scholarly journals Resource Provisioning in Fog Computing: From Theory to Practice †

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2238 ◽  
Author(s):  
José Santos ◽  
Tim Wauters ◽  
Bruno Volckaert ◽  
Filip De Turck
Keyword(s):  
Smart Cities ◽  
Fog Computing ◽  
Resource Provisioning ◽  
Theoretical Approaches ◽  
Theory To Practice ◽  
Optimization Formulation ◽  
Container Orchestration ◽  
Allocation Decisions ◽  
The Internet Of Things ◽  
Theoretical Foundations

The Internet-of-Things (IoT) and Smart Cities continue to expand at enormous rates. Centralized Cloud architectures cannot sustain the requirements imposed by IoT services. Enormous traffic demands and low latency constraints are among the strictest requirements, making cloud solutions impractical. As an answer, Fog Computing has been introduced to tackle this trend. However, only theoretical foundations have been established and the acceptance of its concepts is still in its early stages. Intelligent allocation decisions would provide proper resource provisioning in Fog environments. In this article, a Fog architecture based on Kubernetes, an open source container orchestration platform, is proposed to solve this challenge. Additionally, a network-aware scheduling approach for container-based applications in Smart City deployments has been implemented as an extension to the default scheduling mechanism available in Kubernetes. Last but not least, an optimization formulation for the IoT service problem has been validated as a container-based application in Kubernetes showing the full applicability of theoretical approaches in practical service deployments. Evaluations have been performed to compare the proposed approaches with the Kubernetes standard scheduling feature. Results show that the proposed approaches achieve reductions of 70% in terms of network latency when compared to the default scheduling mechanism.

Fog Computing and Its Role in the Internet of Things

2019 ◽  
pp. 63-71 ◽  
Author(s):  
Nisha Angeline C. V. ◽  
Raja Lavanya
Keyword(s):  
Internet Of Things ◽  
Wireless Sensors ◽  
Smart Cities ◽  
Fog Computing ◽  
Connected Vehicle ◽  
Location Awareness ◽  
Sensors And Actuators ◽  
Computing Paradigm ◽  
The Internet Of Things

Fog computing extends the cloud computing paradigm to the edge of the network, thus enabling a new breed of applications and services. Defining characteristics of the Fog are 1) low latency and location awareness, 2) widespread geographical distribution, 3) mobility, 4) very large number of nodes, 5) predominant role of wireless access, 6) strong presence of streaming and real time applications, and 7) heterogeneity. In this chapter, the authors argue that the above characteristics make the Fog the appropriate platform for a number of critical internet of things (IoT) services and applications, namely connected vehicle, smart grid, smart cities, and in general, wireless sensors and actuators networks (WSANs).

scholarly journals Quality of Service Provision in Fog Computing: Network-Aware Scheduling of Containers

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3978
Author(s):  
Agustín C. Caminero ◽  
Rocío Muñoz-Mansilla
Keyword(s):  
Smart Cities ◽  
Scheduling Algorithm ◽  
Fog Computing ◽  
Optimal Solution ◽  
Data Sets ◽  
Huge Data ◽  
The Status ◽  
Time Requirements ◽  
Allocation Decisions

State-of-the-art scenarios, such as Internet of Things (IoT) and Smart Cities, have recently arisen. They involve the processing of huge data sets under strict time requirements, rendering the use of cloud resources unfeasible. For this reason, Fog computing has been proposed as a solution; however, there remains a need for intelligent allocation decisions, in order to make it a fully usable solution in such contexts. In this paper, a network-aware scheduling algorithm is presented, which aims to select the fog node most suitable for the execution of an application within a given deadline. This decision is made taking the status of the network into account. This scheduling algorithm was implemented as an extension to the Kubernetes default scheduler, and compared with existing proposals in the literature. The comparison shows that our proposal is the only one that can execute all the submitted jobs within their deadlines (i.e., no job is rejected or executed exceeding its deadline) with certain configurations in some of the scenarios tested, thus obtaining an optimal solution in such scenarios.

Fog Computing Application Deployment and Management

2019 ◽  
pp. 68-83
Author(s):  
Ranjitha G. ◽  
Pankaj Lathar ◽  
G. M. Siddesh
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Smart Cities ◽  
Fog Computing ◽  
The Internet ◽  
Access Points ◽  
Computing Paradigm ◽  
Application Deployment ◽  
Iot Devices ◽  
The Internet Of Things

Fog computing enhances cloud computing to be closer to the processes that act on IOT devices. Fogging was introduced to overcome the cloud computing paradigm which was not able to address some services, applications, and other limitations of cloud computing such as security aspects, bandwidth, and latency. Fog computing provides the direct correlation with the internet of things. IBM and CISCO are linking their concepts of internet of things with the help of fog computing. Application services are hosted on the network edge. It improves the efficiency and reduces the amount of data that is transferred to the cloud for analysis, storage, and processing. Developers write the fog application and deploy it to the access points. Several applications like smart cities, healthcare domain, pre-processing, and caching applications have to be deployed and managed properly.

scholarly journals Fog computing scheduling algorithm for smart city

2021 ◽  
Vol 11 (3) ◽  
pp. 2219
Author(s):  
Ahmad Mohammad Alsmadi ◽  
Roba Mahmoud Ali Aloglah ◽  
Nisrein Jamal sanad Abu-darwish ◽  
Ahmad Al Smadi ◽  
Muneerah Alshabanah ◽  
...  
Keyword(s):  
Smart Cities ◽  
Scheduling Algorithm ◽  
Fog Computing ◽  
Smart Devices ◽  
The Internet ◽  
5G Networks ◽  
Sustainable Infrastructure ◽  
Time Latency ◽  
The Internet Of Things ◽  
Fast Transmission

With the advent of the number of smart devices across the globe, increasing the number of users using the Internet. The main aim of the fog computing (FC) paradigm is to connect huge number of smart objects (billions of object) that can make a bright future for smart cities. Due to the large deployments of smart devices, devices are expected to generate huge amounts of data and forward the data through the Internet. FC also refers to an edge computing framework that mitigates the issue by applying the process of knowledge discovery using a data analysis approach to the edges. Thus, the FC approaches can work together with the internet of things (IoT) world, which can build a sustainable infrastructure for smart cities. In this paper, we propose a scheduling algorithm namely the weighted round-robin (WRR) scheduling algorithm to execute the task from one fog node (FN) to another fog node to the cloud. Firstly, a fog simulator is used with the emergent concept of FC to design IoT infrastructure for smart cities. Then, spanning-tree routing (STP) protocol is used for data collection and routing. Further, 5G networks are proposed to establish fast transmission and communication between users. Finally, the performance of our proposed system is evaluated in terms of response time, latency, and amount of data used.

Analysis of Internet of Things Based on Characteristics, Functionalities, and Challenges

2021 ◽  
Vol 5 (1) ◽  
pp. 44-62
Author(s):  
Ganesh Khekare ◽  
Pushpneel Verma ◽  
Urvashi Dhanre ◽  
Seema Raut ◽  
Ganesh Yenurkar
Keyword(s):  
Internet Of Things ◽  
Smart Cities ◽  
Fog Computing ◽  
Smart Devices ◽  
The Internet ◽  
Private Companies ◽  
Internet Availability ◽  
Near Future ◽  
The Internet Of Things

The internet of things (IoT) is transpiring technology. In the last decade, demand of IoT has been increased due to various things like the use of smart devices; increased demand for voice-based services; the concept of smart cities has been evolved; more requirements of processed data in fields of artificial intelligence and machine learning; fog computing, deep learning, etc. IoT is expected to reach the milestone of 30 billion IoT units at the end of the year 2020. Internet of things is the network of statutory things like houses, private companies, automobiles, and various objects integrated with sensors, actuators, software, electronic equipment, and internet availability that provides the facility to devices to interchange their data. The main contribution of this article is to provide state of art about the characteristics, functionalities, and challenges of the internet of things and the journey of IoT right from start to how it will make an impact on people's quality of life throughout the world in the near future.

scholarly journals Towards smarter cities taking advantage of the Fog Computing paradigm

2018 ◽  
Vol 16 (45) ◽  
Author(s):  
Shouddy Tárano León ◽  
Tatiana Delgado Fernández ◽  
Alejandro Luar Pérez Colomé
Keyword(s):  
Real Time ◽  
Recommendation System ◽  
Smart Cities ◽  
Fog Computing ◽  
Decision Making Process ◽  
End User ◽  
Latency Reduction ◽  
Iot Applications ◽  
Computing Paradigm ◽  
The Internet Of Things

The fog computing term has achieved importance in the last years due to its effect in the latency reduction that the Internet of Things [IoT] applications have. These applications demand real-time (or nearly real-time) responses and they are characterized by low bandwidth consumption; hence, the fog computing is relevant in achieving these requests because part of the processing is done near the end user devices. For this reason, the cloud computing paradigm is not enough for some applications, since nowadays, the instant need of data and the decision-making process leverage –or somehow discover– a new horizon that demands a complementary variable. This article consists on an approach to the fog computing term, together with the requirements analysis for engineering solutions in the IoT field. Also, its impact in the smart cities and other fields plus its main challenges are addressed. We also present a guideline to implement a recommendation system for sightseeing places for tourists based in fog computing embraced in a large smart city project located in Havana.

Security in Smart Healthcare System: A Comprehensive Survey

2017 ◽  
Vol 7 (10) ◽  
pp. 39
Author(s):  
P. Jeyadurga ◽  
S. Ebenezer Juliet ◽  
I. Joshua Selwyn ◽  
P. Sivanisha
Keyword(s):  
Secure Communication ◽  
Smart Cities ◽  
Healthcare Systems ◽  
Internet Security ◽  
Security Risk ◽  
System A ◽  
Smart Healthcare ◽  
Comprehensive Survey ◽  
Healthcare Monitoring ◽  
The Internet Of Things

The Internet of things (IoT) is one of the emerging technologies that brought revolution in many application domains such as smart cities, smart retails, healthcare monitoring and so on. As the physical objects are connected via internet, security risk may arise. This paper analyses the existing technologies and protocols that are designed by different authors to ensure the secure communication over internet. It additionally focuses on the advancement in healthcare systems while deploying IoT services.

M2FBalancer: A mist-assisted fog computing-based load balancing strategy for smart cities

2021 ◽  
pp. 1-15
Author(s):  
Subhranshu Sekhar Tripathy ◽  
Diptendu Sinha Roy ◽  
Rabindra K. Barik
Keyword(s):  
Load Balancing ◽  
Resource Utilization ◽  
Smart City ◽  
Load Transfer ◽  
Smart Cities ◽  
Fog Computing ◽  
Round Robin ◽  
Healthcare Management ◽  
Optimization Strategy ◽  
Allocation Method

Nowadays, cities are intended to change to a smart city. According to recent studies, the use of data from contributors and physical objects in many cities play a key element in the transformation towards a smart city. The ‘smart city’ standard is characterized by omnipresent computing resources for the observing and critical control of such city’s framework, healthcare management, environment, transportation, and utilities. Mist computing is considered a computing prototype that performs IoT applications at the edge of the network. To maintain the Quality of Service (QoS), it is impressive to employ context-aware computing as well as fog computing simultaneously. In this article, the author implements an optimization strategy applying a dynamic resource allocation method based upon genetic algorithm and reinforcement learning in combination with a load balancing procedure. The proposed model comprises four layers i.e. IoT layer, Mist layer, Fog layer, and Cloud layer. Authors have proposed a load balancing technique called M2F balancer which regulates the traffic in the network incessantly, accumulates the information about each server load, transfer the incoming query, and disseminate them among accessible servers equally using dynamic resources allocation method. To validate the efficacy of the proposed algorithm makespan, resource utilization, and the degree of imbalance (DOI) are considered as the scheduling parameter. The proposed method is being compared with the Least count, Round Robin, and Weighted Round Robin. In the end, the results demonstrate that the solutions enhance QoS in the mist assisted cloud environment concerning maximization resource utilization and minimizing the makespan. Therefore, M2FBalancer is an effective method to utilize the resources efficiently by ensuring uninterrupted service. Consequently, it improves performance even at peak times.

scholarly journals Surveillance System in Smart Cities: A Dependability Evaluation Based on Stochastic Models

Electronics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 876
Author(s):  
Igor Gonçalves ◽  
Laécio Rodrigues ◽  
Francisco Airton Silva ◽  
Tuan Anh Nguyen ◽  
Dugki Min ◽  
...  
Keyword(s):  
Surveillance System ◽  
Smart Cities ◽  
Heterogeneous Data ◽  
Time To Failure ◽  
Video Streams ◽  
Dependability Evaluation ◽  
The Mean ◽  
Mean Time ◽  
The Internet Of Things

Surveillance monitoring systems are highly necessary, aiming to prevent many social problems in smart cities. The internet of things (IoT) nowadays offers a variety of technologies to capture and process massive and heterogeneous data. Due to the fact that (i) advanced analyses of video streams are performed on powerful recording devices; while (ii) surveillance monitoring services require high availability levels in the way that the service must remain connected, for example, to a connection network that offers higher speed than conventional connections; and that (iii) the trust-worthy dependability of a surveillance system depends on various factors, it is not easy to identify which components/devices in a system architecture have the most impact on the dependability for a specific surveillance system in smart cities. In this paper, we developed stochastic Petri net models for a surveillance monitoring system with regard to varying several parameters to obtain the highest dependability. Two main metrics of interest in the dependability of a surveillance system including reliability and availability were analyzed in a comprehensive manner. The analysis results show that the variation in the number of long-term evolution (LTE)-based stations contributes to a number of nines (#9s) increase in availability. The obtained results show that the variation of the mean time to failure (MTTF) of surveillance cameras exposes a high impact on the reliability of the system. The findings of this work have the potential of assisting system architects in planning more optimized systems in this field based on the proposed models.

scholarly journals Implementation analysis of IoT-based offloading frameworks on cloud/edge computing for sensor generated big data

2021 ◽  
Author(s):  
Karan Bajaj ◽  
Bhisham Sharma ◽  
Raman Singh
Keyword(s):  
High Speed ◽  
Smart Cities ◽  
Fog Computing ◽  
Edge Computing ◽  
Computation Offloading ◽  
Performance Parameters ◽  
Iot Applications ◽  
Time Sensitivity ◽  
Implementation Analysis ◽  
Increasing Demand

AbstractThe Internet of Things (IoT) applications and services are increasingly becoming a part of daily life; from smart homes to smart cities, industry, agriculture, it is penetrating practically in every domain. Data collected over the IoT applications, mostly through the sensors connected over the devices, and with the increasing demand, it is not possible to process all the data on the devices itself. The data collected by the device sensors are in vast amount and require high-speed computation and processing, which demand advanced resources. Various applications and services that are crucial require meeting multiple performance parameters like time-sensitivity and energy efficiency, computation offloading framework comes into play to meet these performance parameters and extreme computation requirements. Computation or data offloading tasks to nearby devices or the fog or cloud structure can aid in achieving the resource requirements of IoT applications. In this paper, the role of context or situation to perform the offloading is studied and drawn to a conclusion, that to meet the performance requirements of IoT enabled services, context-based offloading can play a crucial role. Some of the existing frameworks EMCO, MobiCOP-IoT, Autonomic Management Framework, CSOS, Fog Computing Framework, based on their novelty and optimum performance are taken for implementation analysis and compared with the MAUI, AnyRun Computing (ARC), AutoScaler, Edge computing and Context-Sensitive Model for Offloading System (CoSMOS) frameworks. Based on the study of drawn results and limitations of the existing frameworks, future directions under offloading scenarios are discussed.

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