Development and application of low-latency edge IoT agent device for ubiquitous power Internet of Things

2021 ◽  
Author(s):  
Ben Wang ◽  
Rui She ◽  
Qinghai Ou ◽  
Ningchi Zhang ◽  
Yanru Wang ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Low Latency

scholarly journals Software Architecture of a Fog Computing Node for Industrial Internet of Things

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3715
Author(s):  
Ioan Ungurean ◽  
Nicoleta Cristina Gaitan
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Development Process ◽  
Fog Computing ◽  
Low Latency ◽  
Practical Implementation ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Starting Point ◽  
Hard Real Time

In the design and development process of fog computing solutions for the Industrial Internet of Things (IIoT), we need to take into consideration the characteristics of the industrial environment that must be met. These include low latency, predictability, response time, and operating with hard real-time compiling. A starting point may be the reference fog architecture released by the OpenFog Consortium (now part of the Industrial Internet Consortium), but it has a high abstraction level and does not define how to integrate the fieldbuses and devices into the fog system. Therefore, the biggest challenges in the design and implementation of fog solutions for IIoT is the diversity of fieldbuses and devices used in the industrial field and ensuring compliance with all constraints in terms of real-time compiling, low latency, and predictability. Thus, this paper proposes a solution for a fog node that addresses these issues and integrates industrial fieldbuses. For practical implementation, there are specialized systems on chips (SoCs) that provides support for real-time communication with the fieldbuses through specialized coprocessors and peripherals. In this paper, we describe the implementation of the fog node on a system based on Xilinx Zynq UltraScale+ MPSoC ZU3EG A484 SoC.

scholarly journals Zero-Wire

2021 ◽  
Vol 25 (1) ◽  
pp. 34-38
Author(s):  
Jonathan Oostvogels ◽  
Fan Yang ◽  
Sam Michiels ◽  
Wouter Joosen ◽  
Danny Hughes
Keyword(s):  
Wireless Networks ◽  
Internet Of Things ◽  
Wireless Networking ◽  
The Internet ◽  
Low Latency ◽  
Real Time Control ◽  
Time Control ◽  
Performance Guarantees ◽  
Delay Sensitive ◽  
The Internet Of Things

Latency-sensitive applications for the Internet of Things (IoT) often require performance guarantees that contemporary wireless networks fail to offer. Application scenarios involving real-time control of industrial machinery, robotics, or delay-sensitive actuation therefore typically still rely on cables: today's wireless networks cannot deliver messages in a sufficiently small and predictable amount of time. Drop-in wireless replacements for these cabled systems would nevertheless provide great benefit by eliminating the high cost and complexity associated with running cables in harsh industrial environments [1]. The symbolsynchronous bus, introduced in this article and embodied in a platform called Zero-Wire, is a novel wireless networking paradigm that addresses this gap. Using concurrent optical transmissions, it strives to bring low-latency deterministic networking to the wireless IoT.

scholarly journals A Privacy-Preserving Message Forwarding Framework with key caching for low latency

2019 ◽  
Vol 8 (12) ◽  
pp. 886-895
Keyword(s):  
Internet Of Things ◽  
Privacy Preserving ◽  
Low Latency ◽  
Assessment Procedure ◽  
Communication Effectiveness ◽  
Extrapolation Procedure ◽  
Transmission Process ◽  
Cloud Server ◽  
Conventional Methods

For exchanging messages over opportunistic exchanges in cloud calculating-empowered Internet of Things (IoT), opportunistic Cloud of Things (CoT) is encouraging for customers by means of an emergent conveying policy. In recent times, for predicting upcoming interactions by the determination of enlightening message promoting effectiveness as well as system quantity, several informally-awake structures have been placed onward, influencing consumers’ communal features as well as interaction account. Nevertheless, in the extrapolation procedure as well as communication phase of unprincipled CoT distinct secrecy remains commonly ignored. Towards assuring distinct secrecy as well as improving communication effectiveness, in this broadsheet, we develop a secrecy preservative communication promoting context aimed at unprincipled CoT. For improving transmission effectiveness of incurable customers, we mainly assemble twofold-level design of a cloud server. The proposed method can efficiently safeguard distinct secrecy through incorporating a safety-centered flexibility extrapolation procedure using an overpowering assessment procedure. This paper also introduces data key caching to reduce the latency during the transmission process. The proposed method outperforms the conventional methods.

A Scalable Big Stream Cloud Architecture for the Internet of Things

2015 ◽  
Vol 5 (4) ◽  
pp. 26-53 ◽  
Author(s):  
Laura Belli ◽  
Simone Cirani ◽  
Luca Davoli ◽  
Gianluigi Ferrari ◽  
Lorenzo Melegari ◽  
...  
Keyword(s):  
Internet Of Things ◽  
The Internet ◽  
Low Latency ◽  
Smart Objects ◽  
Heterogeneous Devices ◽  
Cloud Architecture ◽  
Iot Applications ◽  
Processing Platform ◽  
The Internet Of Things ◽  
Constrained Devices

The Internet of Things (IoT) will consist of billions (50 billions by 2020) of interconnected heterogeneous devices denoted as “Smart Objects:” tiny, constrained devices which are going to be pervasively deployed in several contexts. To meet low-latency requirements, IoT applications must rely on specific architectures designed to handle the gigantic stream of data coming from Smart Objects. This paper propose a novel Cloud architecture for Big Stream applications that can efficiently handle data coming from Smart Objects through a Graph-based processing platform and deliver processed data to consumer applications with low latency. The authors reverse the traditional “Big Data” paradigm, where real-time constraints are not considered, and introduce the new “Big Stream” paradigm, which better fits IoT scenarios. The paper provides a performance evaluation of a practical open-source implementation of the proposed architecture. Other practical aspects, such as security considerations, and possible business oriented exploitation plans are presented.

Applying Security to a Big Stream Cloud Architecture for the Internet of Things

2020 ◽  
pp. 1260-1284
Author(s):  
Laura Belli ◽  
Simone Cirani ◽  
Luca Davoli ◽  
Gianluigi Ferrari ◽  
Lorenzo Melegari ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Large Data ◽  
The Internet ◽  
Low Latency ◽  
Stream Data ◽  
Memory Processing ◽  
Cloud Architecture ◽  
Iot Devices ◽  
The Internet Of Things

The Internet of Things (IoT) is expected to interconnect billions (around 50 by 2020) of heterogeneous sensor/actuator-equipped devices denoted as “Smart Objects” (SOs), characterized by constrained resources in terms of memory, processing, and communication reliability. Several IoT applications have real-time and low-latency requirements and must rely on architectures specifically designed to manage gigantic streams of information (in terms of number of data sources and transmission data rate). We refer to “Big Stream” as the paradigm which best fits the selected IoT scenario, in contrast to the traditional “Big Data” concept, which does not consider real-time constraints. Moreover, there are many security concerns related to IoT devices and to the Cloud. In this paper, we analyze security aspects in a novel Cloud architecture for Big Stream applications, which efficiently handles Big Stream data through a Graph-based platform and delivers processed data to consumers, with low latency. The authors detail each module defined in the system architecture, describing all refinements required to make the platform able to secure large data streams. An experimentation is also conducted in order to evaluate the performance of the proposed architecture when integrating security mechanisms.

Fog Computing to Serve the Internet of Things Applications

2019 ◽  
Vol 2 (2) ◽  
pp. 44-56 ◽  
Author(s):  
Amjad Hudaib ◽  
Layla Albdour
Keyword(s):  
Internet Of Things ◽  
New Technologies ◽  
Performance Metrics ◽  
Fog Computing ◽  
High Mobility ◽  
Low Latency ◽  
Performance Measurements ◽  
Sensors And Actuators ◽  
Consumption Cost ◽  
Latency Response

Due to centralized nature for cloud computing and some other reasons, high mobility cannot be supported and low latency requirements for some applications such as Internet of Things (IoT) that require real time and mobility support. To satisfy such requirements new technologies, fog computing is a good solution, where we use edges of network for service provisioning instead of far datacenters allocated in clouds. Low latency response is the most attractive property for fog computing, which is very suitable for IoT multi-billion devices, sensors and actuators generates huge amount of data that need processing and analysis for smart decision generation. The main objective of this article is to show the super ability of fog computing over cloud-only computing. The authors present a patient monitoring system as a case study for simulation; they evaluated the performance of the system using: latency, network usage, power consumption, cost of execution and simulation execution time performance metrics. The results show that the Fog computing is superior over Cloud-only paradigm in all performance measurements.

Speeding Up the Internet of Things: LEAIoT: A Lightweight Encryption Algorithm Toward Low-Latency Communication for the Internet of Things

2018 ◽  
Vol 7 (6) ◽  
pp. 31-37 ◽  
Author(s):  
Muhammad Asif Habib ◽  
Mudassar Ahmad ◽  
Sohail Jabbar ◽  
Syed Hassan Ahmed ◽  
Joel J.P.C. Rodrigues
Keyword(s):  
Internet Of Things ◽  
Encryption Algorithm ◽  
The Internet ◽  
Low Latency ◽  
The Internet Of Things ◽  
Lightweight Encryption

scholarly journals Evolutionary Detection Accuracy of Secret Data in Audio Steganography for Securing 5G-Enabled Internet of Things

Symmetry ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 2071
Author(s):  
Mohammed J. Alhaddad ◽  
Monagi H. Alkinani ◽  
Mohammed Salem Atoum ◽  
Alaa Abdulsalm Alarood
Keyword(s):  
Internet Of Things ◽  
Sampling Rate ◽  
Sound Quality ◽  
Low Latency ◽  
Detection Accuracy ◽  
Bit Rate ◽  
Secret Data ◽  
Sensitive Data ◽  
Audio Steganography ◽  
Wireless Links

With the unprecedented growing demand for communication between Internet of Things (IoT) devices, the upcoming 5G and 6G technologies will pave the path to a widespread use of ultra-reliable low-latency applications in such networks. However, with most of the sensitive data being transmitted over wireless links, security, privacy and trust management are emerging as big challenges to handle. IoT applications vary, from self-driving vehicles, drone deliveries, online shopping, IoT smart cities, e-healthcare and robotic assisted surgery, with many applications focused on Voice over IP (VoIP) and require securing data from potential eavesdroppers and attackers. One well-known technique is a hidden exchange of secret data between the devices for which security can be achieved with audio steganography. Audio steganography is an efficient, reliable and low-latency mechanism used for securely communicating sensitive data over wireless links. MPEG-1 Audio Layer 3’s (MP3’s) bit rate falls within the acceptable sound quality required for audio. Its low level of noise distortion does not affect its sound quality, which makes it a good carrier medium for steganography and watermarking. The strength of any embedding technique lies with its undetectability measure. Although there are many detection techniques available for both steganography and watermarking, the detection accuracy of secret data has been proven erroneous. It has yet to be confirmed whether different bit rates or a constant sampling rate for embedding eases detection. The accuracy of detecting hidden information in MP3 files drops with the influence of the compression rate or increases. This drop or increase is caused by either the increase in file track size, the sampling rate or the bit rate. This paper presents an experimental study that evaluates the detection accuracy of the secret data embedded in MP3. Training data were used for the embedding and detection of text messages in MP3 files. Several iterations were evaluated. The experimental results show that the used approach was effective in detecting the embedded data in MP3 files. An accuracy rate of 97.92% was recorded when detecting secret data in MP3 files under 128-kbps compression. This result outperformed the previous research work.

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