Towards a replication service for data-intensive fog applications

Hasenburg, Jonathan; Grambow, Martin; Bermbach, David

doi:10.1145/3341105.3374060

Cited by 31 publications

(25 citation statements)

References 20 publications

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“…Tong et al 38 and, to some extent Heintz et al 36 take a similar approach to FogTorch, while 4‐7,35,39‐55 employ a more efficient heuristics approach to solve the formalized optimization problem. Naas et al 56 offer a heuristics‐based solution as well, but place data replicas rather than services, a challenge that is also addressed in References 57,58. Formulating such assignment problems requires complete information about the system upfront, including infrastructure and software implementation details.…”

Section: Related Workmentioning

confidence: 99%

From zero to fog: Efficient engineering of fog‐based Internet of Things applications

2021

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In Internet of Things (IoT) data processing, cloud computing alone does not suffice due to latency constraints, bandwidth limitations, and privacy concerns. By introducing intermediary nodes closer to the edge of the network that offer compute services in proximity to IoT devices, fog computing can reduce network strain and high access latency to application services. While this is the only viable approach to enable efficient IoT applications, the issue of component placement among cloud and intermediary nodes in the fog adds a new dimension to system design. State‐of‐the‐art solutions to this issue rely on simulation or solving a formalized assignment problem through heuristics only, which both have their drawbacks. In this article, we present a five‐step process for designing practical fog‐based IoT applications that combines best practices, simulation, and testbed analysis to converge towards an efficient system architecture. We then apply this process in a smart factory case study. By deploying filtered options to a physical testbed, we show that each step of our process converges towards more efficient application designs.

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Section: Related Workmentioning

confidence: 99%

From zero to fog: Efficient engineering of fog‐based Internet of Things applications

2021

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“…To remedy this, a number of edge computing platforms have been proposed to abstract from the underlying infrastructure. To this end, they employ service offloading techniques, data geo-replication, or resource sharing [3,14,15,27,29].…”

Section: Edge Computingmentioning

confidence: 99%

Towards a Computing Platform for the LEO Edge

Pfandzelter

Hasenburg

Bermbach

2021

Proceedings of the 4th International Workshop on Edge Systems, Analytics and Networking

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The new space race is heating up as private companies such as SpaceX and Amazon are building large satellite constellations in low-earth orbit (LEO) to provide global broadband internet access. As the number of subscribers connected to this access network grows, it becomes necessary to investigate if and how edge computing concepts can be applied to LEO satellite networks.In this paper, we discuss the unique characteristics of the LEO edge and analyze the suitability of three organization paradigms for applications considering developer requirements. We conclude that the serverless approach is the most promising solution, opening up the field for future research. CCS CONCEPTS• Computer systems organization → Heterogeneous (hybrid) systems; Distributed architectures; • Networks → Cloud computing.

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“…Hasenburg et al 14 proposed a middleware architecture to aid programmers in data transmission and DRP inside a fog environment, which employs an F-base data distribution component. Based on division and conquers, Naas et al 15 presented a heuristic method for DRP in fog infrastructure.…”

Section: Related Workmentioning

confidence: 99%

A metaheuristic‐based data replica placement approach for data‐intensive IoT applications in the fog computing environment

2021

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Over the past few years, Internet of Things (IoT) applications have grown rapidly.The data-intensive IoT applications that take advantage of cloud servers for computations and data storage will result in higher latency and other network traffic in the Internet core. IoT applications are characterized by their sensitivity to latency. As an example, delays will result in irreparable damage in the medical and healthcare industries. Cloud servers are no longer necessary because cloud computing utilizes fog nodes that are closer to users. Nodes with different hardware capabilities pose a significant challenge since they differ significantly in latency and traffic reduction. This article presented a metaheuristic-based method using the non-dominated sorting genetic algorithm II for data-intensive IoT applications in fog infrastructure. Besides, we provide a new automatic method for managing data replica transmissions, including deploying them in a fog cloud environment. The proposed solution was evaluated in the iFogSim simulator and compared with two other data replica placement methods in different scenarios. The results showed a decrease in latency and cost for data access and an increase in data availability.

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Towards a replication service for data-intensive fog applications

Cited by 31 publications

References 20 publications

From zero to fog: Efficient engineering of fog‐based Internet of Things applications

From zero to fog: Efficient engineering of fog‐based Internet of Things applications

Towards a Computing Platform for the LEO Edge

A metaheuristic‐based data replica placement approach for data‐intensive IoT applications in the fog computing environment

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