scholarly journals Data Deduplication for Efficient Storage on Cloud using Fog Computing Paradigm

2020 ◽  
Vol 9 (1) ◽  
pp. 812-815
Keyword(s):  
Cloud Computing ◽  
Data Compression ◽  
Distributed System ◽  
Fog Computing ◽  
Geographic Area ◽  
Cloud Services ◽  
Data Deduplication ◽  
Computing Paradigm ◽  
Efficient Storage ◽  
Large Geographic Area

Cloud services have taken the IT world by storm by making its services available to everyone over large geographic area. With the increasing amount of data generate every minute it has become increasing difficult to manage resources and the storage. Thus, data compression techniques like data de duplication that aims at executing the redundancy of data and forming chunks of data that can be stored on a distributed system can be proved to a logistic solution. But when it comes to cloud problems like security has always been a major issue. In order to eliminate these challenges, we need to implement a layer of fog computing they would deal with the shortcomings of cloud computing and at the same time present a filtration front before the incoming data.

scholarly journals Fog-Based CDN Framework for Minimizing Latency of Web Services Using Fog-Based HTTP Browser

2021 ◽  
Vol 13 (12) ◽  
pp. 320
Author(s):  
Ahmed H. Ibrahim ◽  
Zaki T. Fayed ◽  
Hossam M. Faheem
Keyword(s):  
Cloud Computing ◽  
Web Services ◽  
Fog Computing ◽  
Partial Solution ◽  
Cloud Services ◽  
Network Layer ◽  
Cloud Data ◽  
Download Time ◽  
Computing Paradigm ◽  
Cloud Servers

Cloud computing has been a dominant computing paradigm for many years. It provides applications with computing, storage, and networking capabilities. Furthermore, it enhances the scalability and quality of service (QoS) of applications and offers the better utilization of resources. Recently, these advantages of cloud computing have deteriorated in quality. Cloud services have been affected in terms of latency and QoS due to the high streams of data produced by many Internet of Things (IoT) devices, smart machines, and other computing devices joining the network, which in turn affects network capabilities. Content delivery networks (CDNs) previously provided a partial solution for content retrieval, availability, and resource download time. CDNs rely on the geographic distribution of cloud servers to provide better content reachability. CDNs are perceived as a network layer near cloud data centers. Recently, CDNs began to perceive the same degradations of QoS due to the same factors. Fog computing fills the gap between cloud services and consumers by bringing cloud capabilities close to end devices. Fog computing is perceived as another network layer near end devices. The adoption of the CDN model in fog computing is a promising approach to providing better QoS and latency for cloud services. Therefore, a fog-based CDN framework capable of reducing the load time of web services was proposed in this paper. To evaluate our proposed framework and provide a complete set of tools for its use, a fog-based browser was developed. We showed that our proposed fog-based CDN framework improved the load time of web pages compared to the results attained through the use of the traditional CDN. Different experiments were conducted with a simple network topology against six websites with different content sizes along with a different number of fog nodes at different network distances. The results of these experiments show that with a fog-based CDN framework offloading autonomy, latency can be reduced by 85% and enhance the user experience of websites.

Examining IoT's Applications Using Cloud Services

2018 ◽  
pp. 147-163 ◽  
Author(s):  
Saravanan K ◽  
P. Srinivasan
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Distributed Computing ◽  
Knowledge Sharing ◽  
Effective Communication ◽  
Cloud Services ◽  
On Demand ◽  
Computing Paradigm ◽  
Iot Devices ◽  
And Storage

Cloud IoT has evolved from the convergence of Cloud computing with Internet of Things (IoT). The networked devices in the IoT world grow exponentially in the distributed computing paradigm and thus require the power of the Cloud to access and share computing and storage for these devices. Cloud offers scalable on-demand services to the IoT devices for effective communication and knowledge sharing. It alleviates the computational load of IoT, which makes the devices smarter. This chapter explores the different IoT services offered by the Cloud as well as application domains that are benefited by the Cloud IoT. The challenges on offloading the IoT computation into the Cloud are also discussed.

A Cloud Trusting Mechanism Based on Resource Ranking

2020 ◽  
pp. 130-155
Author(s):  
Ajai K. Daniel
Keyword(s):  
Cloud Computing ◽  
Resource Management ◽  
Service Selection ◽  
Cloud Service ◽  
Cloud Services ◽  
Storage And Retrieval ◽  
Computing Paradigm ◽  
Efficient Resource ◽  
Software And Hardware ◽  
Cloud User

The cloud-based computing paradigm helps organizations grow exponentially through means of employing an efficient resource management under the budgetary constraints. As an emerging field, cloud computing has a concept of amalgamation of database techniques, programming, network, and internet. The revolutionary advantages over conventional data computing, storage, and retrieval infrastructures result in an increase in the number of organizational services. Cloud services are feasible in all aspects such as cost, operation, infrastructure (software and hardware) and processing. The efficient resource management with cloud computing has great importance of higher scalability, significant energy saving, and cost reduction. Trustworthiness of the provider significantly influences the possible cloud user in his selection of cloud services. This chapter proposes a cloud service selection model (CSSM) for analyzing any cloud service in detail with multidimensional perspectives.

Novel Taxonomy to Select Fog Products and Challenges Faced in Fog Environments

2021 ◽  
pp. 2558-2571
Author(s):  
Akashdeep Bhardwaj
Keyword(s):  
Cloud Computing ◽  
Distributed Computing ◽  
High Speed ◽  
Low Cost ◽  
Fog Computing ◽  
Research Work ◽  
Cloud Services ◽  
Smart Devices ◽  
Viable Solution ◽  
Last Mile

This article describes how the rise of fog computing to improve cloud computing performance and the acceptance of smart devices is slowly but surely changing our future and shaping the computing environment around us. IoT integrated with advances in low cost computing, storage and power, along with high speed networks and big data, supports distributed computing. However, much like cloud computing, which are under constant security attacks and issues, distributed computing also faces similar challenges and security threats. This can be mitigated to a great extent using fog computing, which extends the limits of Cloud services to the last mile edge near to the nodes and networks, thereby increasing the performance and security levels. Fog computing also helps increase the reach and comes across as a viable solution for distributed computing. This article presents a review of the academic literature research work on the Fog Computing. The authors discuss the challenges in Fog environment and propose a new taxonomy.

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 An IoT-Based Fog Computing Model

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2783 ◽  
Author(s):  
Kun Ma ◽  
Antoine Bagula ◽  
Clement Nyirenda ◽  
Olasupo Ajayi
Keyword(s):  
Cloud Computing ◽  
Fog Computing ◽  
Physical Distance ◽  
Cloud Services ◽  
Daily Lives ◽  
Service Computing ◽  
Network Bandwidth ◽  
Computing Model ◽  
Data Source ◽  
The Internet Of Things

The internet of things (IoT) and cloud computing are two technologies which have recently changed both the academia and industry and impacted our daily lives in different ways. However, despite their impact, both technologies have their shortcomings. Though being cheap and convenient, cloud services consume a huge amount of network bandwidth. Furthermore, the physical distance between data source(s) and the data centre makes delays a frequent problem in cloud computing infrastructures. Fog computing has been proposed as a distributed service computing model that provides a solution to these limitations. It is based on a para-virtualized architecture that fully utilizes the computing functions of terminal devices and the advantages of local proximity processing. This paper proposes a multi-layer IoT-based fog computing model called IoT-FCM, which uses a genetic algorithm for resource allocation between the terminal layer and fog layer and a multi-sink version of the least interference beaconing protocol (LIBP) called least interference multi-sink protocol (LIMP) to enhance the fault-tolerance/robustness and reduce energy consumption of a terminal layer. Simulation results show that compared to the popular max–min and fog-oriented max–min, IoT-FCM performs better by reducing the distance between terminals and fog nodes by at least 38% and reducing energy consumed by an average of 150 KWh while being at par with the other algorithms in terms of delay for high number of tasks.

scholarly journals Towards Distributed Data Management in Fog Computing

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Vasileios Moysiadis ◽  
Panagiotis Sarigiannidis ◽  
Ioannis Moscholios
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Large Scale ◽  
Fog Computing ◽  
Cloud Services ◽  
Smart Devices ◽  
Distributed Data ◽  
Storage Allocation ◽  
Huge Amount ◽  
Distributed Data Storage

In the emerging area of the Internet of Things (IoT), the exponential growth of the number of smart devices leads to a growing need for efficient data storage mechanisms. Cloud Computing was an efficient solution so far to store and manipulate such huge amount of data. However, in the next years it is expected that Cloud Computing will be unable to handle the huge amount of the IoT devices efficiently due to bandwidth limitations. An arising technology which promises to overwhelm many drawbacks in large-scale networks in IoT is Fog Computing. Fog Computing provides high-quality Cloud services in the physical proximity of mobile users. Computational power and storage capacity could be offered from the Fog, with low latency and high bandwidth. This survey discusses the main features of Fog Computing, introduces representative simulators and tools, highlights the benefits of Fog Computing in line with the applications of large-scale IoT networks, and identifies various aspects of issues we may encounter when designing and implementing social IoT systems in the context of the Fog Computing paradigm. The rationale behind this work lies in the data storage discussion which is performed by taking into account the importance of storage capabilities in modern Fog Computing systems. In addition, we provide a comprehensive comparison among previously developed distributed data storage systems which consist of a promising solution for data storage allocation in Fog Computing.

From Cloud Computing to Fog Computing

2018 ◽  
Vol 1 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Sanjay P. Ahuja ◽  
Niharika Deval
Keyword(s):  
Cloud Computing ◽  
Fog Computing ◽  
Cost Savings ◽  
End Users ◽  
Internet Technology ◽  
Future Research ◽  
Computing Paradigm ◽  
Close Proximity ◽  
Iot Devices ◽  
Communication Control

This article describes how in recent years, Cloud Computing has emerged as a fundamental computing paradigm that has significantly changed the approach of enterprises as well as end users towards implementation of Internet technology. The key characteristics such as on-demand resource provision, scalability, rapid elasticity, higher flexibility, and significant cost savings have influenced enterprises of all sizes in the wide and successful adoption of Cloud Computing. Despite numerous advantages, Cloud Computing has its fair share of downsides as well. One of those major concerns is latency issues which has relevance to the Internet of Things (IoT). A new computing paradigm has been proposed by Cisco in early 2014 and termed 'Fog Computing'. Fog Computing otherwise known as Edge Computing is the integration of Cloud Computing and IoT. Being located in close proximity to the IoT devices, the Fog assists with latency requirements of IoT related applications. It also meets the data processing needs of IoT devices which are resource constrained by bringing computation, communication, control and storage closer to the end users. Clouds continue to offer support for data analytics. One can think of the IoT-Fog-Cloud as being part of a continuum. This article surveys the current literature on Fog Computing and provides a discussion on the background, details and architecture of Fog Computing, as well as the application areas of Fog Computing. The article concludes with some recommendations in the areas of future research.

scholarly journals A survey on fog computing: research challenges in security and privacy issues

2018 ◽  
Vol 7 (2.7) ◽  
pp. 335 ◽  
Author(s):  
T Veerraju ◽  
Dr K. Kiran Kumar
Keyword(s):  
Fog Computing ◽  
Cloud Services ◽  
Security And Privacy ◽  
Limited Resources ◽  
Privacy And Security ◽  
Computing Paradigm ◽  
Is Security ◽  
Real Time Applications ◽  
And Storage ◽  
Privacy Issues

With the rapid advancement of Internet of Things has enabled to combine the intercommunication and interconnection between seamless networks. Cloud computing provides backend solutions and one among the most prominent technologies for the users, still cannot be solved all the problems such as latency of real time applications. However, a new computing paradigm comes in to the picture. Many of the researchers focused on this exemplar known as Fog/Edge computing, which has been planned to the extension of cloud services. Fog provides the services to the edge of the networks, which makes communication, computation and storage for end users through fog devices and for servers like controllers. We analyze the study, which aims to augment low bandwidth, latency along with the privacy and security.   The major problem in the Fog computing is security due to the limited resources. In this paper, we investigated the protection issues and confrontation of Fog and also provide countermeasures on security for different attacks. We focused the future security directions and challenges to address in fog networks.

scholarly journals Fog Computing-Security Platform for IoT and Cloud in-Healthcare System

2019 ◽  
Vol 9 (2) ◽  
pp. 4419-4424
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Service Management ◽  
New Technology ◽  
Fog Computing ◽  
Cloud Services ◽  
Third Party ◽  
Selection System ◽  
Search Tool

The introduction of cloud computing has revolutionized business and technology. Cloud computing has merged technology and business creating an almost indistinguishable framework. Cloud computing has utilized various techniques that have been vital in reshaping the way computers are used in business, IT, and education. Cloud computing has replaced the distributed system of using computing resources to a centralized system where resources are easily shared between user and organizations located in different geographical locations. Traditionally the resources are usually stored and managed by a third-party, but the process is usually transparent to the user. The new technology led to the introduction of various user needs such as to search the cloud and associated databases. The development of a selection system used to search the cloud such as in the case of ELECTRE IS and Skyline; this research will develop a system that will be used to manage and determine the quality of service constraints of these new systems with regards to networked cloud computing. The method applied will mimic the various selection system in JAVA and evaluate the Quality of service for multiple cloud services. The FogTorch search tool will be used for quality service management of three cloud services.

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