scholarly journals Towards a Fog-Enabled Intelligent Transportation System to Reduce Traffic Jam

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3916 ◽  
Author(s):  
Celso A. R. L. Brennand ◽  
Geraldo P. Rocha Filho ◽  
Guilherme Maia ◽  
Felipe Cunha ◽  
Daniel L. Guidoni ◽  
...  
Keyword(s):  
Intelligent Transportation System ◽  
Fog Computing ◽  
Processing Load ◽  
Urban Centers ◽  
Planning Time ◽  
Traffic Jam ◽  
Computing Paradigm ◽  
Stop Time ◽  
Communication Evaluation ◽  
Different Characteristics

Frustrations, monetary losses, lost time, high fuel consumption and CO 2 emissions are some of the problems caused by traffic jams in urban centers. In an attempt to solve this problem, this article proposes a traffic service to control congestion, named FOXS–Fast Offset Xpath Service. FOXS aims to reduce the problems generated by a traffic jam in a distributed way through roads classification and the suggestion of new routes to vehicles. Unlike the related works, FOXS is modeled using the Fog computing paradigm. Therefore, it is possible to take advantage of the inherent aspects of this paradigm, such as low latency, processing load balancing, scalability, geographical correlation and the reduction of bandwidth usage. In order to validate FOXS, our performance evaluation considers two realistic urban scenarios with different characteristics. When compared with related works, FOXS shows a reduction in stop time by up to 70%, the CO 2 emissions by up to 29% and, the planning time index by up to 49%. When considering communication evaluation metrics, FOXS reaches a better result than other solutions on the packet collisions metric (up to 11.5%) and on the application delay metric (up to 30%).

Simulation and Emulation Tools for Fog Computing

2020 ◽  
Vol 13 ◽  
Author(s):  
Simar Preet Singh ◽  
Rajesh Kumar ◽  
Anju Sharma ◽  
S. Raji Reddy ◽  
Priyanka Vashisht
Keyword(s):  
Quality Of Service ◽  
Programming Languages ◽  
Traffic Management ◽  
Fog Computing ◽  
Research Work ◽  
Research Experience ◽  
Computing Paradigm ◽  
Quality Of Service Parameters ◽  
User Friendly

Background: Fog computing paradigm has recently emerged and gained higher attention in present era of Internet of Things. The growth of large number of devices all around, leads to the situation of flow of packets everywhere on the Internet. To overcome this situation and to provide computations at network edge, fog computing is the need of present time that enhances traffic management and avoids critical situations of jam, congestion etc. Methods: For research purposes, there are many methods to implement the scenarios of fog computing i.e. real-time implementation, implementation using emulators, implementation using simulators etc. The present study aims to describe the various simulation and emulation tools for implementing fog computing scenarios. Results: Review shows that iFogSim is the simulator that most of the researchers use in their research work. Among emulators, EmuFog is being used at higher pace than other available emulators. This might be due to ease of implementation and user-friendly nature of these tools and language these tools are based upon. The use of such tools enhance better research experience and leads to improved quality of service parameters (like bandwidth, network, security etc.). Conclusion: There are many fog computing simulators/emulators based on many different platforms that uses different programming languages. The paper concludes that the two main simulation and emulation tools in the area of fog computing are iFogSim and EmuFog. Accessibility of these simulation/emulation tools enhance better research experience and leads to improved quality of service parameters along with the ease of their usage.

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 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 A Fog Computing-Based Architecture for Medical Records Management

2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Cícero A. Silva ◽  
Gibeon S. Aquino ◽  
Sávio R. M. Melo ◽  
Dannylo J. B. Egídio
Keyword(s):  
Medical Records ◽  
Fog Computing ◽  
Medical Data ◽  
Data Sources ◽  
Medical Applications ◽  
Records Management ◽  
Medical Field ◽  
Computing Paradigm ◽  
And Storage

The aging of the world’s population and the growth in the number of people with chronic diseases have increased expenses with medical care. Thus, the use of technological solutions has been widely adopted in the medical field to improve the patients’ health. In this context, approaches based on Cloud Computing have been used to store and process the information generated in these solutions. However, using Cloud can create delays that are intolerable for medical applications. Thus, the Fog Computing paradigm emerged as an alternative to overcome this problem, bringing computation and storage closer to the data sources. However, managing medical data stored in Fog is still a challenge. Moreover, characteristics of availability, performance, interoperability, and privacy need to be considered in approaches that aim to explore this problem. So, this article shows a software architecture based on Fog Computing and designed to facilitate the management of medical records. This architecture uses Blockchain concepts to provide the necessary privacy features and to allow Fog Nodes to carry out the authorization process in a distributed way. Finally, this paper describes a case study that evaluates the performance, privacy, and interoperability requirements of the proposed architecture in a home-centered healthcare scenario.

scholarly journals On the Location of Fog Nodes in Fog-Cloud Infrastructures

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2445 ◽  
Author(s):  
Rodrigo A. C. da Silva ◽  
Nelson L. S. da Fonseca
Keyword(s):  
Fog Computing ◽  
Real Data ◽  
Mixed Integer ◽  
End User ◽  
Computing Paradigm ◽  
Linear Programming Formulation ◽  
Cloud Infrastructures ◽  
New Applications ◽  
Integer Linear Programming Formulation

In the fog computing paradigm, fog nodes are placed on the network edge to meet end-user demands with low latency, providing the possibility of new applications. Although the role of the cloud remains unchanged, a new network infrastructure for fog nodes must be created. The design of such an infrastructure must consider user mobility, which causes variations in workload demand over time in different regions. Properly deciding on the location of fog nodes is important to reduce the costs associated with their deployment and maintenance. To meet these demands, this paper discusses the problem of locating fog nodes and proposes a solution which considers time-varying demands, with two classes of workload in terms of latency. The solution was modeled as a mixed-integer linear programming formulation with multiple criteria. An evaluation with real data showed that an improvement in end-user service can be obtained in conjunction with the minimization of the costs by deploying fewer servers in the infrastructure. Furthermore, results show that costs can be further reduced if a limited blocking of requests is tolerated.

scholarly journals Elastic Computing in the Fog on Internet of Things to Improve the Performance of Low Cost Nodes

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1489 ◽  
Author(s):  
Rafael Fayos-Jordan ◽  
Santiago Felici-Castell ◽  
Jaume Segura-Garcia ◽  
Adolfo Pastor-Aparicio ◽  
Jesus Lopez-Ballester
Keyword(s):  
Operating System ◽  
Internet Of Things ◽  
Low Cost ◽  
Fog Computing ◽  
Mesh Network ◽  
Raspberry Pi ◽  
The Internet ◽  
Processing Unit ◽  
Computing Paradigm ◽  
Elastic Computing

The Internet of Things (IoT) is a network widely used with the purpose of connecting almost everything, everywhere to the Internet. To cope with this goal, low cost nodes are being used; otherwise, it would be very expensive to expand so fast. These networks are set up with small distributed devices (nodes) that have a power supply, processing unit, memory, sensors, and wireless communications. In the market, we can find different alternatives for these devices, such as small board computers (SBCs), e.g., Raspberry Pi (RPi)), with different features. Usually these devices run a coarse version of a Linux operating system. Nevertheless, there are many scenarios that require enhanced computational power that these nodes alone are unable to provide. In this context, we need to introduce a kind of collaboration among the devices to overcome their constraints. We based our solution in a combination of clustering techniques (building a mesh network using their wireless capabilities); at the same time we try to orchestrate the resources in order to improve their processing capabilities in an elastic computing fashion. This paradigm is called fog computing on IoT. We propose in this paper the use of cloud computing technologies, such as Linux containers, based on Docker, and a container orchestration platform (COP) to run on the top of a cluster of these nodes, but adapted to the fog computing paradigm. Notice that these technologies are open source and developed for Linux operating system. As an example, in our results we show an IoT application for soundscape monitoring as a proof of concept that it will allow us to compare different alternatives in its design and implementation; in particular, with regard to the COP selection, between Docker Swarm and Kubernetes. We conclude that using and combining these techniques, we can improve the overall computation capabilities of these IoT nodes within a fog computing paradigm.

scholarly journals An Edge-Fog Secure Self-Authenticable Data Transfer Protocol

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3612 ◽  
Author(s):  
Algimantas Venčkauskas ◽  
Nerijus Morkevicius ◽  
Vaidas Jukavičius ◽  
Robertas Damaševičius ◽  
Jevgenijus Toldinas ◽  
...  
Keyword(s):  
Data Transfer ◽  
Fog Computing ◽  
Transport Layer ◽  
Area Network ◽  
Lossy Networks ◽  
Redundant Data ◽  
Computing Paradigm ◽  
User Data ◽  
Constrained Devices ◽  
Transfer Protocol

Development of the Internet of Things (IoT) opens many new challenges. As IoT devices are getting smaller and smaller, the problems of so-called “constrained devices” arise. The traditional Internet protocols are not very well suited for constrained devices comprising localized network nodes with tens of devices primarily communicating with each other (e.g., various sensors in Body Area Network communicating with each other). These devices have very limited memory, processing, and power resources, so traditional security protocols and architectures also do not fit well. To address these challenges the Fog computing paradigm is used in which all constrained devices, or Edge nodes, primarily communicate only with less-constrained Fog node device, which collects all data, processes it and communicates with the outside world. We present a new lightweight secure self-authenticable transfer protocol (SSATP) for communications between Edge nodes and Fog nodes. The primary target of the proposed protocol is to use it as a secure transport for CoAP (Constrained Application Protocol) in place of UDP (User Datagram Protocol) and DTLS (Datagram Transport Layer Security), which are traditional choices in this scenario. SSATP uses modified header fields of standard UDP packets to transfer additional protocol handling and data flow management information as well as user data authentication information. The optional redundant data may be used to provide increased resistance to data losses when protocol is used in unreliable networks. The results of experiments presented in this paper show that SSATP is a better choice than UDP with DTLS in the cases, where the CoAP block transfer mode is used and/or in lossy networks.

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