Feasibility of Fog Computing

Varghese, Blesson; Wang, Nan; Nikolopoulos, Dimitrios S.; Buyya, Rajkumar

doi:10.1007/978-3-030-43795-4_5

Cited by 47 publications

(42 citation statements)

References 22 publications

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“…First, it brings about little delay. As introduced in [7–9], the two‐tier architecture, compared to the cloud‐only architecture, can reduce delay by about 20%, and can even reduce by

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50% with the increasing number of real‐time IoT systems. Since the two‐tier framework can utilise calculation and storage capabilities of fog nodes themselves, it makes local decisions and feedbacks to the IoT systems in time.…”

Section: Introductionmentioning

confidence: 99%

Workload scheduling toward worst‐case delay and optimal utility for single‐hop Fog‐IoT architecture

et al. 2018

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“…First, it brings about little delay. As introduced in [7–9], the two‐tier architecture, compared to the cloud‐only architecture, can reduce delay by about 20%, and can even reduce by

≃

Section: Introductionmentioning

confidence: 99%

Workload scheduling toward worst‐case delay and optimal utility for single‐hop Fog‐IoT architecture

et al. 2018

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“…The authors of [122] have considered the fog computing architecture theoretically and mathematically while comparing the performance of fog computing paradigm with traditional cloud computing framework based on service latency and energy consumption. Fog computing reduces the data traffic between cloud and network edge by 90% and average response time for a user by 20% when compared with cloud-only model [123]. Authors in [124] have discussed the definition and concept of fog computing in-depth, comparing it with similar concepts such as mobile-edge computing (MEC) and mobile cloud computing (MCC).…”

Section: B Fog Computing Architecturementioning

confidence: 99%

A Survey on IoT Security: Application Areas, Security Threats, and Solution Architectures

et al. 2019

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The Internet of Things (IoT) is the next era of communication. Using the IoT, physical objects can be empowered to create, receive, and exchange data in a seamless manner. Various IoT applications focus on automating different tasks and are trying to empower the inanimate physical objects to act without any human intervention. The existing and upcoming IoT applications are highly promising to increase the level of comfort, efficiency, and automation for the users. To be able to implement such a world in an evergrowing fashion requires high security, privacy, authentication, and recovery from attacks. In this regard, it is imperative to make the required changes in the architecture of the IoT applications for achieving end-to-end secure IoT environments. In this paper, a detailed review of the security-related challenges and sources of threat in the IoT applications is presented. After discussing the security issues, various emerging and existing technologies focused on achieving a high degree of trust in the IoT applications are discussed. Four different technologies, blockchain, fog computing, edge computing, and machine learning, to increase the level of security in IoT are discussed. INDEX TERMS Internet of Things (IoT), IoT security, blockchain, fog computing, edge computing, machine learning, IoT applications, distributed systems.

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“…In a nutshell, the significance of cloudlets can be witnessed in latency-sensitive applications, such as real-time cognitive assistance, AR, face recognition, and location-aware online games, in handheld devices. Varghese in [64] tested a Pokemon game in which locations can be updated constantly using GPS coordinates. Users must collect geographically distributed Pokemons and train them virtually for battles, locate the movement of peers, and create high-value profiles.…”

Section: A Lr In Cloudletsmentioning

confidence: 99%

“…Applications such as the Internet of vehicles [71], the Internet of sensors [72], and the Internet of mobile phones [25], are ubiquitous. Such technologies and many other are advancing toward a future interaction paradigm shift known as 5G [64], which can create data in bulks requiring increased bandwidth and considerable processing. Cloudlets at the leading edge have the potential to meet the emerging needs of future technologies.…”

Section: ) Cloudlet-assisted Sdnmentioning

confidence: 99%

Cloudlet Computing: Recent Advances, Taxonomy, and Challenges

et al. 2021

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A cloudlet is an emerging computing paradigm that is designed to meet the requirements and expectations of the Internet of things (IoT) and tackle the conventional limitations of a cloud (e.g., high latency). The idea is to bring computing resources (i.e., storage and processing) to the edge of a network. This article presents a taxonomy of cloudlet applications, outlines cloudlet utilities, and describes recent advances, challenges, and future research directions. Based on the literature, a unique taxonomy of cloudlet applications is designed. Moreover, a cloudlet computation offloading application for augmenting resourceconstrained IoT devices, handling compute-intensive tasks, and minimizing the energy consumption of related devices is explored. This study also highlights the viability of cloudlets to support smart systems and applications, such as augmented reality, virtual reality, and applications that require high-quality service. Finally, the role of cloudlets in emergency situations, hostile conditions, and in the technological integration of future applications and services is elaborated in detail. INDEX TERMS Cloud computing, Edge computing, Cloudlets, Internet of things, Computation offloading, Smart city, Smart health.

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Feasibility of Fog Computing

Cited by 47 publications

References 22 publications

Workload scheduling toward worst‐case delay and optimal utility for single‐hop Fog‐IoT architecture

Workload scheduling toward worst‐case delay and optimal utility for single‐hop Fog‐IoT architecture

A Survey on IoT Security: Application Areas, Security Threats, and Solution Architectures

Cloudlet Computing: Recent Advances, Taxonomy, and Challenges

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