A Rapid Testing Framework for a Mobile Cloud

Balasubramanian, Daniel; Dubey, Abhishek; Otte, William R.; Emfinger, William; Kumar, Pranav Srinivas; Karsai, Gábor

doi:10.1109/rsp.2014.6966903

Cited by 13 publications

(6 citation statements)

References 11 publications

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“…Yet unlike MockFog, these testbeds can only simulate realistic network conditions, not the constrained compute capabilities of fog nodes, especially at the edge. Balasubramanian et al 74 present a testbed for fog applications that facilitates emulating these constraints but requires physical hardware for each node rather than cheaper virtual machines.…”

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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“…Consequently, this challenge has been a key research topic in the last few years. On the one hand, there are static solutions using upfront best practices [103,52,71,112], simulation [60,59,51,67,23,116,129,107,39,115,46], testbed evaluation [55,84,32,37,84,32,10,35,7,78], a combination of those [105,110], or formalized assignment problems [34,24,25,92,47,5,61,72,126,134,65]. On the other hand, dynamic approaches using centralized schedulers [14,121,81,36,6,91,87,135,98,88,…”

Section: Related Workmentioning

confidence: 99%

Towards Auction-Based Function Placement in Serverless Fog Platforms

Bermbach

Maghsudi

Hasenburg

et al. 2020

2020 IEEE International Conference on Fog Computing (ICFC)

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The Function-as-a-Service (FaaS) paradigm has a lot of potential as a computing model for fog environments comprising both cloud and edge nodes. When the request rate exceeds capacity limits at the edge, some functions need to be offloaded from the edge towards the cloud. In this paper, we present an auction-inspired approach in which application developers bid on resources while fog nodes decide locally which functions to execute and which to offload in order to maximize revenue. We evaluate our approach through a number of simulations, our proof-of-concept prototype AuctionWhisk, and a number of experiments with AuctionWhisk.

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“…Yet unlike MockFog, these testbeds can only simulate realistic network conditions, not the constrained compute capabilities of fog nodes, especially at the edge. Balasubramanian et al [53] present a testbed for fog applications that facilitates emulating these constraints, yet requires physical hardware for each node rather than cheaper virtual machines.…”

Section: Related Workmentioning

confidence: 99%

From Zero to Fog: Efficient Engineering of Fog-Based Internet of Things Applications

Pfandzelter,

Hasenburg,

Bermbach

2020

Preprint

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In 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 either simulation or solving a formalized assignment problem through heuristics, which are both inaccurate and fail to scale with a solution space that grows exponentially. In this paper, we present a three step process for designing practical fog-based IoT applications that uses 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.

show abstract

A Rapid Testing Framework for a Mobile Cloud

Cited by 13 publications

References 11 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 Auction-Based Function Placement in Serverless Fog Platforms

From Zero to Fog: Efficient Engineering of Fog-Based Internet of Things Applications

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