Large Data Exchange Based on the Internet of Things

2020 ◽  
Author(s):  
Guest Editor Liutian Ye
Keyword(s):  
Internet Of Things ◽  
Data Exchange ◽  
Large Data ◽  
The Internet ◽  
The Internet Of Things

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.

The Study on the Methodology of Transactionevent in the Ale of Rfid Networks

2014 ◽  
Vol 556-562 ◽  
pp. 5321-5327
Author(s):  
Hui Qun Zhao ◽  
Hai Gang Yang
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Large Data ◽  
The Internet ◽  
Prototype System ◽  
Processing Efficiency ◽  
Long Period ◽  
Rfid Networks ◽  
Integrated Program ◽  
The Internet Of Things

TransactionEvent is one of the five events defined in EPCGlobal standard. As TransactionEvent lasts for a long period and processes large data, it has a higher demand of real-time. The process of the TransactionEvent in the Internet of Things is complex. In order to overcome these disadvantages, this paper proposes a non-integrated program. This program will ensure the TransactionEvent processing efficiency, reliability and real time. In the end of this paper, the article will implement a prototype system of a commercial IoT to verify this method.

scholarly journals Security Issues and Challenges in IOT: a Comprehensive Study

2018 ◽  
Vol 7 (2.32) ◽  
pp. 298 ◽  
Author(s):  
M Bhargavi ◽  
Dr M.Nagabhushana Rao
Keyword(s):  
Internet Of Things ◽  
Data Exchange ◽  
Denial Of Service ◽  
The Internet ◽  
Security Architecture ◽  
Iot Security ◽  
Security Issues ◽  
Continuous Support ◽  
The Internet Of Things ◽  
Comprehensive Study

The Internet of Things (IoT) is a revolutionary model, with rising wireless sensor network technology. In IoT network devices are connected and communicated with each other or with human. IoT is extremely available to security assaults. In recent years, the internet of things has a continuous support in research. In the upcoming scenario, IoT will play an important role and changes our day-to-day life, principles as well as industry models. In this paper we provide ensuring security of data exchange, IoT architecture and IoT Security architecture, applications, drawbacks of IoT. We study about various security issues, Problems, normal and Denial of service attacks in different layers, issues and research defy in IoT are also discussed.   

scholarly journals Predicting Heart Diseases from Large Scale IoT Data Using a Map-Reduce Paradigm

2020 ◽  
Vol 10 (1) ◽  
pp. 422-430
Author(s):  
Faris Mohammad Abd ◽  
Mehdi Ebady Manaa
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Internet Of Things ◽  
Heart Diseases ◽  
Large Data ◽  
Machine Learning Algorithms ◽  
Healthcare Sector ◽  
Map Reduce ◽  
The Internet ◽  
The Internet Of Things

AbstractOver the last few years, the huge amount of data represented a major obstacle to data analysis. Big data implies that the volume of data undergoes a faster progress than computational speeds, thereby demanding a larger data storage capacity. The Internet of Things (IoT) is a main source of data that is closely related to big data, as the former extends to a variety of fields such as healthcare, entertainment, and disaster control. Despite the different advantages associated with the composition of Big Data analytics and IoT, there are a number of complex difficulties and issues involved that need to be resolved and managed to ensure an accurate data analysis. Some of these solutions include the utilization of map-reduce techniques, processing, and large data scale, particularly for the relatively less time that this method requires to process large data from the Internet of Things. Machine learning algorithms of this kind are often implemented in the healthcare sector. Medical facilities need to be advanced so that more appropriate decisions can be made in terms of patient diagnosis and treatment options. In this work, two datasets have been used: the first set, used in the prediction of heart diseases, obtained an accuracy rate of 84.5 for RF and 83 for J48, whereas the second dataset is related to weather stations (automated sensors) and obtained accuracy rates of 88.5 and 86.5 for RF and J48, respectively.

scholarly journals An Improved Energy-Aware Clustering Method for The Regional Queries in The Internet of Things

2020 ◽  
Author(s):  
Arezoo Khatibi ◽  
Omid Khatibi
Keyword(s):  
Internet Of Things ◽  
Energy Efficient ◽  
Large Data ◽  
Base Station ◽  
The Internet ◽  
Heterogeneous Cluster ◽  
Energy Aware ◽  
Save Energy ◽  
Index Tree ◽  
The Internet Of Things

Abstract We will offer a method to improve energy efficient consumption for processing queries on the Internet of Things. We focused on an energy efficient hierarchical clustering index tree such that we can facilitate time-correlated region queries in the I.o.T (Internet of Things). We try to improve clustering and make a change on its proposed index tree. We try to do this by optimizing the query processing. We improve clustering to increase the accuracy of the Internet of Things and prevent the network from disconnecting. In the article that we have chosen, there is a heterogeneous cluster which means there exists a large data difference in the two ends of a cluster. Also, it often happens that the same information is sent to the base station by two overlapping clusters; therefore, we save energy by eliminating duplicated data.

scholarly journals Intelligent Algorithms of Wireless Communication for Internet of Things Service Security and Privacy Assurance

2021 ◽  
Author(s):  
Yuanguo Wang ◽  
Xiaogang Jiang ◽  
Qian Yu ◽  
Xiuling Zhang ◽  
Bailu Zhao ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Communication Networks ◽  
Data Exchange ◽  
Large Scale ◽  
Low Complexity ◽  
Internet Security ◽  
Security And Privacy ◽  
The Internet ◽  
Management Service ◽  
The Internet Of Things

Abstract Due to its huge application potential, the Internet of Things has received extensive attention from governments, academia and industry. The core concepts of the Internet of Things are perception, control, transmission and intelligence. Through technical means, the coordination of things and things, people and things, and people and people has been realized, thus forming a network based on sensor networks, the Internet, and mobile communication networks. A larger complex network system. However, restricted by the characteristics of network structure, terminal equipment, communication methods, application scenarios, etc., some security and privacy issues unique to the Internet of Things cannot be directly solved by existing Internet security technologies. Aiming at the general high complexity of existing algorithms, this article starts with the different phase-frequency characteristics of different filters, and designs a new low-complexity reduction system algorithm. According to the characteristics of the system that the filter structure can be flexibly selected, the method randomly allocates different filters to each sub-carrier and adjusts the phase of signal superimposition, thereby constructing a coordinated communication facility and management service coordination suitable for large-scale distributed IoT services. The interactive access control architecture realizes the confidentiality of data exchange between services.

scholarly journals Offline-First Sleep Assessment (OFFSA): Internet of Things Polysomnography Sleep Assessment Framework for Sleep Monitoring in Rural Environment

2019 ◽  
Vol 8 (4) ◽  
pp. 6112-6118
Keyword(s):  
Internet Of Things ◽  
Data Security ◽  
Data Exchange ◽  
Target Location ◽  
Medical Data ◽  
Patient Data ◽  
The Internet ◽  
Graphic User Interface ◽  
Sleep Assessment ◽  
The Internet Of Things

Sleep is a mandatory biological requirement for humans that require appropriate proportions and quality. The assessment method in determining the best sleep quality and the medical gold standard is to use a Polysomnography device. The advantages of the Internet of Things can significantly increase the usefulness of Polysomnography in suburban areas. The target location of this framework makes our consideration adhere to the Offline-First Internet of Things method to overcome the limitations of the internet at that location. Unfortunately, there are still problems coming from the concept of the Internet of Things itself, and the problem is in data security. So we propose a framework for Polysomnography devices that connects the Internet of Things with a focus on the security and confidentiality of patient data called Offline-First Sleep Assessment (OFFSA). We enumerate patient medical data and archive encryption to improve patient data security. The confidentiality of our patient data is achieved by encryption on every medical data exchange and is only open on the Graphic User Interface application on the device that has been registered.

scholarly journals Usages of Spark Framework with Different Machine Learning Algorithms

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Mohamed Ali Mohamed ◽  
Ibrahim Mahmoud El-henawy ◽  
Ahmad Salah
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Internet Of Things ◽  
Large Data ◽  
Machine Learning Algorithms ◽  
Smart Devices ◽  
The Internet ◽  
Learning Methods ◽  
Machine Learning Methods ◽  
The Internet Of Things

Sensors, satellites, mobile devices, social media, e-commerce, and the Internet, among others, saturate us with data. The Internet of Things, in particular, enables massive amounts of data to be generated more quickly. The Internet of Things is a term that describes the process of connecting computers, smart devices, and other data-generating equipment to a network and transmitting data. As a result, data is produced and updated on a regular basis to reflect changes in all areas and activities. As a consequence of this exponential growth of data, a new term and idea known as big data have been coined. Big data is required to illuminate the relationships between things, forecast future trends, and provide more information to decision-makers. The major problem at present, however, is how to effectively collect and evaluate massive amounts of diverse and complicated data. In some sectors or applications, machine learning models are the most frequently utilized methods for interpreting and analyzing data and obtaining important information. On their own, traditional machine learning methods are unable to successfully handle large data problems. This article gives an introduction to Spark architecture as a platform that machine learning methods may utilize to address issues regarding the design and execution of large data systems. This article focuses on three machine learning types, including regression, classification, and clustering, and how they can be applied on top of the Spark platform.

Preparation of Raspberry Pi for IoT-Enabled Applications

2018 ◽  
pp. 264-308 ◽  
Author(s):  
Manoj Devare
Keyword(s):  
Internet Of Things ◽  
Low Power ◽  
Data Exchange ◽  
Raspberry Pi ◽  
The Internet ◽  
Virtual Agents ◽  
Digital Twins ◽  
Step Procedure ◽  
Smart Factories ◽  
The Internet Of Things

This chapter shares the experiences in systematic, well-tested, and executed step-by-step procedure for the preparation of the Raspberry Pi single board computer (SBC) for the internet of things (IoT)-enabled applications. This chapter is useful for beginners and professionals working for automation of smart factories with the help of IoT and Cloud. Moreover, interesting data exchange techniques like low power wireless alternatives ZigBee, LORA, BLE, 6LowPAN, SigFox, and multi-queue telemetry transport (MQTT) are also stated. The related IoT preceding and succeeding technologies, like machine-to-machine(M2M), cyber-physical-systems (CPS), web of things (WoT), SCADA are also the part of insights. Various supporting technologies for the success of IoT like commercial and open source IoT cloud platforms, virtual agents(VA), and digital twins are also discussed.

IoT Architecture and Protocols in 5G Environment

2018 ◽  
pp. 105-130
Author(s):  
Ahmed Mahmoud Mostafa
Keyword(s):  
Internet Of Things ◽  
Data Exchange ◽  
Global Network ◽  
The Internet ◽  
Information Network ◽  
International Telecommunication Union ◽  
International Telecommunication ◽  
Physical Attributes ◽  
The Internet Of Things ◽  
Existing Data

The Internet of Things (IoT) is defined by the International Telecommunication Union (ITU) and IoT European Research Cluster (IERC) as a dynamic global network infrastructure with self-configuring capabilities based on standard and interoperable communication protocols where physical and virtual “things” have identities, physical attributes and virtual personalities, use intelligent interfaces and are seamlessly integrated into the information network. Many of the applications and use cases that drive the requirements and capabilities of 5G are about end-to-end communication between devices. This chapter describes the enabling technologies for the Internet of Things, the IoT architecture, the network and communication infrastructure for IoT, and the importance of scalability for 5G based IoT systems. Also, naming and addressing issues in IoT is presented along with an overview of the existing data exchange protocols that can be applied to IoT based systems.

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