Since its inception in 2012, fog computing has played a dominant role in addressing the quality of service (QoS). However, with the emergence of the internet of things and artificial intelligence technologies, which create a “smart world” where everything is automated, offering quality of service alone is no longer sufficient as it does not offer a satisfactory user experience. Quality of experience (QoE), which satisfies user experience and improves user performance, becomes vital and fog computing remains a key technology. To understand QoE, there was a need to distinguish it from QoS based on stance, scope, perspective, focus, and methods. A systematic literature review was done looking at works that use fog computing to maintain or improve QoE with the focus being on problems being addressed in a paper and how the results contributed to improving QoE. Critical analysis of the review showed that even though strides have been made to improve QoE, open research challenges still exist that require intervention to improve or maintain acceptable QoE in fog computing to satisfy user needs.
{"title":"Fog Computing Quality of Experience: Review and Open Challenges","authors":"W. T. Vambe","doi":"10.4018/ijfc.317110","DOIUrl":"https://doi.org/10.4018/ijfc.317110","url":null,"abstract":"Since its inception in 2012, fog computing has played a dominant role in addressing the quality of service (QoS). However, with the emergence of the internet of things and artificial intelligence technologies, which create a “smart world” where everything is automated, offering quality of service alone is no longer sufficient as it does not offer a satisfactory user experience. Quality of experience (QoE), which satisfies user experience and improves user performance, becomes vital and fog computing remains a key technology. To understand QoE, there was a need to distinguish it from QoS based on stance, scope, perspective, focus, and methods. A systematic literature review was done looking at works that use fog computing to maintain or improve QoE with the focus being on problems being addressed in a paper and how the results contributed to improving QoE. Critical analysis of the review showed that even though strides have been made to improve QoE, open research challenges still exist that require intervention to improve or maintain acceptable QoE in fog computing to satisfy user needs.","PeriodicalId":218786,"journal":{"name":"Int. J. Fog Comput.","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114826421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A number of studies have recently emerged to address the issue of resource allocation in edge computing environments. However, there are few works considering how to optimize resource allocation while satisfying market's requirements in multiagent technique for distributed allocation of Edge resources in distributed control. This study use trading-based multiagent resource allocation model as an allocation mechanism to optimal allocate resources through genetic algorithm in an Edge computing environment. The proposed model supports the optimal process between Edge computing cases to apply and allows Edge buyers and Edge providers both to derive their own pricing strategies and to analyze the respective impact to their welfare. The k-pricing schemes are adjustly to meet the Edge users/providers requirement and constraints set by composed services.
{"title":"Resource Allocation With Multiagent Trading Over the Edge Services","authors":"Yee-Ming Chen, C. Hsieh","doi":"10.4018/ijfc.309138","DOIUrl":"https://doi.org/10.4018/ijfc.309138","url":null,"abstract":"A number of studies have recently emerged to address the issue of resource allocation in edge computing environments. However, there are few works considering how to optimize resource allocation while satisfying market's requirements in multiagent technique for distributed allocation of Edge resources in distributed control. This study use trading-based multiagent resource allocation model as an allocation mechanism to optimal allocate resources through genetic algorithm in an Edge computing environment. The proposed model supports the optimal process between Edge computing cases to apply and allows Edge buyers and Edge providers both to derive their own pricing strategies and to analyze the respective impact to their welfare. The k-pricing schemes are adjustly to meet the Edge users/providers requirement and constraints set by composed services.","PeriodicalId":218786,"journal":{"name":"Int. J. Fog Comput.","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116841548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Edge computing has become a popular paradigm in recent years for reducing network congestion and serving real-time IoT applications by providing services close to end-user devices. It is difficult to develop applications in an edge computing environment due to resource constraints and the diverse and distributed nature of edge computing nodes. The authors compared the performance of monolithic architecture and MicroServices Architecture (MSA) in edge computing environments to determine which architecture can better meet the diverse requirements imposed by edge computing environments. A single application has been developed using both MSA and monolithic architecture for water requirement prediction for irrigation in rice crop. In terms of peak throughput, MSA outperformed monolithic architecture by about 22%, and similarly for peak response times, MSA outperformed monolithic architecture by about 28%. The average CPU usage of MSA is about 49.26% less than the monolithic architecture.
{"title":"Evaluating the Performance of Monolithic and Microservices Architectures in an Edge Computing Environment","authors":"Nitin Rathore, A. Rajavat","doi":"10.4018/ijfc.309139","DOIUrl":"https://doi.org/10.4018/ijfc.309139","url":null,"abstract":"Edge computing has become a popular paradigm in recent years for reducing network congestion and serving real-time IoT applications by providing services close to end-user devices. It is difficult to develop applications in an edge computing environment due to resource constraints and the diverse and distributed nature of edge computing nodes. The authors compared the performance of monolithic architecture and MicroServices Architecture (MSA) in edge computing environments to determine which architecture can better meet the diverse requirements imposed by edge computing environments. A single application has been developed using both MSA and monolithic architecture for water requirement prediction for irrigation in rice crop. In terms of peak throughput, MSA outperformed monolithic architecture by about 22%, and similarly for peak response times, MSA outperformed monolithic architecture by about 28%. The average CPU usage of MSA is about 49.26% less than the monolithic architecture.","PeriodicalId":218786,"journal":{"name":"Int. J. Fog Comput.","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116972286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Energy internet (EI) was proposed to improve the utilization of multiple energy and meet the growing demand for energy. This paper proposes the distributed consensus control algorithm combined with a multi-agent system (MAS) which is applied to distributed generators in the energy internet. By selecting the incremental cost (IC) of each generation unit as the consensus variable, the algorithm is able to solve the conventional centralized economic dispatch (ED) problem in a distributed scheduling manner. The proposed algorithm is veriðed in the MAS layer and through a simulation model of the EI network in the MATLAB software. Simulation results conclude that incremental cost converges to its optimal value whether load demand is varying or generators plug-and-play. Distributed consensus control algorithm can provide better service for EI, it is immune to topological variations and accommodate desired plug-and-play features, and it enables real-time modeling and simulation of complex power systems.
{"title":"Distributed Consensus Based and Network Economic Control of Energy Internet Management","authors":"Yee-Ming Chen, C. Hsieh","doi":"10.4018/ijfc.309140","DOIUrl":"https://doi.org/10.4018/ijfc.309140","url":null,"abstract":"Energy internet (EI) was proposed to improve the utilization of multiple energy and meet the growing demand for energy. This paper proposes the distributed consensus control algorithm combined with a multi-agent system (MAS) which is applied to distributed generators in the energy internet. By selecting the incremental cost (IC) of each generation unit as the consensus variable, the algorithm is able to solve the conventional centralized economic dispatch (ED) problem in a distributed scheduling manner. The proposed algorithm is veriðed in the MAS layer and through a simulation model of the EI network in the MATLAB software. Simulation results conclude that incremental cost converges to its optimal value whether load demand is varying or generators plug-and-play. Distributed consensus control algorithm can provide better service for EI, it is immune to topological variations and accommodate desired plug-and-play features, and it enables real-time modeling and simulation of complex power systems.","PeriodicalId":218786,"journal":{"name":"Int. J. Fog Comput.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130656680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hewan Shrestha, Puviyarai T., Sana Sodanapalli, Chandramohan Dhasarathan
The emerging trend of internet of things in recent times is a blessing for various industries in the world. With the increasing amount of data generated by these devices, it makes it difficult for proper data flow and computation over the regular cloud architecture. Fog computing is a great alternative for cloud computing as it supports computation in devices over a large distributed geographical area, which is a plus for fog computing. Having applications in various domains including healthcare, logistics, design, marketing, manufacturing, and many more, fog computing is a great boon for the future. Evolving fog computing in various domains with different methods and techniques has shaped a clear future for it. Applicability of fog computing in vehicular communications and storage-as-a-service has made the term more popular these days. It is a review of all the possible fog computing-enabled applications and their future scope. It also prepares a basis for further research into fog computing domain-enabled services with low latency and minimum costs.
{"title":"Evolution of Fog Computing Applications, Opportunities, and Challenges: A Systematic Review","authors":"Hewan Shrestha, Puviyarai T., Sana Sodanapalli, Chandramohan Dhasarathan","doi":"10.4018/ijfc.2021010101","DOIUrl":"https://doi.org/10.4018/ijfc.2021010101","url":null,"abstract":"The emerging trend of internet of things in recent times is a blessing for various industries in the world. With the increasing amount of data generated by these devices, it makes it difficult for proper data flow and computation over the regular cloud architecture. Fog computing is a great alternative for cloud computing as it supports computation in devices over a large distributed geographical area, which is a plus for fog computing. Having applications in various domains including healthcare, logistics, design, marketing, manufacturing, and many more, fog computing is a great boon for the future. Evolving fog computing in various domains with different methods and techniques has shaped a clear future for it. Applicability of fog computing in vehicular communications and storage-as-a-service has made the term more popular these days. It is a review of all the possible fog computing-enabled applications and their future scope. It also prepares a basis for further research into fog computing domain-enabled services with low latency and minimum costs.","PeriodicalId":218786,"journal":{"name":"Int. J. Fog Comput.","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123767265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sana Sodanapalli, Hewan Shrestha, Chandramohan Dhasarathan, Puviyarasi T., Sam Goundar
Edge computing is an exciting new approach to network architecture that helps organizations break beyond the limitations imposed by traditional cloud-based networks. It has emerged as a viable and important architecture that supports distributed computing to deploy compute and storage resources closer to the data source. Edge and fog computing addresses three principles of network limitations of bandwidth, latency, congestion, and reliability. The research community sees edge computing at manufacturing, farming, network optimization, workplace safety, improved healthcare, transportation, etc. The promise of this technology will be realized through addressing new research challenges in the IoT paradigm and the design of highly-efficient communication technology with minimum cost and effort.
{"title":"Recent Advances in Edge Computing Paradigms: Taxonomy Benchmarks and Standards for Unconventional Computing","authors":"Sana Sodanapalli, Hewan Shrestha, Chandramohan Dhasarathan, Puviyarasi T., Sam Goundar","doi":"10.4018/ijfc.2021010103","DOIUrl":"https://doi.org/10.4018/ijfc.2021010103","url":null,"abstract":"Edge computing is an exciting new approach to network architecture that helps organizations break beyond the limitations imposed by traditional cloud-based networks. It has emerged as a viable and important architecture that supports distributed computing to deploy compute and storage resources closer to the data source. Edge and fog computing addresses three principles of network limitations of bandwidth, latency, congestion, and reliability. The research community sees edge computing at manufacturing, farming, network optimization, workplace safety, improved healthcare, transportation, etc. The promise of this technology will be realized through addressing new research challenges in the IoT paradigm and the design of highly-efficient communication technology with minimum cost and effort.","PeriodicalId":218786,"journal":{"name":"Int. J. Fog Comput.","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126900276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Advanced technologies are changing the educational and organizational landscape. Technologies such as augmented reality are providing professionals access to technology-enhanced activities that promote greater acquisition of new concepts through immersive learning experiences. Prior research conducted on augmented reality has resulted in findings that demonstrate numerous benefits associated with its use including increasing learner levels of motivation, content knowledge, and critical and problem-solving skills. These tools have been implemented at all levels of education and across a range of professional settings. This article will explore how the inclusion of these tools provide employees access to cutting-edge technologies that promote skill growth and improve efficacy in their professional responsibilities and how fog computing has the capability enhance this technology.
{"title":"Designing Instruction and Professional Development to Support Augmented Reality Activities","authors":"K. Torres, Aubrey L. C. Statti","doi":"10.4018/ijfc.2021010102","DOIUrl":"https://doi.org/10.4018/ijfc.2021010102","url":null,"abstract":"Advanced technologies are changing the educational and organizational landscape. Technologies such as augmented reality are providing professionals access to technology-enhanced activities that promote greater acquisition of new concepts through immersive learning experiences. Prior research conducted on augmented reality has resulted in findings that demonstrate numerous benefits associated with its use including increasing learner levels of motivation, content knowledge, and critical and problem-solving skills. These tools have been implemented at all levels of education and across a range of professional settings. This article will explore how the inclusion of these tools provide employees access to cutting-edge technologies that promote skill growth and improve efficacy in their professional responsibilities and how fog computing has the capability enhance this technology.","PeriodicalId":218786,"journal":{"name":"Int. J. Fog Comput.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130633224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Brain tumor segmentation and detection is one of the most critical parts in the field of medical regions. Tumor is a cancer type that can be visible in any part of the body in case of primary and secondary tumor. The different type of brain tumor is glioma, benign, malignant, meningioma. This research helps in retrieving the tumor region in the brain with the help of 2D MRI images. The system predicts using MATLAB which is a programming platform and analyze the tumor from different method like canny edge, Otsu's binary, fuzzy c-means (FCM), and k-means clustering to improve the borders using the pixel technique. Using convolution neural network (CNN), neural network, and natural language processing, the system detects brain tumor based on the pre-processing and post-processing feature. Moreover, the authors figure out which tumor affected is the most important feature to protect the lifespan in the initial stages. Finally, it acknowledges the result in the mail format to the doctor or patient.
{"title":"Advanced Brain Tumor Detection System","authors":"Monica S. Kumar, Swathi K. Bhat, V. R. Thakare","doi":"10.4018/ijfc.2020070103","DOIUrl":"https://doi.org/10.4018/ijfc.2020070103","url":null,"abstract":"Brain tumor segmentation and detection is one of the most critical parts in the field of medical regions. Tumor is a cancer type that can be visible in any part of the body in case of primary and secondary tumor. The different type of brain tumor is glioma, benign, malignant, meningioma. This research helps in retrieving the tumor region in the brain with the help of 2D MRI images. The system predicts using MATLAB which is a programming platform and analyze the tumor from different method like canny edge, Otsu's binary, fuzzy c-means (FCM), and k-means clustering to improve the borders using the pixel technique. Using convolution neural network (CNN), neural network, and natural language processing, the system detects brain tumor based on the pre-processing and post-processing feature. Moreover, the authors figure out which tumor affected is the most important feature to protect the lifespan in the initial stages. Finally, it acknowledges the result in the mail format to the doctor or patient.","PeriodicalId":218786,"journal":{"name":"Int. J. Fog Comput.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125277030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Yadav, Dr. Gulbakshee Dharmela, Khushali Mistry
Online reviews play a vital role in today's business and commerce. In the world of e-commerce, reviews are the best signs of success and failure. Businesses that have good reviews get a lot of free exposure on websites and pages that have good reviews show up at the top of the search results. Fake reviews are everywhere online. Online fake reviews are the reviews which are written by someone who has not actually used the product or the services. Because of the cut-throat competition, sellers are now willing to resort to unfair means to make their product stand out. This work introduces some supervised machine learning techniques to detect fake online reviews and also be able to block the malicious users who post such reviews.
{"title":"Fake Review Detection Using Machine Learning Techniques","authors":"S. Yadav, Dr. Gulbakshee Dharmela, Khushali Mistry","doi":"10.4018/ijfc.2020070104","DOIUrl":"https://doi.org/10.4018/ijfc.2020070104","url":null,"abstract":"Online reviews play a vital role in today's business and commerce. In the world of e-commerce, reviews are the best signs of success and failure. Businesses that have good reviews get a lot of free exposure on websites and pages that have good reviews show up at the top of the search results. Fake reviews are everywhere online. Online fake reviews are the reviews which are written by someone who has not actually used the product or the services. Because of the cut-throat competition, sellers are now willing to resort to unfair means to make their product stand out. This work introduces some supervised machine learning techniques to detect fake online reviews and also be able to block the malicious users who post such reviews.","PeriodicalId":218786,"journal":{"name":"Int. J. Fog Comput.","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114493885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Kumar, Mohammed Ammar, Shah Abhay Kantilal, V. R. Thakare
Cloud is a collective term for a large number of developments and possibilities. Various data can be stored by the large amount of people onto the cloud storage facility without any bound of limitations as it provides tremendous space. Open systems like Android (Google Apps) still face many day- to-day security threats or attacks. With recent demand, cloud computing has raised security concerns for both service providers and consumers. Major issues like data transfer over wireless network across the globe have to be protected from unauthorized usage over the cloud as altered data can lead to great loss. In this regard, data auditing along with integrity, dynamic capabilities, and privacy preserving, and plays as an important role for preventing data from various cloud attacks which is considered in this work. The work also includes efficient auditor which plays a crucial role in securing the cloud environment. This paper presents a review on the cloud computing concepts and security issues inherent within the context of cloud computing and cloud infrastructure.
{"title":"Advanced Data Storage Security System for Public Cloud","authors":"J. Kumar, Mohammed Ammar, Shah Abhay Kantilal, V. R. Thakare","doi":"10.4018/ijfc.2020070102","DOIUrl":"https://doi.org/10.4018/ijfc.2020070102","url":null,"abstract":"Cloud is a collective term for a large number of developments and possibilities. Various data can be stored by the large amount of people onto the cloud storage facility without any bound of limitations as it provides tremendous space. Open systems like Android (Google Apps) still face many day- to-day security threats or attacks. With recent demand, cloud computing has raised security concerns for both service providers and consumers. Major issues like data transfer over wireless network across the globe have to be protected from unauthorized usage over the cloud as altered data can lead to great loss. In this regard, data auditing along with integrity, dynamic capabilities, and privacy preserving, and plays as an important role for preventing data from various cloud attacks which is considered in this work. The work also includes efficient auditor which plays a crucial role in securing the cloud environment. This paper presents a review on the cloud computing concepts and security issues inherent within the context of cloud computing and cloud infrastructure.","PeriodicalId":218786,"journal":{"name":"Int. J. Fog Comput.","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126472193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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