scholarly journals Sustainable Smart Cities: A Fog Computing Framework for a Smart Urban Transport Network

2018 ◽  
Vol 28 (4) ◽  
pp. 68-80 ◽  
Author(s):  
Ioan-Mădălin Neagu
Keyword(s):  
Smart City ◽  
Smart Cities ◽  
Fog Computing ◽  
Urban Transport ◽  
Transport Network ◽  
Social Implications ◽  
End User ◽  
Funding Sources ◽  
Computing Framework

Abstract In the present paper, a fog computing framework for smart urban transport is developed. The proposed framework is adapted to the smart city concept. It uses a collaborative multitude of end-user clients to carry out a substantial amount of communication and computation. It can be adapted for specific situations of smart cities in Romania, such as: Cluj-Napoca, Timișoara, Iași or Bucharest. Economic and social implications as well as available European funding sources are presented.

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.

Desain Banyumas Smart City Berbasis Internet of Things (IoT) Menggunakan Fog Computing Architecture

2020 ◽  
Vol 1 (1) ◽  
pp. 7-13
Author(s):  
Bayu Prastyo ◽  
Faiz Syaikhoni Aziz ◽  
Wahyu Pribadi ◽  
A.N. Afandi
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Communication Technology ◽  
Smart City ◽  
Communication Systems ◽  
Intelligent System ◽  
Smart Cities ◽  
Fog Computing ◽  
The Internet ◽  
Traffic Lights

Internet use in Banyumas Regency is now increasingly diverse according to the demands of the needs. The development of communication technology raises various aspects that also develop. For example, the use of the internet for a traffic light control system so that it can be adjusted according to the settings and can be monitored in real time. In the development of communication technology, the term Internet of Things (IoT) emerged as the concept of extending the benefits of internet communication systems to give impulses to other systems. In other words, IoT is used as a communication for remote control and monitoring by utilizing an internet connection. The Internet of Things in the era is now being developed to create an intelligent system for the purposes of controlling various public needs until the concept of the smart city emerges. Basically, smart cities utilize internet connections for many purposes such as controlling CCTV, traffic lights, controlling arm robots in the industry and storing data in hospitals. If the system is carried out directly from the device to the central server, there will be a very long queue of data while the system created requires speed and accuracy of time so that a system is needed that allows sufficient data control and processing to be carried out on network edge users. Then fog Computing is used with the hope that the smart city system can work with small latency values ​​so that the system is more real-time in sending or receiving data.

scholarly journals Desain Banyumas Smart City Berbasis Internet of Things (IoT) Menggunakan Fog Computing Architecture

2020 ◽  
Vol 1 (2) ◽  
pp. 6-13
Author(s):  
Bayu Prastyo ◽  
Faiz Syaikhoni Aziz ◽  
Wahyu Pribadi ◽  
A.N. Afandi
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Communication Technology ◽  
Smart City ◽  
Communication Systems ◽  
Intelligent System ◽  
Smart Cities ◽  
Fog Computing ◽  
The Internet ◽  
Traffic Lights

Internet use in Banyumas Regency is now increasingly diverse according to the demands of the needs. The development of communication technology raises various aspects that also develop. For example, the use of the internet for a traffic light control system so that it can be adjusted according to the settings and can be monitored in real time. In the development of communication technology, the term Internet of Things (IoT) emerged as the concept of extending the benefits of internet communication systems to give impulses to other systems. In other words, IoT is used as a communication for remote control and monitoring by utilizing an internet connection. The Internet of Things in the era is now being developed to create an intelligent system for the purposes of controlling various public needs until the concept of the smart city emerges. Basically, smart cities utilize internet connections for many purposes such as controlling CCTV, traffic lights, controlling arm robots in the industry and storing data in hospitals. If the system is carried out directly from the device to the central server, there will be a very long queue of data while the system created requires speed and accuracy of time so that a system is needed that allows sufficient data control and processing to be carried out on network edge users. Then fog Computing is used with the hope that the smart city system can work with small latency values ​​so that the system is more real-time in sending or receiving data

An Extension of the MiSCi Middleware for Smart Cities Based on Fog Computing

Fog Computing ◽  
2018 ◽  
pp. 230-250
Author(s):  
Jose Aguilar ◽  
Manuel B. Sanchez ◽  
Marxjhony Jerez ◽  
Maribel Mendonca
Keyword(s):  
Embedded Systems ◽  
Intelligent Agents ◽  
Smart City ◽  
Smart Cities ◽  
Fog Computing ◽  
Sources Of Information ◽  
Multiple Sources ◽  
Computing Paradigm ◽  
Reflective Middleware ◽  
The People

In a Smart City is required computational platforms, which allow environments with multiple interconnected and embedded systems, where the technology is integrated with the people, and can respond to unpredictable situations. One of the biggest challenges in developing Smart City is how to describe and dispose of enormous and multiple sources of information, and how to share and merge it into a single infrastructure. In previous works, we have proposed an Autonomic Reflective Middleware with emerging and ubiquitous capabilities, which is based on intelligent agents that can be adapted to the existing dynamism in a city for, ubiquitously, respond to the requirements of citizens, using emerging ontologies that allow the adaptation to the context. In this work, we extend this middleware using the fog computing paradigm, to solve this problem. The fog extends the cloud to be closer to the things that produce and act on the smart city. In this paper, we present the extension to the middleware, and examples of utilization in different situations in a smart city.

scholarly journals Exploring the influence of big data on city transport operations: a Markovian approach

2017 ◽  
Vol 37 (1) ◽  
pp. 75-104 ◽  
Author(s):  
Rashid Mehmood ◽  
Royston Meriton ◽  
Gary Graham ◽  
Patrick Hennelly ◽  
Mukesh Kumar
Keyword(s):  
Big Data ◽  
Markov Model ◽  
Absorptive Capacity ◽  
Smart City ◽  
Smart Cities ◽  
Theoretical Framework ◽  
Social Implications ◽  
Content Type ◽  
Depth Analysis ◽  
City System

Purpose The purpose of this paper is to advance knowledge of the transformative potential of big data on city-based transport models. The central question guiding this paper is: how could big data transform smart city transport operations? In answering this question the authors present initial results from a Markov study. However the authors also suggest caution in the transformation potential of big data and highlight the risks of city and organizational adoption. A theoretical framework is presented together with an associated scenario which guides the development of a Markov model. Design/methodology/approach A model with several scenarios is developed to explore a theoretical framework focussed on matching the transport demands (of people and freight mobility) with city transport service provision using big data. This model was designed to illustrate how sharing transport load (and capacity) in a smart city can improve efficiencies in meeting demand for city services. Findings This modelling study is an initial preliminary stage of the investigation in how big data could be used to redefine and enable new operational models. The study provides new understanding about load sharing and optimization in a smart city context. Basically the authors demonstrate how big data could be used to improve transport efficiency and lower externalities in a smart city. Further how improvement could take place by having a car free city environment, autonomous vehicles and shared resource capacity among providers. Research limitations/implications The research relied on a Markov model and the numerical solution of its steady state probabilities vector to illustrate the transformation of transport operations management (OM) in the future city context. More in depth analysis and more discrete modelling are clearly needed to assist in the implementation of big data initiatives and facilitate new innovations in OM. The work complements and extends that of Setia and Patel (2013), who theoretically link together information system design to operation absorptive capacity capabilities. Practical implications The study implies that transport operations would actually need to be re-organized so as to deal with lowering CO2 footprint. The logistic aspects could be seen as a move from individual firms optimizing their own transportation supply to a shared collaborative load and resourced system. Such ideas are radical changes driven by, or leading to more decentralized rather than having centralized transport solutions (Caplice, 2013). Social implications The growth of cities and urban areas in the twenty-first century has put more pressure on resources and conditions of urban life. This paper is an initial first step in building theory, knowledge and critical understanding of the social implications being posed by the growth in cities and the role that big data and smart cities could play in developing a resilient and sustainable transport city system. Originality/value Despite the importance of OM to big data implementation, for both practitioners and researchers, we have yet to see a systematic analysis of its implementation and its absorptive capacity contribution to building capabilities, at either city system or organizational levels. As such the Markov model makes a preliminary contribution to the literature integrating big data capabilities with OM capabilities and the resulting improvements in system absorptive capacity.

scholarly journals Applications of Integrated IoT-Fog-Cloud Systems to Smart Cities: A Survey

Electronics ◽  
2021 ◽  
Vol 10 (23) ◽  
pp. 2918
Author(s):  
Nader Mohamed ◽  
Jameela Al-Jaroodi ◽  
Sanja Lazarova-Molnar ◽  
Imad Jawhar
Keyword(s):  
Smart City ◽  
New Technologies ◽  
Smart Cities ◽  
Fog Computing ◽  
Optimization Methods ◽  
Cloud Services ◽  
Security Measures ◽  
Operations And Maintenance ◽  
And Performance ◽  
The One

Several cities have recently moved towards becoming smart cities for better services and quality of life for residents and visitors, with: optimized resource utilization; increased environmental protection; enhanced infrastructure operations and maintenance; and strong safety and security measures. Smart cities depend on deploying current and new technologies and different optimization methods to enhance services and performance in their different sectors. Some of the technologies assisting smart city applications are the Internet of Things (IoT), fog computing, and cloud computing. Integrating these three to serve one system (we will refer to it as integrated IoT-fog-cloud system (iIFC)) creates an advanced platform to develop and operate various types of smart city applications. This platform will allow applications to use the best features from the IoT devices, fog nodes, and cloud services to deliver best capabilities and performance. Utilizing this powerful platform will provide many opportunities for enhancing and optimizing applications in energy, transportation, healthcare, and other areas. In this paper we survey various applications of iIFCs for smart cities. We identify different common issues associated with utilizing iIFCs for smart city applications. These issues arise due to the characteristics of iIFCs on the one side and the requirements of different smart city applications on the other. In addition, we outline the main requirements to effectively utilize iIFCs for smart city applications. These requirements are related to optimization, networking, and security.

An Extension of the MiSCi Middleware for Smart Cities Based on Fog Computing

2019 ◽  
pp. 778-798
Author(s):  
Jose Aguilar ◽  
Manuel B. Sanchez ◽  
Marxjhony Jerez ◽  
Maribel Mendonca
Keyword(s):  
Embedded Systems ◽  
Intelligent Agents ◽  
Smart City ◽  
Smart Cities ◽  
Fog Computing ◽  
Sources Of Information ◽  
Multiple Sources ◽  
Computing Paradigm ◽  
Reflective Middleware ◽  
The People

In a Smart City is required computational platforms, which allow environments with multiple interconnected and embedded systems, where the technology is integrated with the people, and can respond to unpredictable situations. One of the biggest challenges in developing Smart City is how to describe and dispose of enormous and multiple sources of information, and how to share and merge it into a single infrastructure. In previous works, we have proposed an Autonomic Reflective Middleware with emerging and ubiquitous capabilities, which is based on intelligent agents that can be adapted to the existing dynamism in a city for, ubiquitously, respond to the requirements of citizens, using emerging ontologies that allow the adaptation to the context. In this work, we extend this middleware using the fog computing paradigm, to solve this problem. The fog extends the cloud to be closer to the things that produce and act on the smart city. In this paper, we present the extension to the middleware, and examples of utilization in different situations in a smart city.

An Extension of the MiSCi Middleware for Smart Cities Based on Fog Computing

2017 ◽  
Vol 10 (4) ◽  
pp. 23-41 ◽  
Author(s):  
Jose Aguilar ◽  
Manuel B. Sanchez ◽  
Marxjhony Jerez ◽  
Maribel Mendonca
Keyword(s):  
Embedded Systems ◽  
Intelligent Agents ◽  
Smart City ◽  
Smart Cities ◽  
Fog Computing ◽  
Sources Of Information ◽  
Multiple Sources ◽  
Computing Paradigm ◽  
Reflective Middleware ◽  
The People

In a Smart City is required computational platforms, which allow environments with multiple interconnected and embedded systems, where the technology is integrated with the people, and can respond to unpredictable situations. One of the biggest challenges in developing Smart City is how to describe and dispose of enormous and multiple sources of information, and how to share and merge it into a single infrastructure. In previous works, we have proposed an Autonomic Reflective Middleware with emerging and ubiquitous capabilities, which is based on intelligent agents that can be adapted to the existing dynamism in a city for, ubiquitously, respond to the requirements of citizens, using emerging ontologies that allow the adaptation to the context. In this work, we extend this middleware using the fog computing paradigm, to solve this problem. The fog extends the cloud to be closer to the things that produce and act on the smart city. In this paper, we present the extension to the middleware, and examples of utilization in different situations in a smart city.

scholarly journals Fog Computing for Smart Cities’ Big Data Management and Analytics: A Review

2020 ◽  
Vol 12 (11) ◽  
pp. 190
Author(s):  
Elarbi Badidi ◽  
Zineb Mahrez ◽  
Essaid Sabir
Keyword(s):  
Big Data ◽  
Public Space ◽  
Data Storage ◽  
Smart City ◽  
Urban Areas ◽  
Smart Cities ◽  
Fog Computing ◽  
Space Management ◽  
Network Bandwidth ◽  
Edge And Fog Computing

Demographic growth in urban areas means that modern cities face challenges in ensuring a steady supply of water and electricity, smart transport, livable space, better health services, and citizens’ safety. Advances in sensing, communication, and digital technologies promise to mitigate these challenges. Hence, many smart cities have taken a new step in moving away from internal information technology (IT) infrastructure to utility-supplied IT delivered over the Internet. The benefit of this move is to manage the vast amounts of data generated by the various city systems, including water and electricity systems, the waste management system, transportation system, public space management systems, health and education systems, and many more. Furthermore, many smart city applications are time-sensitive and need to quickly analyze data to react promptly to the various events occurring in a city. The new and emerging paradigms of edge and fog computing promise to address big data storage and analysis in the field of smart cities. Here, we review existing service delivery models in smart cities and present our perspective on adopting these two emerging paradigms. We specifically describe the design of a fog-based data pipeline to address the issues of latency and network bandwidth required by time-sensitive smart city applications.

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