoT devices. Unfortunately, it still suffers from high delay and low bandwidth when communicating with cloud servers. Although the transmission delay of the edge server is low, its computing capacity lacks scalability and elasticity.To make matters worse, in the real world, the wireless connection between IoT devices and the cloud is intermittent, which can cause offloading failures during large-scale DNN data transmission. In this article, we describe a DNN model migration framework to overcome the abovementioned challenges, which consists of three parts: DNN model preprocessing, partition-offloading plan, and partition-uploading plan. Accordingly, we introduce the operation of the DNN migration and the available methods for each part. In addition, we improve the DNN partition-uploading plan in a multiuser edge-cloud collaborative computing environment. Finally, we highlight the important challenges of achieving more efficient DNN migration and point out the unresolved issues of DNN migration, which may shed light on future research directions.

Research Article| March 01, 2016 The Internet of Geophysical Things: Raspberry Pi Enhanced REF TEK (RaPiER) System Integration and Evaluation Frank Sepulveda; Frank Sepulveda aDepartment of Geology, Baylor University, One Bear Place #97354, Waco, Texas 76798 U.S.A.frank_sepulveda@baylor.edu Search for other works by this author on: GSW Google Scholar Jay Pulliam Jay Pulliam aDepartment of Geology, Baylor University, One Bear Place #97354, Waco, Texas 76798 U.S.A.frank_sepulveda@baylor.edu Search for other works by this author on: GSW Google Scholar Author and Article Information Frank Sepulveda aDepartment of Geology, Baylor University, One Bear Place #97354, Waco, Texas 76798 U.S.A.frank_sepulveda@baylor.edu Jay Pulliam aDepartment of Geology, Baylor University, One Bear Place #97354, Waco, Texas 76798 U.S.A.frank_sepulveda@baylor.edu Publisher: Seismological Society of America First Online: 14 Jul 2017 Online Issn: 1938-2057 Print Issn: 0895-0695 © 2016 by the Seismological Society of America Seismological Research Letters (2016) 87 (2A): 345–357. https://doi.org/10.1785/0220150234 Article history First Online: 14 Jul 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Frank Sepulveda, Jay Pulliam; The Internet of Geophysical Things: Raspberry Pi Enhanced REF TEK (RaPiER) System Integration and Evaluation. Seismological Research Letters 2016;; 87 (2A): 345–357. doi: https://doi.org/10.1785/0220150234 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietySeismological Research Letters Search Advanced Search ABSTRACT The proliferation of commercial Internet of Things (IoT) devices is raising consumers’ awareness of the benefits of enhancing everyday objects with the ability to communicate, sense, and process information. Commercial‐off‐the‐shelf (COTS) versions of the embedded technologies responsible for the rise of the IoT are easy‐to‐use, inexpensive, and relatively powerful. IoT Makers, technological do‐it‐yourself enthusiasts, utilize these technologies and the IoT ecosystem to create IoT devices that range from casual hobbyist to entrepreneurial in nature.In an effort to develop a “no‐engineer‐needed” Internet of Geophysical Things (IoGT) device, we integrated a COTS embedded computer with a geoscience‐related COTS data acquisition system (DAS). Using skills common to geoscientists, we integrated the Raspberry Pi System‐On‐Chip with the REF TEK (a Trimble brand) 130‐01 DAS. This Raspberry Pi enhanced REF TEK (RaPiER) provides IoGT Makers a platform for the development of geoscientific sensor node or network enhancements. IoGT Makers can use the RaPiER to tinker with IoT capabilities while simultaneously acquiring research‐quality data. Geoscientific (i.e., seismic) application areas that may benefit from RaPiER, particularly RaPiER nodal processing, include earthquake and engineering seismology.In this article, we discuss the emerging technologies that allow IoGT Makers to build their own IoGT device. We review our selection of the Raspberry Pi and REF TEK 130‐01 for IoGT device integration. We provide a RaPiER system integration guide and REF TEK interface software compiled for the Raspberry Pi ( available in the electronic supplement to this article). We present methods to expand RaPiER capabilities using the Raspberry Pi’s ecosystem. Last, we discuss our evaluation of RaPiER’s performance and its suitability for realistic field deployments. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

Internet of Things (IoT) has gained huge popularity through its rapid advancements and wide applicability in real world applications that have transformed our lives. Communication plays an integral role in connecting IoT devices. For effective communication in IoT, the protocols that offer lightweight, secure and reliable communication without compromising the computational and energy limitations, of the employed constrained IoT devices are the need of hour. Literature reveals certain protocols such as CoAP, MQTT, XMPP, RESTFUL Services, 6LoWPAN, RPL etc, that can be deployed for carrying communication at different layers. This paper insight the various IoT protocols applied at different layers of IoT protocol suite and analyze the efficacy and reliability of these protocols on the basis of energy efficiency, security and lightweight nature of protocols.

Internet of Things (IoT) is an emerging technology that consists of tiny sensors embedded with IoT devices used in e-Health, smart cities and assisted living. IoT devices are equipped with constrained power, memory, and computing capabilities, which creates new security challenges. By integrating sensors and wireless technologies, this cutting-edge technology automates numerous routine tasks in different domains. The main goal of advancing IoT in the existing healthcare system is to automate the monitoring of hospitals and patients’ health by spreading goodwill toward the IoT vision. IoT has gained popularity on practically all platforms that are available. This paper presents a remote patient health monitoring and diagnosis system that uses Message Queuing Telemetry Transport protocol (MQTT) and Internet of Things (IoT) devices with one time pad cryptography. The proposed plan offers end-to-end data secrecy for an IoT system using MQTT that enables e-health and mobility. Patients’ movements inside nursing homes and healthcare facilities are also managed safely without the need for periodic reconfigurations. Prior to communicating through the MQTT protocol, this secure crypto scheme encrypts the message on both the publisher and subscriber ends. According to the results, the proposed scheme is more efficient than delegation-based architecture in terms of security and lightweight communication. The proposed system established communication between patients and medical experts using IoT technologies to alleviate the hospital strain caused by congestion in medical treatment and enable an expressway of medical responses. According to our results the proposed scheme has low computational overhead compared to other solutions that use conventional encryption to guarantee robust protection against most of the IoT security attacks.