Towards a distributed computing framework for Fog

Jeong, Taeyeol; Chung, Jaeyoon; Hong, James Won‐Ki; Ha, Sangtae

doi:10.1109/fwc.2017.8368528

Cited by 19 publications

(12 citation statements)

References 19 publications

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“…A relevant resilience challenge deals with network disconnection between components of different IoT stages, such as thing, mist, fog, or cloud [16], [114][115][116][117][118][119][120][121]. Therefore, it is necessary to establish mechanisms to ensure resilience to fog-based IoT systems for data transmission [16], [122], such as fault management mechanisms for IoT nodes [16].…”

Section: ) Resiliencementioning

confidence: 99%

A Survey on Trustworthiness for the Internet of Things

Ribeiro

Kamienski

2021

IEEE Access

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IoT systems use sensors to collect data from smart environments and manage resources through data analysis. An IoT system deals with many connected devices with different network and hardware constraints in a real-world scenario. An IoT system needs to handle low-latency data analysis, security threats, internal vulnerabilities, and network disconnections, which cause data loss and incorrect decisions. Trustworthiness (also known as dependability) provides various features for an IoT end-to-end data flow, such as resilience, security, availability, reliability, scalability, maintainability, heterogeneity, hardware resources management, fault management policies, and data quality. This paper presents a survey on trustworthiness and dependability in IoT systems and proposes the Trustworthiness for IoT Framework (TW-IoT) to provide trustworthiness at the data level for mist and fog-based IoT systems. The TW-IoT framework provides data trustworthiness to ensure a continuous and uninterrupted operation of IoT data flow. We also discuss challenges and trade-offs related to data trustworthiness in IoT.

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Section: ) Resiliencementioning

confidence: 99%

A Survey on Trustworthiness for the Internet of Things

Ribeiro

Kamienski

2021

IEEE Access

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“…They have presented the perception of segments and used the term "reversibility" in favor of the application design phase to accept node failures in edge computing. The work in [36] emphasizes fault tolerance by providing the concept of crystal for fog application. Crystal's framework allows programmers to develop application with crystal objects as a building segment.…”

Section: B Fault Tolerancementioning

confidence: 99%

A Decentralized Edge Computing Latency-Aware Task Management Method With High Availability for IoT Applications

Bukhsh¹,

Abdullah

Bajwa

2021

IEEE Access

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Rapid growth of Internet of Things (IoT), and other intelligent devices, introduced different applications which offer real-time latency features; however, it is difficult to handle the large volumes of data produced during the computational process, to adequately complete tasks. The decentralized edge computing process handles the task at the user's end to accomplish latency applications, but recent research adopted centralized methodologies for computing in the edge network, placing additional overhead for cluster management and grouping. In this paper, we formulate an edge nodes group on task arrivals with a decentralized technique to process jobs, in a parallel mode, to complete execution. In addition, high availability will be added to promise effective processing of IoT based applications executed in the edge computing system. In the edge node environment, where resources are restricted, there is a requirement for high availability methods, which can deliver system reliability according to the local device information, without the data of network topology. In this paper, our technique is to enhance network reliability with the help of the edge node's local information, which is executed in the distributed edge computing network, while also proposing a high availability technique to enhance the overall IoT environment. Our proposed Latency Aware Algorithm for Edge Computing with High Availability (LAAECHA) detects edge nodes faults, repairs edge nodes and replaces edge nodes with backups, using a new algorithm in a decentralized mode. Our research results show that the proposed LAAECHA method is more effective than existing methods, ensuring latency-aware IoT applications achieve their deadlines, while significantly reducing network traffic as well as guaranteeing system availability and reliability of the IoT network.

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“…They have introduced concept of phase and used the 'reversibility' in context of application design to tolerate node failure. The study in [34] focuses on providing fault tolerance by providing abstraction of crystal for fog application development. Crystals allow application developers to easily build a sustainable fog application by using crystal instances as a building block.…”

Section: B Reliability and Fault Tolerancementioning

confidence: 99%

A Decentralized Latency-Aware Task Allocation and Group Formation Approach With Fault Tolerance for IoT Applications

et al. 2020

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Development of internet of things (IoT) and smart devices eased life by offering numerous applications targeting to provide real-time low latency services, but they also brought challenges in handling huge data generated from the powerful computations, to get a job done. Decentralized edge computing could help to achieve latency requirements of the applications by executing them closer to the user at edge of network, but most of the current studies actually deployed centralized approaches for cluster computing at edge, which put extra overhead of cluster formation and management. In this article, we propose to group heterogeneous edge nodes on task arrival with a more decentralized method and execute tasks in parallel to meet their deadline. On the other hand, to guarantee successful execution of critical IoT application running in an edge network, fault tolerance has to be significantly considered. For resource limited edge devices, there is a great need for efficient fault tolerance techniques, which can provide reliability based on device's local information, without worrying about overall network topology. In this article, our novel method is to increase task reliability being executed in distributed edge computing environment through finding reliability of an edge node locally, and by providing fault tolerance to increase overall application availability. Our proposed fault tolerance technique works in decentralized mode by executing new algorithms to handle above mentioned problems. Our experiment results show that our approach is effective as well as providing desired goals of achieving deadline for latency-aware IoT applications, with staggering decrease in overall network traffic along with ensuring reliability and availability.

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Towards a distributed computing framework for Fog

Cited by 19 publications

References 19 publications

A Survey on Trustworthiness for the Internet of Things

A Survey on Trustworthiness for the Internet of Things

A Decentralized Edge Computing Latency-Aware Task Management Method With High Availability for IoT Applications

A Decentralized Latency-Aware Task Allocation and Group Formation Approach With Fault Tolerance for IoT Applications

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