scholarly journals Video Cloud Services for Hospitals: Designing an End-to-End Cloud Service Platform for Medical Video Storage and Secure Access

10.2196/18139 ◽  
2020 ◽  
Vol 5 (1) ◽  
pp. e18139
Author(s):  
Piotr Pawałowski ◽  
Cezary Mazurek ◽  
Mikołaj Leszczuk ◽  
Jean-Marie Moureaux ◽  
Amine Chaabouni
Keyword(s):  
Video Quality ◽  
Cloud Service ◽  
Video Data ◽  
Cloud Services ◽  
Information And Communications Technology ◽  
Video Encoding ◽  
Rapid Expansion ◽  
Long Run ◽  
Generic Architecture ◽  
End To End

The amount of medical video data that has to be securely stored has been growing exponentially. This rapid expansion is mainly caused by the introduction of higher video resolution such as 4K and 8K to medical devices and the growing usage of telemedicine services, along with a general trend toward increasing transparency with respect to medical treatment, resulting in more and more medical procedures being recorded. Such video data, as medical data, must be maintained for many years, resulting in datasets at the exabytes scale that each hospital must be able to store in the future. Currently, hospitals do not have the required information and communications technology infrastructure to handle such large amounts of data in the long run. In this paper, we discuss the challenges and possible solutions to this problem. We propose a generic architecture for a holistic, end-to-end recording and storage platform for hospitals, define crucial components, and identify existing and future solutions to address all parts of the system. This paper focuses mostly on the recording part of the system by introducing the major challenges in the area of bioinformatics, with particular focus on three major areas: video encoding, video quality, and video metadata.

scholarly journals Video Cloud Services for Hospitals: Designing an End-to-End Cloud Service Platform for Medical Video Storage and Secure Access (Preprint)

2020 ◽  
Author(s):  
Piotr Pawałowski ◽  
Cezary Mazurek ◽  
Mikołaj Leszczuk ◽  
Jean-Marie Moureaux ◽  
Amine Chaabouni
Keyword(s):  
Video Quality ◽  
Cloud Service ◽  
Video Data ◽  
Cloud Services ◽  
Information And Communications Technology ◽  
Video Encoding ◽  
Rapid Expansion ◽  
Long Run ◽  
Generic Architecture ◽  
End To End

UNSTRUCTURED The amount of medical video data that has to be securely stored has been growing exponentially. This rapid expansion is mainly caused by the introduction of higher video resolution such as 4K and 8K to medical devices and the growing usage of telemedicine services, along with a general trend toward increasing transparency with respect to medical treatment, resulting in more and more medical procedures being recorded. Such video data, as medical data, must be maintained for many years, resulting in datasets at the exabytes scale that each hospital must be able to store in the future. Currently, hospitals do not have the required information and communications technology infrastructure to handle such large amounts of data in the long run. In this paper, we discuss the challenges and possible solutions to this problem. We propose a generic architecture for a holistic, end-to-end recording and storage platform for hospitals, define crucial components, and identify existing and future solutions to address all parts of the system. This paper focuses mostly on the recording part of the system by introducing the major challenges in the area of bioinformatics, with particular focus on three major areas: video encoding, video quality, and video metadata.

scholarly journals Assessing Determinants of Continuance Intention towards Personal Cloud Services: Extending UTAUT2 with Technology Readiness

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 467
Author(s):  
Shih-Chih Chen ◽  
Shing-Han Li ◽  
Shih-Chi Liu ◽  
David C. Yen ◽  
Athapol Ruangkanjanases
Keyword(s):  
Rapid Development ◽  
Cloud Service ◽  
Individual Characteristics ◽  
Partial Least Square ◽  
Cloud Services ◽  
Least Square ◽  
Information And Communications Technology ◽  
Technology Readiness ◽  
Continuance Intention ◽  
Systems Research

In addition to the rapid development of global information and communications technology (ICT) and the Internet, recent rapid growth in cloud computing technology represents another important trend. Individual continuance intention towards information technology is a critical area in which information systems research can be performed. This study aims to develop an integrated model designed to explain and predict an individual’s continuance intention towards personal cloud services based on the concepts of technology readiness (TR) and the unified theory of acceptance and use of technology 2 (UTAUT2), moderated by gender, age, and experience of personal cloud services. The key results of the partial least square test largely support the proposed model’s validity and the significant impact of effort expectancy, social influence, hedonic motivation, price value, habit, and technology readiness on continuance intention towards personal cloud services. In addition to providing symmetric theoretical support with the proposed model and transforming the individual characteristics of TR into UTAUT2, this study could be used to enhance and analyze users’ adoption of personal cloud services and also increase the symmetry of the model’s explanation and prediction. The findings from this research contribute to providing practical implications and academic resources as well as improving our understanding of personal cloud service applications.

scholarly journals Dynamic High Availability Architecture Framework for SOA Computing

2018 ◽  
Vol 7 (3.12) ◽  
pp. 740
Author(s):  
S Kumaresan ◽  
Sumithra Devi.K.A
Keyword(s):  
Real Time ◽  
Cloud Service ◽  
High Availability ◽  
Cloud Services ◽  
Loose Coupling ◽  
Cloud Environment ◽  
Architecture Framework ◽  
Generic Architecture ◽  
Multiple Platform ◽  
Complicated Situation

In Software technology stackCloud services provides easy coupling implementation to enhance encapsulation data between multiple platform data exchanges. My finding towards  introducing High Availability Architecture for cloud environment which covers Load Balancing, Failover, High Availability Resources. To achieve thisfeatures it’s identified framework architecture which is called as Dynamic High Availability Architecture Framework for SOA Computing which increase cloud services standard inhigh witheasy adaptable security. Even though cloud service supports loose coupling and isolation business logics. At current cloud service provide wants to launch new web service request on fly same service will notnotified into client in real-time scenario.  To overcome this complicated situation we have introduced (GHAFC) Generic Architecture Framework in Cloud Computing. Which will support data exchanges between producer and consumer onthe fly with real time scenario.

Applied Research of Assessment Methods on Video Quality

2012 ◽  
Vol 262 ◽  
pp. 157-162
Author(s):  
Chong Gu ◽  
Zhan Jun Si
Keyword(s):  
Video Processing ◽  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Rapid Development ◽  
Video Quality ◽  
Objective Evaluation ◽  
Video Data ◽  
Assessment System ◽  
Video Encoding ◽  
High Definition

With the rapid development of modern video technology, the range of video applications is increasing, such as online video conferencing, online classroom, online medical, etc. However, due to the quantity of video data is large, video has to be compressed and encoded appropriately, but the encoding process may cause some distortions on video quality. Therefore, how to evaluate the video quality efficiently and accurately is essential in the fields of video processing, video quality monitoring and multimedia video applications. In this article, subjective, and comprehensive evaluation method of video quality were introduced, a video quality assessment system was completed, four ITU recommended videos were encoded and evaluated by Degradation Category Rating (DCR) and Structural Similarity (SSIM) methods using five different formats. After that, comprehensive evaluations with weights were applied. Results show that data of all three evaluations have good consistency; H.264 is the best encoding method, followed by Xvid and wmv8; the higher the encoding bit rate is, the better the evaluations are, but comparing to 1000kbps, the subjective and objective evaluation scores of 1400kbps couldn’t improve obviously. The whole process could also evaluate new encodings methods, and is applicable for high-definition video, finally plays a significant role in promoting the video quality evaluation and video encoding.

scholarly journals End-to-end QoS computation for vertical service composition in the cloud

2021 ◽  
Author(s):  
Raed Karim
Keyword(s):  
Service Composition ◽  
Cloud Service ◽  
Cloud Services ◽  
Prior History ◽  
Functional Requirements ◽  
Active System ◽  
Qos Prediction ◽  
Cloud Providers ◽  
End To End ◽  
Prediction Approach

Cloud services are designed to provide users with different computing models such as software-as-a-Services (SaaS), Infrastructure-as-a-Service (IaaS), Data-as-a-Service (DaaS), and other IT related services (denoted as XaaS). Easy, scalable and on-demand cloud services are offered by cloud providers to users. With the prevalence of different types of cloud services, the task of selecting the best cloud service solution has become more and more challenging. Cloud service solutions are offered through a collaboration of different cloud services at different cloud layers. This type of collaborations is denoted as vertical service composition. Quality of Service (QoS) properties are used as differentiating factors for selecting the best services among functionally equivalent services. In this thesis, we introduce a new service selection framework for the cloud which vertically matches services offered by different cloud providers based on users’ end-to-end QoS requirements. Functional requirements can be satisfied by the required cloud service (software service, platform service, etc) alone. However, users’ QoS requirements must be satisfied using all involved cloud services in a service composition. Therefore, in order to select the best cloud service compositions for users, QoS values of these compositions must be end-to-end. To tackle the problem of computing unknown end-to-end QoS values of vertical cloud service compositions for target users (for whom these values are computed), we propose two strategies: QoS mapping and aggregation and QoS prediction. The former deals with new cloud service compositions with no prior history. Using this strategy, we can map users’ QoS requirements onto different cloud layers and then we aggregate QoS values guaranteed by cloud providers to estimate end-to-end QoS values. The latter deals with cloud service compositions for which QoS data have been recorded in an active system. Using the QoS prediction strategy, we utilize historical QoS data of previously invoked service compositions and other service and user information to predict end-to-end QoS values. The presented experimental results demonstrate the importance of considering vertically composed cloud services when computing end-to-end QoS values as opposed to traditional prediction approaches. Our QoS prediction approach outperforms other prediction approaches in terms of the prediction accuracy by at least 20%.

QoS Evaluation of End-to-End Services in Virtualized Computing Environments

2015 ◽  
Vol 12 (1) ◽  
pp. 27-44 ◽  
Author(s):  
Guofeng Yan ◽  
Yuxing Peng ◽  
Shuhong Chen ◽  
Pengfei You
Keyword(s):  
Performance Analysis ◽  
Performance Metrics ◽  
Virtual Machines ◽  
Cloud Service ◽  
Stochastic Approach ◽  
Cloud Services ◽  
Acceptance Probability ◽  
Computing Environments ◽  
End To End ◽  
Qos Evaluation

Quality of service (QoS) optimization for end-to-end (e2e) services always depends on performance analysis in cloud-based service delivery industry. However, performance analysis of e2e services becomes difficult as the scale and complexity of virtualized computing environments increase. In this paper, the authors present a novel hierarchical stochastic approach to evaluate the QoS of e2e virtualized cloud services using Quasi-Birth Death structures, where jobs arrive according to a stochastic process and request virtual machines (VMs), which are specified in terms of resources, i.e., VM-configuration. To reduce the complexity of performance evaluation, the overall virtualized cloud services are partitioned into three sub-hierarchies. The authors analyze each individual sub-hierarchy using stochastic queueing approach. Thus, the key performance metrics of e2e cloud service QoS, such as acceptance probability and e2e response delay incurred on user requests, are obtained.

scholarly journals End-to-end QoS computation for vertical service composition in the cloud

2021 ◽  
Author(s):  
Raed Karim
Keyword(s):  
Service Composition ◽  
Cloud Service ◽  
Cloud Services ◽  
Prior History ◽  
Functional Requirements ◽  
Active System ◽  
Qos Prediction ◽  
Cloud Providers ◽  
End To End ◽  
Prediction Approach

Cloud services are designed to provide users with different computing models such as software-as-a-Services (SaaS), Infrastructure-as-a-Service (IaaS), Data-as-a-Service (DaaS), and other IT related services (denoted as XaaS). Easy, scalable and on-demand cloud services are offered by cloud providers to users. With the prevalence of different types of cloud services, the task of selecting the best cloud service solution has become more and more challenging. Cloud service solutions are offered through a collaboration of different cloud services at different cloud layers. This type of collaborations is denoted as vertical service composition. Quality of Service (QoS) properties are used as differentiating factors for selecting the best services among functionally equivalent services. In this thesis, we introduce a new service selection framework for the cloud which vertically matches services offered by different cloud providers based on users’ end-to-end QoS requirements. Functional requirements can be satisfied by the required cloud service (software service, platform service, etc) alone. However, users’ QoS requirements must be satisfied using all involved cloud services in a service composition. Therefore, in order to select the best cloud service compositions for users, QoS values of these compositions must be end-to-end. To tackle the problem of computing unknown end-to-end QoS values of vertical cloud service compositions for target users (for whom these values are computed), we propose two strategies: QoS mapping and aggregation and QoS prediction. The former deals with new cloud service compositions with no prior history. Using this strategy, we can map users’ QoS requirements onto different cloud layers and then we aggregate QoS values guaranteed by cloud providers to estimate end-to-end QoS values. The latter deals with cloud service compositions for which QoS data have been recorded in an active system. Using the QoS prediction strategy, we utilize historical QoS data of previously invoked service compositions and other service and user information to predict end-to-end QoS values. The presented experimental results demonstrate the importance of considering vertically composed cloud services when computing end-to-end QoS values as opposed to traditional prediction approaches. Our QoS prediction approach outperforms other prediction approaches in terms of the prediction accuracy by at least 20%.

scholarly journals Dynamic OverCloud: Realizing Microservices-Based IoT-Cloud Service Composition over Multiple Clouds

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 969 ◽  
Author(s):  
Jungsu Han ◽  
Sun Park ◽  
JongWon Kim
Keyword(s):  
Service Composition ◽  
Cloud Service ◽  
Cloud Services ◽  
Information And Communications Technology ◽  
Software Framework ◽  
Iot Devices ◽  
Multiple Clouds ◽  
Cloud Service Composition ◽  
Convergence Trend ◽  
Lock In

With the expansion of cloud-leveraged Information and Communications Technology (ICT) convergence trend, cloud-native computing is starting to be the de-facto paradigm together with MSA(Microservices Architecture)-based service composition for agility and efficiency. Moreover, by bridging the Internet of Things (IoT) and cloud together, a variety of cloud applications are explosively emerging. As an example, the so-called IoT-Cloud services, which are cloud-leveraged inter-connected services with distributed IoT devices, dynamically utilize geographically-distributed multiple clouds since mobile IoT devices can selectively connect to the near-by cloud resources for low-latency and high-throughput connectivity. In comparison, most public cloud providers may cause vendor lock-in problems that limit the inter-operable service compositions. Thus, in this paper, we propose a new overlay approach to address the above limitations, denoted as Dynamic OverCloud, which is a specially-arranged razor-thin overlay layer that provides users with an inter-operable and visibility-supported environment for MSA-based IoT-Cloud service composition over the existing multiple clouds. Then, we design a software framework that dynamically builds the proposed concept. We also describe a detailed implementation of the software framework with workflows. Finally, we verify its feasibility by realizing a smart energy IoT-Cloud service with the suggested operation lifecycle.

Personalized cloud service review analysis based on modularized ontology

2020 ◽  
Vol 44 (5) ◽  
pp. 953-975
Author(s):  
Emna Ben-Abdallah ◽  
Khouloud Boukadi ◽  
Mohamed Hammami ◽  
Mohamed Hedi Karray
Keyword(s):  
Knowledge Base ◽  
Positive Impact ◽  
Cloud Service ◽  
Service Evaluation ◽  
End Users ◽  
Cloud Services ◽  
Limited Information ◽  
Content Type ◽  
Ontology Language ◽  
Modular Ontology

PurposeThe purpose of this paper is to analyze cloud reviews according to the end-user context and requirements.Design/methodology/approachpropose a comprehensive knowledge base composed of interconnected Web Ontology Language, namely, modular ontology for cloud service opinion analysis (SOPA). The SOPA knowledge base will be the basis of context-aware cloud service analysis using consumers' reviews. Moreover, the authors provide a framework to evaluate cloud services based on consumers' reviews opinions.FindingsThe findings show that there is a positive impact of personalizing the cloud service analysis by considering the reviewers' contexts in the performance of the framework. The authors also proved that the SOPA-based framework outperforms the available cloud review sites in term of precision, recall and F-measure.Research limitations/implicationsLimited information has been provided in the semantic web literature about the relationships between the different domains and the details on how that can be used to evaluate cloud service through consumer reviews and latent opinions. Furthermore, existing approaches are lacking lightweight and modular mechanisms which can be utilized to effectively exploit information existing in social media.Practical implicationsThe SOPA-based framework facilitates the opinion based service evaluation through a large number of consumer's reviews and assists the end-users in analyzing services as per their requirements and their own context.Originality/valueThe SOPA ontology is capable of representing the content of a product/service as well as its related opinions, which are extracted from the customer's reviews written in a specific context. Furthermore, the SOPA-based framework facilitates the opinion based service evaluation through a large number of consumer's reviews and assists the end-users in analyzing services as per their requirements and their own context.

scholarly journals A Generic Model for Identifying QoS Parameters Interrelations in Cloud Services Selection Ontology during Runtime

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 563
Author(s):  
Babu Rajendiran ◽  
Jayashree Kanniappan
Keyword(s):  
Service Providers ◽  
Cloud Service ◽  
Cloud Services ◽  
Operating Costs ◽  
Generic Model ◽  
Business Organizations ◽  
Cloud Environment ◽  
Cloud Service Provider ◽  
Qos Parameters ◽  
Computer Based

Nowadays, many business organizations are operating on the cloud environment in order to diminish their operating costs and to select the best service from many cloud providers. The increasing number of Cloud Services available on the market encourages the cloud consumer to be conscious in selecting the most apt Cloud Service Provider that satisfies functionality, as well as QoS parameters. Many disciplines of computer-based applications use standardized ontology to represent information in their fields that indicate the necessity of an ontology-based representation. The proposed generic model can help service consumers to identify QoS parameters interrelations in the cloud services selection ontology during run-time, and for service providers to enhance their business by interpreting the various relations. The ontology has been developed using the intended attributes of QoS from various service providers. A generic model has been developed and it is tested with the developed ontology.

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