Healthcare is one of the industries that seeks to deliver medical services to patients on time. One of the issues it currently grapples with is real-time patient data exchange between various healthcare organizations....
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Healthcare is one of the industries that seeks to deliver medical services to patients on time. One of the issues it currently grapples with is real-time patient data exchange between various healthcare organizations. This challenge was solved by both centralized and decentralized cloud computing architecture solutions. In this paper, we review the current state of these two cloudcomputing architectures in the health sector with regard to the effect on the efficiency of Health Information Exchange (HIE) systems. Our study seeks to determine the relevance of these cloudcomputing approaches in assisting healthcare facilities in the decision-making process to adopt HIE systems. This paper considers the system performance, patient data privacy, and cost and identifies research directions in each of the architectures. This study shows that there are some benefits in both cloud architectures, but there are also some drawbacks. The prominent characteristic of centralized cloudcomputing is that all data and information are stored together at one location, known as a single data center. This offers many services, such as integration, effectiveness, simplicity, and rapid information access. However, it entails providing data privacy and confidentiality aspects because it will face the hazard of a single point of failure. On the other hand, decentralized cloud computing is built to safeguard data privacy and security whereby data are distributed to several nodes as a way of forming mini-data centers. This increases the system's ability to cope with a node failure. Thus, continuity and less latency are achieved. Nevertheless, it poses integration issues because managing data from several sites could be a problem, and the costs of operating several data centers are higher and complex. This paper also pays attention to the differences in aspects like efficiency, capacity, and cost. This paper assists healthcare organizations in determining the most suitable cloud architecture
decentralizedcloud platforms have emerged as a promising paradigm to exploit the idle computing resources across the Internet to catch up with the ever-increasing cloudcomputing *** any user or enterprise can be the...
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decentralizedcloud platforms have emerged as a promising paradigm to exploit the idle computing resources across the Internet to catch up with the ever-increasing cloudcomputing *** any user or enterprise can be the cloud provider in the decentralizedcloud,the performance assessment of the heterogeneous computing resources is of vital ***,with the consideration of the untrustworthiness of the participants and the lack of unified performance assessment metric,the performance monitoring reliability and the incentive for cloud providers to offer real and stable performance together constitute the computational performance assessment problem in the decentralized *** this paper,we present a robust performance assessment solution RODE to solve this *** mainly consists of a performance monitoring mechanism and an assessment of the claimed performance(AoCP)*** performance monitoring mechanism first generates reliable and verifiable performance monitoring results for the workloads executed by untrusted cloud *** on the performance monitoring results,the AoCP mechanism forms a unified performance assessment metric to incentivize cloud providers to offer performance as *** extensive experiments,we show RODE can accurately monitor the performance of cloud providers on the premise of reliability,and incentivize cloud providers to honestly present the performance information and maintain the performance stability.
Today's public cloud services suffer from fundamental privacy issues, e.g., as demonstrated by the global surveillance disclosures. The lack of privacy in cloudcomputing stems from its inherent centrality. State-...
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ISBN:
(纸本)9781509036844
Today's public cloud services suffer from fundamental privacy issues, e.g., as demonstrated by the global surveillance disclosures. The lack of privacy in cloudcomputing stems from its inherent centrality. State-of-the-art approaches that increase privacy for cloud services either operate cloud-like services on user's devices or encrypt data prior to upload to the cloud. However, these techniques jeopardize advantages of the cloud such as elasticity of processing resources. In contrast, we propose decentralized private clouds to allow users to protect their privacy and still benefit from the advantages of cloudcomputing. Our approach utilizes idle resources of friends and family to realize a trusted, decentralized system in which cloud services can be operated securely and privacy-preserving. We discuss our approach and substantiate its feasibility with initial experiments.
Cameras are found everywhere in the Internet of Things (IoT). We propose a scalable platform using SAVI for the continuous collection of context-aware processed video from mobile devices. Users can perform efficient c...
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Cameras are found everywhere in the Internet of Things (IoT). We propose a scalable platform using SAVI for the continuous collection of context-aware processed video from mobile devices. Users can perform efficient context-based searches on the total collection of labeled videos. In this paper we discuss the challenges and benefits for video upload, video labeling and context-based search on the SAVI network.
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