A Data Preparation Approach for Cloud Storage Based on Containerized Parallel Patterns

Carrizales, Diana; Sánchez‐Gallegos, Dante D.; Reyes, Hugo; Gonzalez-Compeán, J. L.; Morales-Sandoval, Miguel; Carretero, Jesús; Galaviz-Mosqueda, Alejandro

doi:10.1007/978-3-030-34914-1_45

Cited by 9 publications

(8 citation statements)

References 15 publications

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“…On the scope of the management of NFRs the main proposals have been focused on security and reliability requirements. End-to-end processing schemes have been proposed to mitigate the lack of control over the data in outsourced environments [85]- [87]. In this type of scheme, data are preprocessed before sending them to the cloud by applying techniques such as encryption to reduce security issues [39], [88], [89], and reliability schemes based on coding and redundancy to face outages [47]- [49], [90] or failures in the cloud [44], [91].…”

Section: Related Workmentioning

confidence: 99%

“…These structures allow users to create different processing structures that can be deployed on any combination of edge, fog, or cloud. Also, continuity schemes [85] simultaneously enforce the continuous delivery of data in each stage of a processing structure and to fulfilling the NFRs for data processed by the blocks of the processing structures.…”

Section: Related Workmentioning

confidence: 99%

“…The idea is to attach a continuity scheme to each block in an edge-fog-cloud processing structure to enforce the fulfillment of NFRs for data arriving and departing to/from a block in the processing structures. These schemes are defined in coordination with the push and pull operations invoked by the blocks of a structure [85].…”

Section: B Continuity Schemes For Fulfilling Non-functional Requiremmentioning

confidence: 99%

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On the Continuous Processing of Health Data in Edge-Fog-Cloud Computing by Using Micro/Nanoservice Composition

et al. 2020

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The edge, the fog, the cloud, and even the end-user's devices play a key role in the management of the health sensitive content/data lifecycle. However, the creation and management of solutions including multiple applications executed by multiple users in multiple environments (edge, the fog, and the cloud) to process multiple health repositories that, at the same time, fulfilling non-functional requirements (NFRs) represents a complex challenge for health care organizations. This paper presents the design, development, and implementation of an architectural model to create, on-demand, edge-fog-cloud processing structures to continuously handle big health data and, at the same time, to execute services for fulfilling NFRs. In this model, constructive and modular blocks, implemented as microservices and nanoservices, are recursively interconnected to create edge-fog-cloud processing structures as infrastructureagnostic services. Continuity schemes create dataflows through the blocks of edge-fog-cloud structures and enforce, in an implicit manner, the fulfillment of NFRs for data arriving and departing to/from each block of each edge-fog-cloud structure. To show the feasibility of this model, a prototype was built using this model, which was evaluated in a case study based on the processing of health data for supporting critical decision-making procedures in remote patient monitoring. This study considered scenarios where end-users and medical staff received insights discovered when processing electrocardiograms (ECGs) produced by sensors in wireless IoT devices as well as where physicians received patient records (spirometry studies, ECGs and tomography images) and warnings raised when online analyzing and identifying anomalies in the analyzed ECG data. A scenario where organizations manage multiple simultaneous each edge-fog-cloud structure for processing of health data and contents delivered to internal and external staff was also studied. The evaluation of these scenarios showed the feasibility of applying this model to the building of solutions interconnecting multiple services/applications managing big health data through different environments. INDEX TERMS Big health data, edge-fog-cloud, health-IoT processing, Internet of Things, microservice architecture.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: B Continuity Schemes For Fulfilling Non-functional Requiremmentioning

confidence: 99%

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On the Continuous Processing of Health Data in Edge-Fog-Cloud Computing by Using Micro/Nanoservice Composition

et al. 2020

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“…In [10] [11] [12], there is a set of solutions for building efficient and flexible end-to-end cloud storage. Information integrity is preserved based on the IDA implementation embedded in parallel processing patterns.…”

Section: Related Workmentioning

confidence: 99%

On the Complexity and Performance of the Information Dispersal Algorithm

et al. 2020

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The Information Dispersal Algorithm (IDA) has become a key component in several faulttolerant massive storage systems. From a theoretical point of view, it is a linear transformation over a finite field on the vectors that make up a given file. Direct transformation adds redundancy, splitting the initial file into a new set of files called dispersals. The inverse transformation recovers the original file from a subset of dispersals. This piece of research demonstrates the impact of input and output (I/O) operations on direct and inverse transformations. Different alternatives to control the exchange of elements between RAM and disk were evaluated, which is the key operation to build a vector in memory and store its entries in a file. First, the impact of the working finite field was tested; second, the impact of the use of a buffer for exchange between the RAM and the hard disk, and finally, several instances of the algorithm with which to evaluate the impact of parallelism were simultaneously deployed. The results demonstrate that the combination of these factors may have an important effect on the speed of both direct and inverse procedures.

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“…In these types of infrastructures (any combination of edge, fog, or cloud), the virtual containers (

) are key to deploy services on each infrastructure [ 11 , 12 , 13 ]. These services provide dataflows from the IoT to the cloud that produce different types of data and information, which proves to be key for organizations to conduct critical decision-making processes [ 14 , 15 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

A WoT-Based Method for Creating Digital Sentinel Twins of IoT Devices

López-Arévalo

Gonzalez-Compeán

Hinojosa-Tijerina

et al. 2021

Sensors

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The data produced by sensors of IoT devices are becoming keystones for organizations to conduct critical decision-making processes. However, delivering information to these processes in real-time represents two challenges for the organizations: the first one is achieving a constant dataflow from IoT to the cloud and the second one is enabling decision-making processes to retrieve data from dataflows in real-time. This paper presents a cloud-based Web of Things method for creating digital twins of IoT devices (named sentinels).The novelty of the proposed approach is that sentinels create an abstract window for decision-making processes to: (a) find data (e.g., properties, events, and data from sensors of IoT devices) or (b) invoke functions (e.g., actions and tasks) from physical devices (PD), as well as from virtual devices (VD). In this approach, the applications and services of decision-making processes deal with sentinels instead of managing complex details associated with the PDs, VDs, and cloud computing infrastructures. A prototype based on the proposed method was implemented to conduct a case study based on a blockchain system for verifying contract violation in sensors used in product transportation logistics. The evaluation showed the effectiveness of sentinels enabling organizations to attain data from IoT sensors and the dataflows used by decision-making processes to convert these data into useful information.

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A Data Preparation Approach for Cloud Storage Based on Containerized Parallel Patterns

Cited by 9 publications

References 15 publications

On the Continuous Processing of Health Data in Edge-Fog-Cloud Computing by Using Micro/Nanoservice Composition

On the Continuous Processing of Health Data in Edge-Fog-Cloud Computing by Using Micro/Nanoservice Composition

On the Complexity and Performance of the Information Dispersal Algorithm

A WoT-Based Method for Creating Digital Sentinel Twins of IoT Devices

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