A Hybrid Fog Architecture: Improving the Efficiency in IoT-based Smart Parking Systems

2019 ◽  
Vol 12 ◽  
Author(s):  
Bhawna Suri ◽  
Pijush Kanti Dutta Pramanik ◽  
Shweta Taneja
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Real World ◽  
Fog Computing ◽  
Shopping Malls ◽  
Communication Latency ◽  
Cloud Architecture ◽  
Smart Parking ◽  
Real Time Applications ◽  
Simulation Results

Background: The abundant use of personal vehicles has raised the challenge of parking the vehicle in a crowded place such as shopping malls. To help the driver with efficient and trouble-free parking, a smart and innovative parking assistance system is required. In addition to discussing the basics of smart parking, Internet of Things (IoT), Cloud computing, and Fog computing, this chapter proposes an IoT-based smart parking system for shopping malls. Methods: To process the IoT data, a hybrid Fog architecture is adopted, to reduce the latency, where the Fog nodes are connected across the hierarchy. The advantages of this auxiliary connection are discussed critically by comparing with other Fog architectures (hierarchical and P2P). An algorithm is defined to support the proposed architecture and is implemented on two real-world use-cases having requirements of identifying the nearest free car parking slot. The implementation is simulated for a single mall scenario as well as for a campus with multiple malls with parking areas spread across them. Results: The simulation results have proved that our proposed architecture shows lower latency as compared to the traditional smart parking systems that use Cloud architecture. Conclusion: The hybrid Fog architecture minimizes communication latency significantly. Hence, the proposed architecture can be suitably applied for other IoT-based real-time applications.

Proposed Back Propagation Deep Neural Network for Intrusion Detection in Internet of Things Fog Computing

2021 ◽  
Vol 9 (4) ◽  
pp. 464-469
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Intrusion Detection ◽  
Fog Computing ◽  
Denial Of Service ◽  
Back Propagation ◽  
Security And Privacy ◽  
Brute Force ◽  
Iot Platform ◽  
Proposed Model

Internet of things (IoT) is an emerging concept which aims to connect billions of devices with each other anytime regardless of their location. Sadly, these IoT devices do not have enough computing resources to process huge amount of data. Therefore, Cloud computing is relied on to provide these resources. However, cloud computing based architecture fails in applications that demand very low and predictable latency, therefore the need for fog computing which is a new paradigm that is regarded as an extension of cloud computing to provide services between end users and the cloud user. Unfortunately, Fog-IoT is confronted with various security and privacy risks and prone to several cyberattacks which is a serious challenge. The purpose of this work is to present security and privacy threats towards Fog-IoT platform and discuss the security and privacy requirements in fog computing. We then proceed to propose an Intrusion Detection System (IDS) model using Standard Deep Neural Network's Back Propagation algorithm (BPDNN) to mitigate intrusions that attack Fog-IoT platform. The experimental Dataset for the proposed model is obtained from the Canadian Institute for Cybersecurity 2017 Dataset. Each instance of the attack in the dataset is separated into separate files, which are DoS (Denial of Service), DDoS (Distributed Denial of Service), Web Attack, Brute Force FTP, Brute Force SSH, Heartbleed, Infiltration and Botnet (Bot Network) Attack. The proposed model is trained using a 3-layer BP-DNN

scholarly journals IoT-Fog A Communication Framework using Blockchain in the Internet of Things

2020 ◽  
Author(s):  
Tanweer Alam
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Fog Computing ◽  
Emerging Technology ◽  
Smart Devices ◽  
The Internet ◽  
Next Generation ◽  
Communication Framework ◽  
Generation Computing ◽  
The Internet Of Things

<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>

Security and Privacy Issues in IoT

2019 ◽  
pp. 129-156
Author(s):  
S. R. Mani Sekhar ◽  
Sharmitha S. Bysani ◽  
Vasireddy Prabha Kiranmai
Keyword(s):  
Cloud Computing ◽  
Information Systems ◽  
Internet Of Things ◽  
Case Studies ◽  
Communication Systems ◽  
Fog Computing ◽  
Security And Privacy ◽  
Privacy Issues

Security and privacy issues are the challenging areas in the field of internet of things (IoT) and fog computing. IoT and fog has become an involving technology allowing major changes in the field of information systems and communication systems. This chapter provides the introduction of IoT and fog technology with a brief explanation of how fog is overcoming the challenges of cloud computing. Thereafter, the authors discuss the different security and privacy issues and its related solutions. Furthermore, they present six different case studies which will help the reader to understand the platform of IoT in fog.

Vehicular Cloud and Fog Computing Architecture, Applications, Services, and Challenges

2020 ◽  
pp. 268-296
Author(s):  
Priyanka Gaba ◽  
Ram Shringar Raw
Keyword(s):  
Cloud Computing ◽  
High Speed ◽  
Fog Computing ◽  
Detailed Comparison ◽  
Fast Response ◽  
Computing Technique ◽  
Vehicular Cloud ◽  
Network Bandwidth ◽  
Real Time Applications ◽  
Safety Features

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.

Confidentiality and Safekeeping Problems and Techniques in Fog Computing

2021 ◽  
pp. 1855-1873
Author(s):  
Nida Kauser Khanum ◽  
Pankaj Lathar ◽  
G. M. Siddesh
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Fog Computing ◽  
Video Stream ◽  
Security And Privacy ◽  
Surveillance Video ◽  
Speech Data ◽  
Real Time Applications ◽  
Privacy Issues ◽  
Intrusion Detection And Prevention

Fog computing is an extension of cloud computing, and it is one of the most important architypes in the current world. Fog computing is like cloud computing as it provides data storage, computation, processing, and application services to end-users. In this chapter, the authors discuss the security and privacy issues concerned with fog computing. The issues present in cloud are also inherited by fog computing, but the same methods available for cloud computing are not applicable to fog computing due to its decentralized nature. The authors also discuss a few real-time applications like healthcare systems, intelligent food traceability, surveillance video stream processing, collection, and pre-processing of speech data. Finally, the concept of decoy technique and intrusion detection and prevention technique is covered.

scholarly journals A Novel Fog-IoT based Framework for Improving Performance of Cloud Computing

2019 ◽  
Vol 8 (12S) ◽  
pp. 889-895
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Secure Communication ◽  
Fog Computing ◽  
Cloud Service ◽  
Raspberry Pi ◽  
New Paradigm ◽  
Privacy And Security ◽  
Security Issues ◽  
Iot Devices

Internet-of-Things (IoT) has been considered as a fundamental part of our day by day existence with billions of IoT devices gathering information remotely and can interoperate within the current Internet framework. Fog computing is nothing but cloud computing to the extreme of network security. It provides computation and storage services via CSP (Cloud Service Provider) to end devices in the Internet of Things (IoT). Fog computing allows the data storing and processing any nearby network devices or nearby cloud endpoint continuum. Using fog computing, the designer can reduce the computation architecture of the IoT devices. Unfortunitily, this new paradigm IoT-Fog faces numerous new privacy and security issues, like authentication and authorization, secure communication, information confidentiality. Despite the fact that the customary cloud-based platform can even utilize heavyweight cryptosystem to upgrade security, it can't be performed on fog devices drectly due to reseource constraints. Additionally, a huge number of smart fog devices are fiercely disseminated and situated in various zones, which expands the danger of being undermined by some pernicious gatherings. Trait Based Encryption (ABE) is an open key encryption conspire that enables clients to scramble and unscramble messages dependent on client qualities, which ensures information classification and hearty information get to control. Be that as it may, its computational expense for encryption and unscrambling stage is straightforwardly corresponding to the multifaceted nature of the arrangements utilized. The points is to assess the planning, CPU burden, and memory burden, and system estimations all through each phase of the cloud-to-things continuum amid an analysis for deciding highlights from a finger tapping exercise for Parkinson's Disease patients. It will be appeared there are confinements to the proposed testbeds when endeavoring to deal with upwards of 35 customers at the same time. These discoveries lead us to a proper conveyance of handling the leaves the Intel NUC as the most suitable fog gadget. While the Intel Edison and Raspberry Pi locate a superior balance at in the edge layer, crossing over correspondence conventions and keeping up a self-mending network topology for "thing" devices in the individual territory organize.

scholarly journals An Edge-Fog-Cloud Architecture of Streaming Analytics for Internet of Things Applications

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3594 ◽  
Author(s):  
Hung Cao ◽  
Monica Wachowicz
Keyword(s):  
Internet Of Things ◽  
Data Streams ◽  
Urban Governance ◽  
Smart Cities ◽  
Data Driven ◽  
Business Decisions ◽  
Cloud Architecture ◽  
Smart Parking

Exploring Internet of Things (IoT) data streams generated by smart cities means not only transforming data into better business decisions in a timely way but also generating long-term location intelligence for developing new forms of urban governance and organization policies. This paper proposes a new architecture based on the edge-fog-cloud continuum to analyze IoT data streams for delivering data-driven insights in a smart parking scenario.

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