scholarly journals SCATTER: Service Placement in Real-Time Fog-Assisted IoT Networks

2021 ◽  
Vol 10 (2) ◽  
pp. 26
Author(s):  
Fariba Khosroabadi ◽  
Faranak Fotouhi-Ghazvini ◽  
Hossein Fotouhi
Keyword(s):  
Real Time ◽  
Response Times ◽  
Fog Computing ◽  
Cloud Services ◽  
Task Mapping ◽  
Placement Problem ◽  
Computing Paradigm ◽  
Service Placement ◽  
Network Usage ◽  
Task Placement

Internet of Things (IoT) networks dependent on cloud services usually fail in supporting real-time applications as there is no response time guarantees. The fog computing paradigm has been used to alleviate this problem by executing tasks at the edge of the network, where it is possible to provide time bounds. One of the challenging topics in a fog-assisted architecture is to task placement on edge devices in order to obtain a good performance. The process of task mapping into computational devices is known as Service Placement Problem (SPP). In this paper, we present a heuristic algorithm to solve SPP, dubbed as clustering of fog devices and requirement-sensitive service first (SCATTER). We provide simulations using iFogSim toolkit and experimental evaluations using real hardware to verify the feasibility of the SCATTER algorithm by considering a smart home application. We compared the SCATTER with two existing works: edge-ward and cloud-only approaches, in terms of Quality of Service (QoS) metrics. Our experimental results have demonstrated that SCATTER approach has better performance compared with the edge-ward and cloud-only, 42.1% and 60.2% less application response times, 22% and 27.8% less network usage, 45% and 65.7% less average application loop delays, and 2.33% and 3.2% less energy consumption.

scholarly journals Fog Computing Framework for Smart City Design

2020 ◽  
Vol 14 (01) ◽  
pp. 109
Author(s):  
Mais Haj Qasem ◽  
Alaa Abu-Srhan ◽  
Hutaf Natoureah ◽  
Esra Alzaghoul
Keyword(s):  
Cloud Computing ◽  
Data Processing ◽  
Real Time ◽  
Smart City ◽  
Network Architecture ◽  
Data Exchange ◽  
Fog Computing ◽  
Computing Paradigm ◽  
Network Usage ◽  
The Cost

Fog-computing is a new network architecture and computing paradigm that uses user or near-users devices (network edge) to carry out some processing tasks. Accordingly, it extends the cloud computing with more flexibility the one found in the ubiquitous networks. A smart city based on the concept of fog-computing with flexible hierarchy is proposed in this paper. The aim of the proposed design is to overcome the limitations of the previous approaches, which depends on using various network architectures, such as cloud-computing, autonomic network architecture and ubiquitous network architecture. Accordingly, the proposed approach achieves a reduction of the latency of data processing and transmission with enabled real-time applications, distribute the processing tasks over edge devices in order to reduce the cost of data processing and allow collaborative data exchange among the applications of the smart city. The design is made up of five major layers, which can be increased or merged according to the amount of data processing and transmission in each application. The involved layers are connection layer, real-time processing layer, neighborhood linking layer, main-processing layer, data server layer. A case study of a novel smart public car parking, traveling and direction advisor is implemented using IFogSim and the results showed that reduce the delay of real-time application significantly, reduce the cost and network usage compared to the cloud-computing paradigm. Moreover, the proposed approach, although, it increases the scalability and reliability of the users’ access, it does not sacrifice much time, nor cost and network usage compared to fixed fog-computing design.

scholarly journals Goals and measures for analyzing power consumption data in manufacturing enterprises

2021 ◽  
Vol 3 (1) ◽  
pp. 65-82
Author(s):  
Sören Henning ◽  
Wilhelm Hasselbring ◽  
Heinz Burmester ◽  
Armin Möbius ◽  
Maik Wojcieszak
Keyword(s):  
Power Consumption ◽  
Real Time ◽  
Manufacturing Industry ◽  
Fog Computing ◽  
Electrical Power ◽  
Time Data ◽  
Manufacturing Enterprises ◽  
Computing Paradigm ◽  
Consumption Data ◽  
Analyzing Power

AbstractThe Internet of Things adoption in the manufacturing industry allows enterprises to monitor their electrical power consumption in real time and at machine level. In this paper, we follow up on such emerging opportunities for data acquisition and show that analyzing power consumption in manufacturing enterprises can serve a variety of purposes. In two industrial pilot cases, we discuss how analyzing power consumption data can serve the goals reporting, optimization, fault detection, and predictive maintenance. Accompanied by a literature review, we propose to implement the measures real-time data processing, multi-level monitoring, temporal aggregation, correlation, anomaly detection, forecasting, visualization, and alerting in software to tackle these goals. In a pilot implementation of a power consumption analytics platform, we show how our proposed measures can be implemented with a microservice-based architecture, stream processing techniques, and the fog computing paradigm. We provide the implementations as open source as well as a public show case allowing to reproduce and extend our research.

scholarly journals A survey on fog computing: research challenges in security and privacy issues

2018 ◽  
Vol 7 (2.7) ◽  
pp. 335 ◽  
Author(s):  
T Veerraju ◽  
Dr K. Kiran Kumar
Keyword(s):  
Fog Computing ◽  
Cloud Services ◽  
Security And Privacy ◽  
Limited Resources ◽  
Privacy And Security ◽  
Computing Paradigm ◽  
Is Security ◽  
Real Time Applications ◽  
And Storage ◽  
Privacy Issues

With the rapid advancement of Internet of Things has enabled to combine the intercommunication and interconnection between seamless networks. Cloud computing provides backend solutions and one among the most prominent technologies for the users, still cannot be solved all the problems such as latency of real time applications. However, a new computing paradigm comes in to the picture. Many of the researchers focused on this exemplar known as Fog/Edge computing, which has been planned to the extension of cloud services. Fog provides the services to the edge of the networks, which makes communication, computation and storage for end users through fog devices and for servers like controllers. We analyze the study, which aims to augment low bandwidth, latency along with the privacy and security.   The major problem in the Fog computing is security due to the limited resources. In this paper, we investigated the protection issues and confrontation of Fog and also provide countermeasures on security for different attacks. We focused the future security directions and challenges to address in fog networks.

scholarly journals Blockchain-enabled real-time SLA monitoring for cloud-hosted services

2021 ◽  
Author(s):  
Kashif Mehboob Khan ◽  
Junaid Arshad ◽  
Waheed Iqbal ◽  
Sidrah Abdullah ◽  
Hassan Zaib
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Service Providers ◽  
Response Times ◽  
Cloud Service ◽  
Service Level ◽  
Cloud Services ◽  
Blockchain Technology ◽  
Manual Processing ◽  
And Performance

AbstractCloud computing is an important technology for businesses and individual users to obtain computing resources over the Internet on-demand and flexibly. Although cloud computing has been adopted across diverse applications, the owners of time-and-performance critical applications require cloud service providers’ guarantees about their services, such as availability and response times. Service Level Agreements (SLAs) are a mechanism to communicate and enforce such guarantees typically represented as service level objectives (SLOs), and financial penalties are imposed on SLO violations. Due to delays and inaccuracies caused by manual processing, an automatic method to periodically verify SLA terms in a transparent and trustworthy manner is fundamental to effective SLA monitoring, leading to the acceptance and credibility of such service to the customers of cloud services. This paper presents a blockchain-based distributed infrastructure that leverages fundamental blockchain properties to achieve immutable and trustworthy SLA monitoring within cloud services. The paper carries out an in-depth empirical investigation for the scalability of the proposed system in order to address the challenge of transparently enforcing real-time monitoring of cloud-hosted services leveraging blockchain technology. This will enable all the stakeholders to enforce accurate execution of SLA without any imprecisions and delays by maintaining an immutable ledger publicly across blockchain network. The experimentation takes into consideration several attributes of blockchain which are critical in achieving optimum performance. The paper also investigates key characteristics of these factors and their impact to the behaviour of the system for further scaling it up under various cases for increased service utilization.

scholarly journals Fog-Based CDN Framework for Minimizing Latency of Web Services Using Fog-Based HTTP Browser

2021 ◽  
Vol 13 (12) ◽  
pp. 320
Author(s):  
Ahmed H. Ibrahim ◽  
Zaki T. Fayed ◽  
Hossam M. Faheem
Keyword(s):  
Cloud Computing ◽  
Web Services ◽  
Fog Computing ◽  
Partial Solution ◽  
Cloud Services ◽  
Network Layer ◽  
Cloud Data ◽  
Download Time ◽  
Computing Paradigm ◽  
Cloud Servers

Cloud computing has been a dominant computing paradigm for many years. It provides applications with computing, storage, and networking capabilities. Furthermore, it enhances the scalability and quality of service (QoS) of applications and offers the better utilization of resources. Recently, these advantages of cloud computing have deteriorated in quality. Cloud services have been affected in terms of latency and QoS due to the high streams of data produced by many Internet of Things (IoT) devices, smart machines, and other computing devices joining the network, which in turn affects network capabilities. Content delivery networks (CDNs) previously provided a partial solution for content retrieval, availability, and resource download time. CDNs rely on the geographic distribution of cloud servers to provide better content reachability. CDNs are perceived as a network layer near cloud data centers. Recently, CDNs began to perceive the same degradations of QoS due to the same factors. Fog computing fills the gap between cloud services and consumers by bringing cloud capabilities close to end devices. Fog computing is perceived as another network layer near end devices. The adoption of the CDN model in fog computing is a promising approach to providing better QoS and latency for cloud services. Therefore, a fog-based CDN framework capable of reducing the load time of web services was proposed in this paper. To evaluate our proposed framework and provide a complete set of tools for its use, a fog-based browser was developed. We showed that our proposed fog-based CDN framework improved the load time of web pages compared to the results attained through the use of the traditional CDN. Different experiments were conducted with a simple network topology against six websites with different content sizes along with a different number of fog nodes at different network distances. The results of these experiments show that with a fog-based CDN framework offloading autonomy, latency can be reduced by 85% and enhance the user experience of websites.

scholarly journals Data Deduplication for Efficient Storage on Cloud using Fog Computing Paradigm

2020 ◽  
Vol 9 (1) ◽  
pp. 812-815
Keyword(s):  
Cloud Computing ◽  
Data Compression ◽  
Distributed System ◽  
Fog Computing ◽  
Geographic Area ◽  
Cloud Services ◽  
Data Deduplication ◽  
Computing Paradigm ◽  
Efficient Storage ◽  
Large Geographic Area

Cloud services have taken the IT world by storm by making its services available to everyone over large geographic area. With the increasing amount of data generate every minute it has become increasing difficult to manage resources and the storage. Thus, data compression techniques like data de duplication that aims at executing the redundancy of data and forming chunks of data that can be stored on a distributed system can be proved to a logistic solution. But when it comes to cloud problems like security has always been a major issue. In order to eliminate these challenges, we need to implement a layer of fog computing they would deal with the shortcomings of cloud computing and at the same time present a filtration front before the incoming data.

Fog Computing

Fog Computing ◽  
2018 ◽  
pp. 198-207 ◽  
Author(s):  
Chintan M. Bhatt ◽  
C. K. Bhensdadia
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Real Time ◽  
Fog Computing ◽  
The Internet ◽  
Research Issues ◽  
Computing Paradigm ◽  
Time Interaction ◽  
Edge Network ◽  
The Internet Of Things

The Internet of Things could be a recent computing paradigm, defined by networks of extremely connected things – sensors, actuators and good objects – communication across networks of homes, buildings, vehicles, and even individuals whereas cloud computing could be ready to keep up with current processing and machine demands. Fog computing provides architectural resolution to deal with some of these issues by providing a layer of intermediate nodes what's referred to as an edge network [26]. These edge nodes provide interoperability, real-time interaction, and if necessary, computational to the Cloud. This paper tries to analyse different fog computing functionalities, tools and technologies and research issues.

Feedback-Based Fuzzy Resource Management in IoT-Based-Cloud

2020 ◽  
Vol 3 (1) ◽  
pp. 1-21 ◽  
Author(s):  
Basetty Mallikarjuna
Keyword(s):  
Fog Computing ◽  
High Volume ◽  
Cloud Services ◽  
Dynamic Feedback ◽  
Smart Cameras ◽  
Computing Paradigm ◽  
Qos Parameters ◽  
Speed Up ◽  
Iot Devices ◽  
Smart Home Appliances

The main aim of Internet of Things (IoT) is to get every “thing” (sensors, smart cameras, wearable devices, and smart home appliances) to connect to the internet. Henceforth to produce the high volume of data required for data processing between IoT devices, large storage and the huge number of applications to offer cloud computing as a service. The purpose of IoT-based-cloud is to manage the resources, and effective utilization of tasks in cloud. The end user applications are essential to enhance the QoS parameters. As per the QoS parameters, the service provider makes the speed up of tasks. There is a requirement for assigning responsibilities based on priority. The cloud services are increased to the network edge, and the planned model is under the Fog computing paradigm to reduce the makespan of time. The priority based fuzzy scheduling approach is brought by the dynamic feedback-based mechanism. The planned mechanism is verified with the diverse prevailing algorithms and evidenced that planned methodology is supported by effective results.

scholarly journals An Alertness-Adjustable Cloud/Fog IoT Solution for Timely Environmental Monitoring Based on Wildfire Risk Forecasting

Energies ◽  
2020 ◽  
Vol 13 (14) ◽  
pp. 3693
Author(s):  
Athanasios Tsipis ◽  
Asterios Papamichail ◽  
Ioannis Angelis ◽  
George Koufoudakis ◽  
Georgios Tsoumanis ◽  
...  
Keyword(s):  
Real Time ◽  
Network Architecture ◽  
Fog Computing ◽  
Fire Risk ◽  
Hybrid Network ◽  
Case Scenario ◽  
Wildfire Risk ◽  
Computing Paradigm ◽  
Risk Forecasting ◽  
Burning Index

Internet of Things (IoT) appliances, especially those realized through wireless sensor networks (WSNs), have been a dominant subject for heavy research in the environmental and agricultural sectors. To address the ever-increasing demands for real-time monitoring and sufficiently handle the growing volumes of raw data, the cloud/fog computing paradigm is deemed a highly promising solution. This paper presents a WSN-based IoT system that seamlessly integrates all aforementioned technologies, having at its core the cloud/fog hybrid network architecture. The system was intensively validated using a demo prototype in the Ionian University facilities, focusing on response time, an important metric of future smart applications. Further, the developed prototype is able to autonomously adjust its sensing behavior based on the criticality of the prevailing environmental conditions, regarding one of the most notable climate hazards, wildfires. Extensive experimentation verified its efficiency and reported on its alertness and highly conforming characteristics considering the use-case scenario of Corfu Island’s 2019 fire risk severity. In all presented cases, it is shown that through fog leveraging it is feasible to contrive significant delay reduction, with high precision and throughput, whilst controlling the energy consumption levels. Finally, a user-driven web interface is highlighted to accompany the system; it is capable of augmenting the data curation and visualization, and offering real-time wildfire risk forecasting based on Chandler’s burning index scoring.

scholarly journals Integration of Fog and IoT with Multiensor Data Gathering

2019 ◽  
Vol 8 (4) ◽  
pp. 11785-11787
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Fog Computing ◽  
Data Gathering ◽  
Low Latency ◽  
Computing Paradigm ◽  
City System ◽  
Computing Framework ◽  
The City

In the already existing system number of internet connected devices rapidly increase, this increased demand real-time, for the standard cloud computing framework, low latency services proving to be always a challenge. While In the proposed System, fog computing paradigm serves the demands of the latency sensitive applications in the context of IOT. The IOT is rely on cloud computing by passing information about sensor. This is a decentralized process to gather the information from each and every region of the city. System will check the energy and location of every server. Because whenever server uploads the sensor details it can degrade their energy on every time. So we have to migrate the data by allocating another server which contains the energy to send

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