Fog Computing as Privacy Enabler

Pallas, Frank; Raschke, Philip; Bermbach, David

doi:10.1109/mic.2020.2979161

Cited by 26 publications

(23 citation statements)

References 12 publications

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“…In this paper, we propose using a detour when routing IoT data to edge and cloud compute nodes. We consider such environments as an ideal case for applying detours because: i) The IoT data are not routed through other (peer) users, but rather through the available edge compute nodes which can actually improve privacy [28], [29]. ii) The difference in the capacity of paths with detours can be so large (e.g., due to the different bandwidth limits between Internet and cloud providers), that utilizing such paths may lead to significant benefits (as shown in Section V).…”

Section: Discussionmentioning

confidence: 99%

edgeRouting: Using Compute Nodes in Proximity to Route IoT Data

Karagiannis

Schulte

2021

IEEE Access

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Due to the proliferation of edge computing, cloud providers have started offering compute nodes at the edge of the network in addition to traditional compute nodes in data centers. So far, various systems have been proposed for processing Internet of Things (IoT) data on both edge and cloud compute nodes in order to reduce the communication latency. However, such systems do not typically consider that the network bandwidth between an edge node and a cloud node can be orders of magnitude higher than the bandwidth between an IoT device and a cloud node. As a result, the IoT data are commonly sent selectively to either edge or cloud nodes disregarding alternative network paths through edge nodes, which may have higher network bandwidth, and lower communication latency. To avoid this, in this paper we analyze the latency of sending data to edge and cloud compute nodes of cloud providers. Based on this analysis, we propose edgeRouting which routes the data through the closest edge compute node. By doing that, edgeRouting exploits both the low propagation delay of nodes at the edge, and the high bandwidth among edge and cloud compute nodes of cloud providers. To evaluate our approach, we perform experiments on a real-world setup with nearby and remote compute nodes of a cloud provider, and we show that edgeRouting reduces the communication latency by up to 55% compared to alternative methods.

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Section: Discussionmentioning

confidence: 99%

edgeRouting: Using Compute Nodes in Proximity to Route IoT Data

Karagiannis

Schulte

2021

IEEE Access

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“…In 2016, several benchmarks utilized on the UK's national supercomputer ARCHER were presented 6 . These benchmarks are a combination of real applications (DFT, molecular mechanics-based, CFD, and climate modeling) developed by the UK Met Office and synthetic benchmarks from the HPC Challenge.…”

Section: A Brief Timeline Of Performance Benchmarkingmentioning

confidence: 99%

“…This is because billions of devices and sensors are connected to the Internet, and the data generated by these sources cannot be transferred and processed in geographically distant cloud data centers without incurring considerable communication delays (4). Therefore, the next disruption in the computing landscape is to distribute infrastructure resources and application services further, to bring computing closer to the edge of the network and data sources (5,6). In this article, we use the term "edge computing" to refer to the use of resources located at the edge of a network, such as routers and gateways or dedicated micro data centers, to either provide applications with acceleration by co-hosting services in cooperation with the cloud or by hosting them natively or entirely on edge resources (7).…”

Section: Introductionmentioning

confidence: 99%

A Survey on Edge Performance Benchmarking

et al. 2021

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Edge computing is the next Internet frontier that will leverage computing resources located near users, sensors, and data stores to provide more responsive services. Therefore, it is envisioned that a large-scale, geographically dispersed, and resource-rich distributed system will emerge and play a key role in the future Internet. However, given the loosely coupled nature of such complex systems, their operational conditions are expected to change significantly over time. In this context, the performance characteristics of such systems will need to be captured rapidly, which is referred to as performance benchmarking, for application deployment, resource orchestration, and adaptive decision-making. Edge performance benchmarking is a nascent research avenue that has started gaining momentum over the past five years. This article first reviews articles published over the past three decades to trace the history of performance benchmarking from tightly coupled to loosely coupled systems. It then systematically classifies previous research to identify the system under test, techniques analyzed, and benchmark runtime in edge performance benchmarking.

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“…This reduces the amount and the distance of data transmitted to the Cloud and consequently reduces the impact of security and privacy issues of IoT applications. 5,43 Fog computing improves time to action and reduces response time, thus responding faster and locally to security and privacy threats. 44,45 Moreover, Fog nodes can serve as proxies of the IoT devices.…”

Section: Fog To Enhance Security and Privacy Of Iot Applicationsmentioning

confidence: 99%

Fog computing security and privacy for the Internet of Thing applications: State‐of‐the‐art

Alzoubi

Osmanaj

Jaradat

et al. 2020

Security and Privacy

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Fog nodes are implemented near to end‐users Internet of Things (IoT) devices, which mitigate the impact of low latency, location awareness, and geographic distribution unsupported features of many IoT applications. Moreover, Fog computing decreases the data offload into the Cloud, which decreases the response time. Despite these benefits, Fog computing faces many challenges in meeting security and privacy requirements. These challenges occur due to the limitations of Fog computing resources. In fact, Fog computing may add new security and privacy issues. Although many papers have discussed the Fog security and privacy issues recently, most of these papers have discussed these issues at a very high level. This paper provides a comprehensive understanding of Fog privacy and security issue. In this survey, we review the literature on Fog computing to draw the state‐of‐the‐art of the security and privacy issues raised by Fog computing. The findings of this survey reveal that studying Fog computing is still in its infant stage. Many questions are yet to be answered to address the privacy and security challenges of Fog computing.

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Fog Computing as Privacy Enabler

Cited by 26 publications

References 12 publications

edgeRouting: Using Compute Nodes in Proximity to Route IoT Data

edgeRouting: Using Compute Nodes in Proximity to Route IoT Data

A Survey on Edge Performance Benchmarking

Fog computing security and privacy for the Internet of Thing applications: State‐of‐the‐art

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