Cloud, fog and edge: Cooperation for the future?

Bierzynski, Kay; Escobar, Antonio; Eberl, Matthias

doi:10.1109/fmec.2017.7946409

Cited by 65 publications

(28 citation statements)

References 7 publications

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“…provides the networking and IoT application development environment [37]. Cloud, cloudlets, fog, and edge platforms facilitate the data storage, analysis, and ubiquity in IoT [38].…”

Section: ) Computationmentioning

confidence: 99%

An Empirical Study on System Level Aspects of Internet of Things (IoT)

2020

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Internet of Things (IoT) is an integration of the Sensor, Embedded, Computing, and Communication technologies. The purpose of the IoT is to provide seamless services to anything, anytime at any place. IoT technologies play a crucial role everywhere, which brings the fourth revolution of disruptive technologies after the internet and Information and Communication Technology (ICT). The Research & Development community has predicted that the impact of IoT will be more than the internet and ICT on society, which improves the wellbeing of society and industries. Addressing the predominant system-level design aspects like energy efficiency, robustness, scalability, interoperability, and security issues result in the use of a potential IoT system. This paper presents the current state of art of the functional pillars of IoT and its emerging applications to motivate academicians and researches to develop real-time, energy-efficient, scalable, reliable, and secure IoT applications. This paper summarizes the architecture of IoT, with the contemporary status of IoT architectures. Highlights of the IoT system-level issues to develop more advanced real-time IoT applications have been discussed. Millions of devices exchange information using different communication standards, and interoperability between them is a significant issue. This paper provides the current status of the communication standards and application layer protocols used in IoT with the detailed analysis. The computing paradigms like Cloud, Cloudlet, Fog, and Edge computing facilitate IoT with various services like data offloading, resource and device management, etc. In this paper, an exhaustive analysis of Edge Computing in IoT with different edge computing architectures and existing status are deliberated. The widespread adoption of IoT in society has resulted in privacy and security issues. This paper emphasizes on analyzing the security challenges, privacy and security threats, conventional mitigation techniques, and further scope for IoT security. The features like fewer memory footprints, scheduling, real-time task execution, fewer interrupt, and thread switching latency of Real-Time Operating Systems (RTOS) enables the development of time critical IoT applications. Also, this review offers the analysis of the RTOS's suitable for IoT with the current status and networking stack. Finally, open research issues in IoT system development are discussed.

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“…provides the networking and IoT application development environment [37]. Cloud, cloudlets, fog, and edge platforms facilitate the data storage, analysis, and ubiquity in IoT [38].…”

Section: ) Computationmentioning

confidence: 99%

An Empirical Study on System Level Aspects of Internet of Things (IoT)

2020

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“…The fog computing concept was proposed by Cisco [ 30 , 33 , 34 , 35 , 36 , 37 , 38 ]. Fog computing is also called edge computing by many researchers.…”

Section: Background and Motivationmentioning

confidence: 99%

“…The edge computing [ 26 , 30 , 33 , 34 , 38 ] is the nearest layer which can provide computing capabilities to the end devices. The upper layer of the edge layer is the fog computing layer and the lower layer is the end device layer.…”

Section: Background and Motivationmentioning

confidence: 99%

IMSC-EIoTD: Identity Management and Secure Communication for Edge IoT Devices

Sadique

Rahmani

Johannesson

2020

Sensors

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The Internet of things (IoT) will accommodate several billions of devices to the Internet to enhance human society as well as to improve the quality of living. A huge number of sensors, actuators, gateways, servers, and related end-user applications will be connected to the Internet. All these entities require identities to communicate with each other. The communicating devices may have mobility and currently, the only main identity solution is IP based identity management which is not suitable for the authentication and authorization of the heterogeneous IoT devices. Sometimes devices and applications need to communicate in real-time to make decisions within very short times. Most of the recently proposed solutions for identity management are cloud-based. Those cloud-based identity management solutions are not feasible for heterogeneous IoT devices. In this paper, we have proposed an edge-fog based decentralized identity management and authentication solution for IoT devices (IoTD) and edge IoT gateways (EIoTG). We have also presented a secure communication protocol for communication between edge IoT devices and edge IoT gateways. The proposed security protocols are verified using Scyther formal verification tool, which is a popular tool for automated verification of security protocols. The proposed model is specified using the PROMELA language. SPIN model checker is used to confirm the specification of the proposed model. The results show different message flows without any error.

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“…Experiments showed that fog computing could reduce communication delay and significantly improve cloud computing performance. Bierzynski et al [30] believed that cloud-fog collaboration can solve most problems in IoT and discussed four possible ways to distribute workloads between different levels.…”

Section: Cloud-fog Collaborativementioning

confidence: 99%

Protection of Sensitive Data in Industrial Internet Based on Three-Layer Local/Fog/Cloud Storage

Liu

Yuan

Lai

et al. 2020

Security and Communication Networks

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Industrial Internet technology has developed rapidly, and the security of industrial data has received much attention. At present, industrial enterprises lack a safe and professional data security system. Thus, industries urgently need a complete and effective data protection scheme. This study develops a three-layer framework with local/fog/cloud storage for protecting sensitive industrial data and defines a threat model. For real-time sensitive industrial data, we use the improved local differential privacy algorithm M-RAPPOR to perturb sensitive information. We encode the desensitized data using Reed–Solomon (RS) encoding and then store them in local equipment to realize low cost, high efficiency, and intelligent data protection. For non-real-time sensitive industrial data, we adopt a cloud-fog collaborative storage scheme based on AES-RS encoding to invisibly provide multilayer protection. We adopt the optimal solution of distributed storage in local equipment and the cloud-fog collaborative storage scheme in fog nodes and cloud nodes to alleviate the storage pressure on local equipment and to improve security and recoverability. According to the defined threat model, we conduct a security analysis and prove that the proposed scheme can provide stronger data protection for sensitive data. Compared with traditional methods, this approach strengthens the protection of sensitive information and ensures real-time continuity of open data sharing. Finally, the feasibility of our scheme is validated through experimental evaluation.

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Cloud, fog and edge: Cooperation for the future?

Cited by 65 publications

References 7 publications

An Empirical Study on System Level Aspects of Internet of Things (IoT)

An Empirical Study on System Level Aspects of Internet of Things (IoT)

IMSC-EIoTD: Identity Management and Secure Communication for Edge IoT Devices

Protection of Sensitive Data in Industrial Internet Based on Three-Layer Local/Fog/Cloud Storage

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