scholarly journals Internet of Things-Based Energy Efficiency Optimization Model in Fog Smart Cities

2021 ◽  
Vol 5 (2) ◽  
pp. 105
Author(s):  
Wasswa Shafik ◽  
S. Mojtaba Matinkhah ◽  
Mamman Nur Sanda ◽  
Fawad Shokoor
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Internet Of Things ◽  
Response Time ◽  
Smart Grids ◽  
Smart Cities ◽  
Fog Computing ◽  
The Internet ◽  
Delay Sensitive ◽  
Service Delay

In recent years, the IoT) Internet of Things (IoT) allows devices to connect to the Internet that has become a promising research area mainly due to the constant emerging of the dynamic improvement of technologies and their associated challenges. In an approach to solve these challenges, fog computing came to play since it closely manages IoT connectivity. Fog-Enabled Smart Cities (IoT-ESC) portrays equitable energy consumption of a 7% reduction from 18.2% renewable energy contribution, which extends resource computation as a great advantage. The initialization of IoT-Enabled Smart Grids including (FESC) like fog nodes in fog computing, reduced workload in Terminal Nodes services (TNs) that are the sensors and actuators of the Internet of Things (IoT) set up. This paper proposes an integrated energy-efficiency model computation about the response time and delays service minimization delay in FESC. The FESC gives an impression of an auspicious computing model for location, time, and delay-sensitive applications supporting vertically -isolated, service delay, sensitive solicitations by providing abundant, ascendable, and scattered figuring stowage and system associativity. We first reviewed the persisting challenges in the proposed state-of-the models and based on them. We introduce a new model to address mainly energy efficiency about response time and the service delays in IoT-ESC. The iFogsim simulated results demonstrated that the proposed model minimized service delay and reduced energy consumption during computation. We employed IoT-ESC to decide autonomously or semi-autonomously whether the computation is to be made on Fog nodes or its transfer to the cloud.

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 Load Balancing of Fog Computing Centers: Minimizing Response Time of High Priority Requests

2019 ◽  
Vol 8 (11) ◽  
pp. 2713-2716
Keyword(s):  
Internet Of Things ◽  
Load Balancing ◽  
Response Time ◽  
Fog Computing ◽  
The Internet ◽  
Computing Technology ◽  
Computing Center ◽  
Computing Centers ◽  
The Internet Of Things ◽  
High Priority Request

Fog computing is one of the enabling computing technology which primarily aims to fulfill the requirements of the Internet of Things (IoT). IoT is fast-growing networking and computing sector. The scalability of users, devices, and application is crucial for the success of IoT systems. The load balancing is an approach to distribute the load among computing nodes so that the computing nodes are not overloaded. In this paper, we propose the priority-based request servicing at fog computing centers. We particularly address the situation when the fog node in fog computing center (FCC) receives more workload than their capacity to handle it. The increased workload is shifted to nearby fog nodes rather than to the remote cloud. The proposed approach is able to minimize the offloading the high priority request to other nodes by 11% which proves the novelty of our proposed.

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 On the Energy Efficiency in the Next Generation of Smart Buildings—Supporting Technologies and Techniques

Energies ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 4399 ◽  
Author(s):  
César Benavente-Peces
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Harvesting ◽  
Smart Grids ◽  
Smart Cities ◽  
Clean Energy ◽  
Communication Technologies ◽  
Next Generation ◽  
Smart Buildings ◽  
The Impact

Energy efficiency is one of the most relevant issues that the scientific community, and society in general, must face in the next years. Furthermore, higher energy efficiencies will contribute to worldwide sustainability. Buildings are responsible for 40% of the overall consumed energy. Smart Grids and Smart Buildings are playing an essential role in the definition of the next generation of sustainable Smart Cities. The main goal is reducing the impact of energy consumption on the environment as much as possible. This paper focuses on information communication technologies (ICTs) and techniques, their key characteristics and contribution to obtain higher energy efficiencies in smart buildings. Given that electrical energy is the most used, the investigation mainly centres on this energy. This paper also pays attention to green energies and energy harvesting due to their contribution to energy efficiency by providing additional clean energy. The main contribution of this investigation is pointing out the most relevant existing and emerging ICT technologies and techniques which can be used to optimize the energy efficiency of Smart Buildings. The research puts special attention on available, novel and emerging sensors, communication technologies and standards, intelligence techniques and algorithms, green energies and energy harvesting. All of them enable high-performance intelligent systems to optimize energy consumption and occupants’ comfort. Furthermore, it remarks on the most suitable technologies and techniques, their main features and their applications in Smart Buildings.

scholarly journals Optimizing Hybrid Metaheuristic Algorithm with Cluster Head to Improve Performance Metrics on the IoT

2021 ◽  
Author(s):  
Malik bader alazzam ◽  
Fawaz Alassery
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Smart Grids ◽  
Weather Prediction ◽  
Cluster Head ◽  
Optimization Techniques ◽  
The Internet ◽  
Wide Range ◽  
Whale Optimization ◽  
The Internet Of Things

Abstract The Internet of Things (IoT) has subsequently been applied to a variety of sectors, including smart grids, farming, weather prediction, power generation, wastewater treatment, and so on. So if the Internet of Things has enormous promise in a wide range of applications, there still are certain areas where it may be improved. Designers had focused our present research on reducing the energy consumption of devices in IoT networks, which will result in a longer network lifetime. The far more suitable Cluster Head (CH) throughout the IoT system is determined in this study to optimize energy consumption. Whale Optimization Algorithm (WOA) with Evolutionary Algorithm (EA) is indeed a mixed meta-heuristic algorithm used during the suggested study. Various quantifiable metrics, including the variety of adult nodes, workload, temperatures, remaining energy, and a target value, were utilized IoT network groups. The suggested method then is contrasted to several cutting-edge optimization techniques, including the Artificial Bee Colony method, Neural Network, Adapted Gravity Simulated annealing. The findings show that the suggested hybrid method outperforms conventional methods.

scholarly journals Autonomous WiFi Sensor for Heating Systems in the Internet of Things

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
C. A. Trasviña-Moreno ◽  
R. Blasco ◽  
R. Casas ◽  
A. Marco
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Smart Cities ◽  
High Energy ◽  
Environmental Data ◽  
The Internet ◽  
Processing Unit ◽  
Heating Systems ◽  
Thermoelectric Energy Harvesting ◽  
The Internet Of Things

In smart cities and home applications, the use of Wireless Sensor Networks to extract environmental data becomes more common with the passing of time. These sensors are used for a wide array of applications, but mainly to manage energy consumption in domestic buildings. One of the key energy consumers in households is heating systems. To monitor them, sensors are used with wireless communication protocols, like ZigBee, to transmit data to a central processing unit (CPU). WiFi communications, on the contrary, are rarely seen in these implementations due to its high energy consumption, although almost in every home one can find such networks. Yet, with the Internet of Things (IoT), new revisions of the standard have arisen which enable this technology for wireless sensing. To validate this theory and fill a technological necessity, this proposal is presented. In this work, the design and implementation of an autonomous WiFi sensor, paired with thermoelectric energy harvesting, are presented as an IoT solution for monitoring heating devices. For this, a thorough analysis of the proposed architecture is presented. Tests regarding energy consumption and generation, efficiency, and real world scenario trials are done. Finalizing, a comparison between the obtained results and current implementations is shown.

scholarly journals The Construction of a Smart City Energy Efficiency Management System Oriented to the Mobile Data Aggregation of the Internet of Things

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Longxing Chen ◽  
Ping Han
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Internet Of Things ◽  
Power Distribution ◽  
Reference Model ◽  
Current Status ◽  
The Internet ◽  
Management Platform ◽  
Internet Of Things Technology ◽  
The Internet Of Things

Aiming at the current situation of complicated energy-consuming equipment and large energy consumption in the current enterprise, a reference model scheme of an enterprise energy efficiency management platform based on the Internet of Things is analyzed and the dynamically collected energy consumption information is analyzed using the Internet of Things technology and data mining technology. They provide decision-making support for enterprise energy efficiency management decisions and formulation of energy-saving and emission reduction plans. This article analyzes the current status of energy efficiency management in buildings and points out several pain points in energy efficiency management, including installation difficulties, high software development costs, upgrade difficulties, long debugging cycles, and closed systems, and introduces intelligent power distribution monitoring based on the Internet of Things technology to solve these difficulties. In the system, we analyze the actual value brought by energy efficiency management technology through case studies. It can collect scattered information through the Internet of Things, gather it together to form massive data, and obtain the corresponding information through data analysis and processing. The design is reasonable, the practicality is strong, the use effect is good, and it is easy to promote and use.

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.

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 Energy Efficient Decision based Routing Technique using Fog Computing Paradigm

2019 ◽  
Vol 8 (9S) ◽  
pp. 964-969
Keyword(s):  
Energy Efficiency ◽  
Internet Of Things ◽  
Energy Efficient ◽  
New Technologies ◽  
Fog Computing ◽  
Emergency Situation ◽  
The Internet ◽  
Computing Paradigm ◽  
Current Scenario ◽  
The Internet Of Things

In the era of new technologies, Fog computing becomes very popular in today’s scenario. Fog computing paradigm brings a concept that extends cloud computing to the edge and close proximity to the Internet of Things (IoT) network. The fundamental components of fog computing are fog nodes. Additionally, fog nodes are energy efficient nodes. Numerous fog nodes are deployed in the associated fields that will handle the Internet of Things (IoT) sensors computation. Meanwhile, the Internet of Things (IoT) faces challenges, among which energy efficiency is one of the most prominent or critical challenges in the current scenario. However, sensor devices are an energy constraintthatcreateshotspotduringtheroutingprocess.Forthis reason,tohandlesuchconstraints,thispaperpresentsaneffective hotspot mechanism using fog nodes that demonstrate the routing process and directed the sensors to choose the routing path as selected by the fog node. Moreover, fog node will act as a decision maker node and maintain the energy efficiency of sensors during the routing as fog nodes are energy efficient nodes. As it moves towards the emergency situation, the most appropriate and effective routing approach has been designed who maintain the energy level of sensors will be high during the routing process. The proposed routing technique could be better performance for the sake of efficient routing in terms of energy consumption and prolonging networklifetime.

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