Strategies and systems towards grids and clouds integration:A DBMS-based solution

Mariotti, Mirko; Gervasi, Osvaldo; Vella, Flavio; Cuzzocrea, Alfredo; Costantini, Alessandro

doi:10.1016/j.future.2017.02.047

Cited by 19 publications

(9 citation statements)

References 9 publications

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“…As a result, the Cloud has become more important than ever as a resource to be able to react to all of these expectations for efficiency and effectiveness in the processing of the many different types of information that our society has grown inexorably addicted to [28,29].…”

Section: Related Workmentioning

confidence: 99%

Deploying Efficiently Modern Applications on Cloud

Perri¹,

Simonetti²,

Gervasi³

2022

Preprint

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This study analyses some of the leading technologies for the construction and configuration of IT infrastructures to provide services to users. For modern applications, guaranteeing service continuity even in very high computational load or network problems is essential. Our configuration has among the main objectives of being highly available (HA) and horizontally scalable, that is, able to increase the computational resources that can be delivered when needed and reduce them when they are no longer necessary. Various architectural possibilities are analysed, and the central schemes used to tackle problems of this type are also described in terms of disaster recovery. The benefits offered by virtualisation technologies are highlighted and are bought with modern techniques for managing Docker containers that will be used to build the back-end of a sample infrastructure related to a use-case we have developed. In addition to this, an in-depth analysis is reported on the central autoscaling policies that can help manage high loads of requests from users to the services provided by the infrastructure. The results we have presented show an average response time of 21.7 milliseconds with a standard deviation of 76.3 milliseconds showing excellent responsiveness. Some peaks are associated with high-stress events for the infrastructure, but the response time does not exceed 2 seconds even in this case. The results of the considered use case studied for nine months are presented and discussed. In the study period, we improved the back-end configuration and defined the main metrics to deploy the web application efficiently.

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Section: Related Workmentioning

confidence: 99%

Deploying Efficiently Modern Applications on Cloud

Perri¹,

Simonetti²,

Gervasi³

2022

Preprint

Self Cite

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“…NU!Reha Service allows to train cognitive functions such as memory, attention and executive function, changing the difficulty of activities according to the patient's abilities. This characteristic determines a flexibility service that allows a customization of rehabilitation path [4,[18][19][20][21][22][23][24][25][26]. This flexibility implies a variety of proposed activities, and therapists can improve the platform by making new personalized exercises.…”

Section: Nu!reha Platformmentioning

confidence: 99%

Rapid Prototyping of Virtual Reality Cognitive Exercises in a Tele-Rehabilitation Context

et al. 2021

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In recent years, the need to contain healthcare costs due to the growing public debt of many countries, combined with the need to reduce costly travel by patients unable to move autonomously, have captured the attention of public administrators towards tele-rehabilitation. This trend has been consolidated overwhelmingly following the Covid-19 pandemic, which has made it precarious, difficult and even dangerous for patients to access hospital facilities. We present an approach based on the rapid prototyping of virtual reality, cognitive tele-rehabilitation exercises, which reinforce the group of exercises available in the Nu!reha platform. Patients who experienced injury or pathology need to practice continuous training in order to recover functional abilities, and the therapist needs to monitor the outcomes of such practices. The group of new exercises based on the rapid prototyping approach, become crucial especially in this pandemic period. The Virtual Reality exercises are designed on Unity 3D to empower the therapist to set up personalized exercises in an easy way, enabling the patient to receive personalized stimuli, which are essential for a positive outcome in the practice. Furthermore, the reaction speed of the system is of fundamental importance, as the temporal evolution of the scene must proceed parallel to the patient’s movements, to ensure an effective and efficient therapeutic response. So, we optimized the virtual reality application in order to make the loading phase and the startup phase as fast as possible and we have tested the results obtained with many devices: in particular computers and smartphones with different operating systems and hardware. The implemented method powers up the Nu!Reha system®, a collection of tele-rehabilitation services that helps patients to recover cognitive and functional capabilities.

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“…Nowadays, almost thirty years later, reliability of networks reached a rather high level, as well as intrinsic complexity. This reliability allowed a wide diffusion of the approach of subjecting diagnostic images to automatic classification systems, from evolutionary algorithms [4][5][6][7] to deep networks [8][9][10][11], being them either convolutive or not. Even in the medical sector of dermatology, automatic image recognition and classification was used for decades to detect tumor skin lesions [12,13].…”

Section: Related Workmentioning

confidence: 99%

Skin Cancer Classification Using Inception Network and Transfer Learning

Benedetti

Perri

Simonetti

et al. 2020

Computational Science and Its Applications – ICCSA 2020

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Medical data classification is typically a challenging task due to imbalance between classes. In this paper, we propose an approach to classify dermatoscopic images from HAM10000 (Human Against Machine with 10000 training images) dataset, consisting of seven imbalanced types of skin lesions, with good precision and low resources requirements. Classification is done by using a pretrained convolutional neural network. We evaluate the accuracy and performance of the proposal and illustrate possible extensions.

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Strategies and systems towards grids and clouds integration:A DBMS-based solution

Cited by 19 publications

References 9 publications

Deploying Efficiently Modern Applications on Cloud

Deploying Efficiently Modern Applications on Cloud

Rapid Prototyping of Virtual Reality Cognitive Exercises in a Tele-Rehabilitation Context

Skin Cancer Classification Using Inception Network and Transfer Learning

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