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 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.

Distributed load balancing for heterogeneous fog computing infrastructures in smart cities

2020 ◽  
Vol 67 ◽  
pp. 101221 ◽  
Author(s):  
Roberto Beraldi ◽  
Claudia Canali ◽  
Riccardo Lancellotti ◽  
Gabriele Proietti Mattia
Keyword(s):  
Load Balancing ◽  
Smart Cities ◽  
Fog Computing ◽  
Distributed Load

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

scholarly journals SMS: A Secure Healthcare Model for Smart Cities

Electronics ◽  
2020 ◽  
Vol 9 (7) ◽  
pp. 1135
Author(s):  
Gautami Tripathi ◽  
Mohd Abdul Ahad ◽  
Sara Paiva
Keyword(s):  
Real Time ◽  
Assisted Living ◽  
Smart City ◽  
Smart Cities ◽  
Ambient Assisted Living ◽  
Critical Time ◽  
Personal Data ◽  
Healthcare Management ◽  
Real Time Analysis ◽  
Healthcare Model

Technological innovations have enabled the realization of a utopian world where all objects of everyday life, as well as humans, are interconnected to form an “Internet of Things (IoT).” These connected technologies and IoT solutions have led to the emergence of smart cities where all components are converted into a connected smart ecosystem. IoT has envisioned several areas of smart cities including the modern healthcare environment like real-time monitoring, patient information management, ambient-assisted living, ambient-intelligence, anomaly detection, and accelerated sensing. IoT has also brought a breakthrough in the medical domain by integrating stake holders, medical components, and hospitals to bring about holistic healthcare management. The healthcare domain is already witnessing promising IoT-based solutions ranging from embedded mobile applications to wearable devices and implantable gadgets. However, with all these exemplary benefits, there is a need to ensure the safety and privacy of the patient’s personal and medical data communicated to and from the connected devices and systems. For a smart city, it is pertinent to have an accessible, effective, and secure healthcare system for its inhabitants. This paper discusses the various elements of technology-enabled healthcare and presents a privacy-preserved and secure “Smart Medical System (SMS)” framework for the smart city ecosystem. For providing real-time analysis and responses, this paper proposes to use the concept of secured Mobile Edge Computing (MEC) for performing critical time-bound computations on the edge itself. In order to protect the medical and personal data of the patients and to make the data tamper-proof, the concept of blockchain has been used. Finally, this paper highlights the ways to capture and store the medical big data generated from IoT devices and sensors.

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.

Load balancing strategy in software defined network by improved whale optimization algorithm

2021 ◽  
pp. 1-17
Author(s):  
Santosh Ashokrao Darade ◽  
M. Akkalakshmi
Keyword(s):  
Load Balancing ◽  
Optimization Algorithm ◽  
Time Allocation ◽  
Fog Computing ◽  
Whale Optimization Algorithm ◽  
Optimization Strategy ◽  
Mobility Support ◽  
Proposed Model ◽  
Whale Optimization ◽  
Conventional Models

From the recent study, it is observed that even though cloud computing grants the greatest performance in the case of storage, computing, and networking services, the Internet of Things (IoT) still suffers from high processing latency, awareness of location, and least mobility support. To address these issues, this paper integrates fog computing and Software-Defined Networking (SDN). Importantly, fog computing does the extension of computing and storing to the network edge that could minimize the latency along with mobility support. Further, this paper aims to incorporate a new optimization strategy to address the “Load balancing” problem in terms of latency minimization. A new Thresholded-Whale Optimization Algorithm (T-WOA) is introduced for the optimal selection of load distribution coefficient (time allocation for doing a task). Finally, the performance of the proposed model is compared with other conventional models concerning latency. The simulation results prove that the SDN based T-WOA algorithm could efficiently minimize the latency and improve the Quality of Service (QoS) in Software Defined Cloud/Fog architecture.

A load balancing and optimization strategy (LBOS) using reinforcement learning in fog computing environment

2020 ◽  
Vol 11 (11) ◽  
pp. 4951-4966 ◽  
Author(s):  
Fatma M. Talaat ◽  
Mohamed S. Saraya ◽  
Ahmed I. Saleh ◽  
Hesham A. Ali ◽  
Shereen H. Ali
Keyword(s):  
Reinforcement Learning ◽  
Load Balancing ◽  
Fog Computing ◽  
Optimization Strategy ◽  
Computing Environment

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.

scholarly journals Security-Aware computation offloading for Mobile edge computing-Enabled smart city

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Kai Peng ◽  
Peichen Liu ◽  
Peng Tao ◽  
Qingjia Huang
Keyword(s):  
Load Balancing ◽  
Resource Utilization ◽  
Smart City ◽  
Living Standards ◽  
Computation Offloading ◽  
Smart Devices ◽  
Time Consumption ◽  
Delay Sensitive ◽  
Consumption Energy ◽  
Overall Performance

AbstractSmart city has obtained increasing attention from both academic and industry which has the potential to improve human living standards. A smart city consists of a great number of smart devices which are generating large amounts of data and emerging applications all the time. However, the computing capacity of smart devices are limited. Fortunately, the emergence of MEC can solve the above problem. However, the resources of edge servers in MEC are limited and the capabilities of edge servers are heterogeneous. It is important to improve the average resource utilization of all edge servers and keep load balancing of edge server cluster simultaneously. On the other hand, quite a few numbers of applications are delay-sensitive, it is necessary to ensure the security of these applications. In this paper, we consider joint optimization of mobile device and edge server in MEC-enabled smart city, improving the overall performance of the system. Technically, a new multi-objective computation offloading method is implemented to reduce time consumption, energy consumption, and keep load balancing of edge servers, as well as increase average resource utilization of edge servers while meeting the deadline constraint of delay-sensitive applications. Sufficient experiments have been conducted to prove the effectiveness and superiority of our proposed method in different scenarios.

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