scholarly journals A Semantic Model for Interchangeable Microservices in Cloud Continuum Computing

Information ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 40
Author(s):  
Salman Taherizadeh ◽  
Dimitris Apostolou ◽  
Yiannis Verginadis ◽  
Marko Grobelnik ◽  
Gregoris Mentzas
Keyword(s):  
Fog Computing ◽  
Geographic Location ◽  
Dynamic Environments ◽  
Semantic Model ◽  
Data Interoperability ◽  
Proposed Model ◽  
Open Standards ◽  
Iot Devices ◽  
Cloud Applications ◽  
Computing Models

The rapid growth of new computing models that exploit the cloud continuum has a big impact on the adoption of microservices, especially in dynamic environments where the amount of workload varies over time or when Internet of Things (IoT) devices dynamically change their geographic location. In order to exploit the true potential of cloud continuum computing applications, it is essential to use a comprehensive set of various intricate technologies together. This complex blend of technologies currently raises data interoperability problems in such modern computing frameworks. Therefore, a semantic model is required to unambiguously specify notions of various concepts employed in cloud applications. The goal of the present paper is therefore twofold: (i) offering a new model, which allows an easier understanding of microservices within adaptive fog computing frameworks, and (ii) presenting the latest open standards and tools which are now widely used to implement each class defined in our proposed model.

FoT-Rules: A Semantic Rule-based Approach for Smart Spaces Through Fog of Things

2021 ◽  
Vol 15 (01) ◽  
pp. 23-55
Author(s):  
Cleber Santana ◽  
Ernando Batista ◽  
Brenno Mello ◽  
Cassio Prazeres
Keyword(s):  
Fog Computing ◽  
The Internet ◽  
Semantic Rule ◽  
Semantic Model ◽  
Smart Spaces ◽  
Rule Based ◽  
Technical Details ◽  
Iot Devices ◽  
Rule Based Approach ◽  
The Internet Of Things

Through the Internet of Things (IoT), Smart Spaces will enable environments to adapt according to users’ needs by using smart and connected objects. However, to turn the IoT view into a reality, the users should know about technical details of such objects, which is not a trivial task for most ordinary users. Therefore, this paper presents FoT-Rules, an approach for the construction of semantic rules aiming to create Smart Spaces through Fog of Things, which is a paradigm for Fog Computing in the IoT. FoT-Rules is designed to enable ordinary users to create and execute semantic rules in the Event-Condition-Action standard (ECA) and to take actions at the edge of the network. In this work, we present a scenario where the user can create semantic rules in the ECA standard and, in order to execute these rules at the network edge, FoT-Rules provides the following functionalities: creation of semantic rules; obtaining of the semantic models that contains information related to IoT devices; execution of a semantic reasoner over the semantic model according to the rule created by the user; a semantic observer that is responsible for observing changes in IoT devices; and in case the rule created by the user is activated, an action is taken for an IoT device. Finally, we performed four types of evaluations on our FoT-Rules approach: reliability, efficiency, scalability and usability.

scholarly journals Fog Cloud Model Based Healthcare IoT

2020 ◽  
Vol 8 (6) ◽  
pp. 4114-4117
Keyword(s):  
Social Insurance ◽  
Cloud Model ◽  
Fog Computing ◽  
Cloud Service ◽  
Health Monitoring System ◽  
Capacity Limit ◽  
Proposed Model ◽  
Cloud Servers ◽  
Cloud Applications ◽  
The Impact

Fog Computing (FC) is an advancing figuring innovation that works during a conveyed domain. One of the hindrances with cloud applications such as the health monitoring system is latency. Fog Computing is an incredible way to diminish the processing time or latency. Mist processing is an answer for the latency since it gives calculation, stockpiling, and systems administration asset for IoT, closer to things and clients. One among the promising preferences of mist is lessening administration delay for client applications, while cloud furnishes broad calculation and capacity limit with a superior inactivity. In this manner it's important to realize the transaction between mist processing and cloud, and to gauge the impact of Fog Computing on the IoT administration deferral and QoS. FC means to bring distributed computing highlights on the precarious edge of edge gadgets. The methodology is anticipated to fulfill the base inertness necessity for social insurance Internet-of-Things (IoT) gadgets. Social insurance IoT gadgets produce different volumes of human services information. This gigsantic volume of information prompts high information traffic that causes organize clog and high idleness. an ascent in full circle time delay because of huge information transmission and tremendous bounce tallies among IoTs and cloud servers render social insurance information negligible and deficient for end-clients. The proposed model, which is a fog cloud information model that propounds healthcare as a cloud service, effectively manipulates the data that comes from the user requests.

scholarly journals IMSC-EIoTD: Identity Management and Secure Communication for Edge IoT Devices

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6546
Author(s):  
Kazi Masum Sadique ◽  
Rahim Rahmani ◽  
Paul Johannesson
Keyword(s):  
Secure Communication ◽  
Identity Management ◽  
Security Protocols ◽  
Spin Model ◽  
The Internet ◽  
Human Society ◽  
Proposed Model ◽  
Authentication And Authorization ◽  
Quality Of Living ◽  
Iot Devices

The Internet of things (IoT) will accommodate several billions of devices to the Internet to enhance human society as well as to improve the quality of living. A huge number of sensors, actuators, gateways, servers, and related end-user applications will be connected to the Internet. All these entities require identities to communicate with each other. The communicating devices may have mobility and currently, the only main identity solution is IP based identity management which is not suitable for the authentication and authorization of the heterogeneous IoT devices. Sometimes devices and applications need to communicate in real-time to make decisions within very short times. Most of the recently proposed solutions for identity management are cloud-based. Those cloud-based identity management solutions are not feasible for heterogeneous IoT devices. In this paper, we have proposed an edge-fog based decentralized identity management and authentication solution for IoT devices (IoTD) and edge IoT gateways (EIoTG). We have also presented a secure communication protocol for communication between edge IoT devices and edge IoT gateways. The proposed security protocols are verified using Scyther formal verification tool, which is a popular tool for automated verification of security protocols. The proposed model is specified using the PROMELA language. SPIN model checker is used to confirm the specification of the proposed model. The results show different message flows without any error.

Proposed Back Propagation Deep Neural Network for Intrusion Detection in Internet of Things Fog Computing

2021 ◽  
Vol 9 (4) ◽  
pp. 464-469
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Intrusion Detection ◽  
Fog Computing ◽  
Denial Of Service ◽  
Back Propagation ◽  
Security And Privacy ◽  
Brute Force ◽  
Iot Platform ◽  
Proposed Model

Internet of things (IoT) is an emerging concept which aims to connect billions of devices with each other anytime regardless of their location. Sadly, these IoT devices do not have enough computing resources to process huge amount of data. Therefore, Cloud computing is relied on to provide these resources. However, cloud computing based architecture fails in applications that demand very low and predictable latency, therefore the need for fog computing which is a new paradigm that is regarded as an extension of cloud computing to provide services between end users and the cloud user. Unfortunately, Fog-IoT is confronted with various security and privacy risks and prone to several cyberattacks which is a serious challenge. The purpose of this work is to present security and privacy threats towards Fog-IoT platform and discuss the security and privacy requirements in fog computing. We then proceed to propose an Intrusion Detection System (IDS) model using Standard Deep Neural Network's Back Propagation algorithm (BPDNN) to mitigate intrusions that attack Fog-IoT platform. The experimental Dataset for the proposed model is obtained from the Canadian Institute for Cybersecurity 2017 Dataset. Each instance of the attack in the dataset is separated into separate files, which are DoS (Denial of Service), DDoS (Distributed Denial of Service), Web Attack, Brute Force FTP, Brute Force SSH, Heartbleed, Infiltration and Botnet (Bot Network) Attack. The proposed model is trained using a 3-layer BP-DNN

Survey on DDoS Attacks and Defense Mechanisms in Cloud and Fog Computing

2018 ◽  
Vol 10 (3) ◽  
pp. 61-83 ◽  
Author(s):  
Deepali Chaudhary ◽  
Kriti Bhushan ◽  
B.B. Gupta
Keyword(s):  
Cloud Computing ◽  
Defense Mechanisms ◽  
Low Cost ◽  
Fog Computing ◽  
Smart Devices ◽  
Cloud Environment ◽  
Security Issue ◽  
Process Data ◽  
Ddos Attack ◽  
Iot Devices

This article describes how cloud computing has emerged as a strong competitor against traditional IT platforms by offering low-cost and “pay-as-you-go” computing potential and on-demand provisioning of services. Governments, as well as organizations, have migrated their entire or most of the IT infrastructure to the cloud. With the emergence of IoT devices and big data, the amount of data forwarded to the cloud has increased to a huge extent. Therefore, the paradigm of cloud computing is no longer sufficient. Furthermore, with the growth of demand for IoT solutions in organizations, it has become essential to process data quickly, substantially and on-site. Hence, Fog computing is introduced to overcome these drawbacks of cloud computing by bringing intelligence to the edge of the network using smart devices. One major security issue related to the cloud is the DDoS attack. This article discusses in detail about the DDoS attack, cloud computing, fog computing, how DDoS affect cloud environment and how fog computing can be used in a cloud environment to solve a variety of problems.

scholarly journals Traffic flow features as metrics (TFFM): detection of application layer level DDOS attack scope of IOT traffic flows

2018 ◽  
Vol 7 (2.7) ◽  
pp. 203 ◽  
Author(s):  
Kalathiripi Rambabu ◽  
N Venkatram
Keyword(s):  
Traffic Flow ◽  
Traffic Flows ◽  
Application Layer ◽  
Continuous Growth ◽  
Loosely Coupled ◽  
Ddos Attack ◽  
Proposed Model ◽  
Flow Features ◽  
Target Network ◽  
Iot Devices

The phenomenal and continuous growth of diversified IOT (Internet of Things) dependent networks has open for security and connectivity challenges. This is due to the nature of IOT devices, loosely coupled behavior of internetworking, and heterogenic structure of the networks.  These factors are highly vulnerable to traffic flow based DDOS (distributed-denial of services) attacks. The botnets such as “mirae” noticed in recent past exploits the IoT devises and tune them to flood the traffic flow such that the target network exhaust to response to benevolent requests. Hence the contribution of this manuscript proposed a novel learning-based model that learns from the traffic flow features defined to distinguish the DDOS attack prone traffic flows and benevolent traffic flows. The performance analysis was done empirically by using the synthesized traffic flows that are high in volume and source of attacks. The values obtained for statistical metrics are evincing the significance and robustness of the proposed model

scholarly journals A Hybrid Optimized LSTM Models for Human Activity Recognition with IOT Devices

2021 ◽  
pp. 182-189
Author(s):  
S. Arokiaraj ◽  
Dr. N. Viswanathan
Keyword(s):  
Deep Learning ◽  
Internet Of Things ◽  
Short Term Memory ◽  
The Other ◽  
Learning Models ◽  
Computational Overhead ◽  
Temporal Features ◽  
Human Movements ◽  
Proposed Model ◽  
Iot Devices

With the advent of Internet of things(IoT),HA (HA) recognition has contributed the more application in health care in terms of diagnosis and Clinical process. These devices must be aware of human movements to provide better aid in the clinical applications as well as user’s daily activity.Also , In addition to machine and deep learning algorithms, HA recognition systems has significantly improved in terms of high accurate recognition. However, the most of the existing models designed needs improvisation in terms of accuracy and computational overhead. In this research paper, we proposed a BAT optimized Long Short term Memory (BAT-LSTM) for an effective recognition of human activities using real time IoT systems. The data are collected by implanting the Internet of things) devices invasively. Then, proposed BAT-LSTM is deployed to extract the temporal features which are then used for classification to HA. Nearly 10,0000 dataset were collected and used for evaluating the proposed model. For the validation of proposed framework, accuracy, precision, recall, specificity and F1-score parameters are chosen and comparison is done with the other state-of-art deep learning models. The finding shows the proposed model outperforms the other learning models and finds its suitability for the HA recognition.

scholarly journals A Containerized Approach for Allocating Distributed Stream Queries to Fog Nodes

2021 ◽  
Author(s):  
Hamed Hasibi ◽  
Saeed Sedighian Kashi
Keyword(s):  
Fog Computing ◽  
Stream Processing ◽  
Stream Data ◽  
Process Data ◽  
Stream Query Processing ◽  
Tremendous Amount ◽  
Stream Processing Engines ◽  
Iot Devices ◽  
Distributed Stream Processing

Fog computing brings cloud capabilities closer to the Internet of Things (IoT) devices. IoT devices generate a tremendous amount of stream data towards the cloud via hierarchical fog nodes. To process data streams, many Stream Processing Engines (SPEs) have been developed. Without the fog layer, the stream query processing executes on the cloud, which forwards much traffic toward the cloud. When a hierarchical fog layer is available, a complex query can be divided into simple queries to run on fog nodes by using distributed stream processing. In this paper, we propose an approach to assign stream queries to fog nodes using container technology. We name this approach Stream Queries Placement in Fog (SQPF). Our goal is to minimize end-to-end delay to achieve a better quality of service. At first, in the emulation step, we make docker container instances from SPEs and evaluate their processing delay and throughput under different resource configurations and queries with varying input rates. Then in the placement step, we assign queries among fog nodes by using a genetic algorithm. The practical approach used in SQPF achieves a near-the-best assignment based on the lowest application deadline in real scenarios, and evaluation results are evidence of this goal.

scholarly journals Blockchain-Based Security Model for LoRaWAN Firmware Updates

2022 ◽  
Vol 11 (1) ◽  
pp. 5
Author(s):  
Njabulo Sakhile Mtetwa ◽  
Paul Tarwireyi ◽  
Cecilia Nombuso Sibeko ◽  
Adnan Abu-Mahfouz ◽  
Matthew Adigun
Keyword(s):  
Use Cases ◽  
Smart Devices ◽  
Area Network ◽  
Sensitive Information ◽  
Security Model ◽  
Functional Requirements ◽  
Wide Area Network ◽  
Proposed Model ◽  
Attack Surface ◽  
Iot Devices

The Internet of Things (IoT) is changing the way consumers, businesses, and governments interact with the physical and cyber worlds. More often than not, IoT devices are designed for specific functional requirements or use cases without paying too much attention to security. Consequently, attackers usually compromise IoT devices with lax security to retrieve sensitive information such as encryption keys, user passwords, and sensitive URLs. Moreover, expanding IoT use cases and the exponential growth in connected smart devices significantly widen the attack surface. Despite efforts to deal with security problems, the security of IoT devices and the privacy of the data they collect and process are still areas of concern in research. Whenever vulnerabilities are discovered, device manufacturers are expected to release patches or new firmware to fix the vulnerabilities. There is a need to prioritize firmware attacks, because they enable the most high-impact threats that go beyond what is possible with traditional attacks. In IoT, delivering and deploying new firmware securely to affected devices remains a challenge. This study aims to develop a security model that employs Blockchain and the InterPlanentary File System (IPFS) to secure firmware transmission over a low data rate, constrained Long-Range Wide Area Network (LoRaWAN). The proposed security model ensures integrity, confidentiality, availability, and authentication and focuses on resource-constrained low-powered devices. To demonstrate the utility and applicability of the proposed model, a proof of concept was implemented and evaluated using low-powered devices. The experimental results show that the proposed model is feasible for constrained and low-powered LoRaWAN devices.

scholarly journals Design a blockchain-based middleware layer in the Internet of Things Architecture

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Tanweer Alam
Keyword(s):  
Internet Of Things ◽  
Fog Computing ◽  
Smart Devices ◽  
The Internet ◽  
Novel Approach ◽  
Generation Computing ◽  
Critical Issues ◽  
Iot Devices ◽  
The Internet Of Things

In next-generation computing, the role of cloud, internet and smart devices will be capacious. Nowadays we all are familiar with the word smart. This word is used a number of times in our daily life. The Internet of Things (IoT) will produce remarkable different kinds of information from different resources. It can store big data in the cloud. The fog computing acts as an interface between cloud and IoT. The extension of fog in this framework works on physical things under IoT. The IoT devices are called fog nodes, they can have accessed anywhere within the range of the network. The blockchain is a novel approach to record the transactions in a sequence securely. Developing a new blockchains based middleware framework in the architecture of the Internet of Things is one of the critical issues of wireless networking where resolving such an issue would result in constant growth in the use and popularity of IoT. The proposed research creates a framework for providing the middleware framework in the internet of smart devices network for the internet of things using blockchains technology. Our main contribution links a new study that integrates blockchains to the Internet of things and provides communication security to the internet of smart devices.

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