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

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.

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3616 ◽  
Author(s):  
Kai Fan ◽  
Jie Yin ◽  
Kuan Zhang ◽  
Hui Li ◽  
Yintang Yang

Edge computing is an extension of cloud computing that enables messages to be acquired and processed at low cost. Many terminal devices are being deployed in the edge network to sense and deal with the massive data. By migrating part of the computing tasks from the original cloud computing model to the edge device, the message is running on computing resources close to the data source. The edge computing model can effectively reduce the pressure on the cloud computing center and lower the network bandwidth consumption. However, the security and privacy issues in edge computing are worth noting. In this paper, we propose an efficient auto-correction retrieval scheme for data management in edge computing, named EARS-DM. With automatic error correction for the query keywords instead of similar words extension, EARS-DM can tolerate spelling mistakes and reduce the complexity of index storage space. By the combination of TF-IDF value of keywords and the syntactic weight of query keywords, keywords who are more important will obtain higher relevance scores. We construct an R-tree index building with the encrypted keywords and the children nodes of which are the encrypted identifier FID and Bloom filter BF of files who contain this keyword. The secure index will be uploaded to the edge computing and the search phrase will be performed by the edge computing which is close to the data source. Then EDs sort the matching encrypted file identifier FID by relevance scores and upload them to the cloud server (CS). Performance analysis with actual data indicated that our scheme is efficient and accurate.


2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Zhengyang Song ◽  
Yucong Duan ◽  
Shixiang Wan ◽  
Xiaobing Sun ◽  
Quan Zou ◽  
...  

Wide application of the Internet of Things (IoT) system has been increasingly demanding more hardware facilities for processing various resources including data, information, and knowledge. With the rapid growth of generated resource quantity, it is difficult to adapt to this situation by using traditional cloud computing models. Fog computing enables storage and computing services to perform at the edge of the network to extend cloud computing. However, there are some problems such as restricted computation, limited storage, and expensive network bandwidth in Fog computing applications. It is a challenge to balance the distribution of network resources. We propose a processing optimization mechanism of typed resources with synchronized storage and computation adaptation in Fog computing. In this mechanism, we process typed resources in a wireless-network-based three-tier architecture consisting of Data Graph, Information Graph, and Knowledge Graph. The proposed mechanism aims to minimize processing cost over network, computation, and storage while maximizing the performance of processing in a business value driven manner. Simulation results show that the proposed approach improves the ratio of performance over user investment. Meanwhile, conversions between resource types deliver support for dynamically allocating network resources.


2020 ◽  
Author(s):  
Tanweer Alam

<p>The fog computing is the emerging technology to compute, store, control and connecting smart devices with each other using cloud computing. The Internet of Things (IoT) is an architecture of uniquely identified interrelated physical things, these physical things are able to communicate with each other and can transmit and receive information. <a>This research presents a framework of the combination of the Internet of Things (IoT) and Fog computing. The blockchain is also the emerging technology that provides a hyper, distributed, public, authentic ledger to record the transactions. Blockchains technology is a secured technology that can be a boon for the next generation computing. The combination of fog, blockchains, and IoT creates a new opportunity in this area. In this research, the author presents a middleware framework based on the blockchain, fog, and IoT. The framework is implemented and tested. The results are found positive. </a></p>


Author(s):  
Anshu Devi ◽  
Ramesh Kait ◽  
Virender Ranga

Fog computing is a term coined by networking giant Cisco. It is a new paradigm that extends the cloud computing model by conferring computation, storage, and application services at the periphery of networks. Fog computing is a gifted paradigm of cloud computing that facilitates the mobility, portability, heterogeneity, and processing of voluminous data. These distinct features of fog help to reduce latency and make it suitable for location-sensitive applications. Fog computing features raise new security concerns and challenges. The existing cloud security has not been implemented directly due to mobility, heterogeneity of fog nodes. As we know, IoT has to process large amount of data quickly; therefore, it has various functionality-driven applications that escalate security concerns. The primary aim of this chapter is to present the most recent security aspects such as authentication and trust, reputation-based trust model, rogue fog node and authentication at different level, security threats, challenges, and also highlights the future aspects of fog.


Author(s):  
Priyanka Gaba ◽  
Ram Shringar Raw

VANET, a type of MANET, connects vehicles to provide safety and non-safety features to the drivers and passengers by exchanging valuable data. As vehicles on road are increasing to handle such data cloud computing, functionality is merged with vehicles known as Vehicular Cloud Computing(VCC) to serve VANET with computation, storage, and networking functionalities. But Cloud, a centralized server, does not fit well for vehicles needing high-speed processing, low latency, and more security. To overcome these limitations of Cloud, Fog computing was evolved, extending the functionality of cloud computing model to the edge of the network. This works well for real time applications that need fast response, saves network bandwidth, and is a reliable, secure solution. An application of Fog is with vehicles known as Vehicular Fog Computing (VFC). This chapter discusses cloud computing technique and its benefits and drawbacks, detailed comparison between VCC and VFC, applications of Fog Computing, its security, and forensic challenges.


Author(s):  
Akashdeep Bhardwaj

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.


Author(s):  
Meltem Mutluturk ◽  
Burcu Kor ◽  
Bilgin Metin

The development of information and communication technologies (ICT) has led to many innovative technologies. The integration of technologies such as the internet of things (IoT), cloud computing, and machine learning concepts have given rise to Industry 4.0. Fog and edge computing have stepped in to fill the areas where cloud computing is inadequate to ensure these systems work quickly and efficiently. The number of connected devices has brought about cybersecurity issues. This study reviewed the current literature regarding edge/fog-based cybersecurity in IoT to display the current state.


2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Vasileios Moysiadis ◽  
Panagiotis Sarigiannidis ◽  
Ioannis Moscholios

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.


Electronics ◽  
2018 ◽  
Vol 7 (11) ◽  
pp. 309 ◽  
Author(s):  
Hind Bangui ◽  
Said Rakrak ◽  
Said Raghay ◽  
Barbora Buhnova

Cloud computing has significantly enhanced the growth of the Internet of Things (IoT) by ensuring and supporting the Quality of Service (QoS) of IoT applications. However, cloud services are still far from IoT devices. Notably, the transmission of IoT data experiences network issues, such as high latency. In this case, the cloud platforms cannot satisfy the IoT applications that require real-time response. Yet, the location of cloud services is one of the challenges encountered in the evolution of the IoT paradigm. Recently, edge cloud computing has been proposed to bring cloud services closer to the IoT end-users, becoming a promising paradigm whose pitfalls and challenges are not yet well understood. This paper aims at presenting the leading-edge computing concerning the movement of services from centralized cloud platforms to decentralized platforms, and examines the issues and challenges introduced by these highly distributed environments, to support engineers and researchers who might benefit from this transition.


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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