A cloud service selection model of the cloud service management system was proposed based on dynamic trustworthiness in order to select a trusted service which satisfies user's request from a lot of services with ...
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ISBN:
(纸本)9781509034840
A cloud service selection model of the cloud service management system was proposed based on dynamic trustworthiness in order to select a trusted service which satisfies user's request from a lot of services with similar or same functions. A service selection algorithm was proposed in order to select the closest classification for the user's requester. A trust evaluation mechanism was introduced, combined with direct trust and domain recommended trust. Then a service resource was selected among the requester's classification, which is trusted, When the transaction was completed, the service satisfaction was evaluated and the trust degree was updated. Simulation results show that the model can improve the service requesters' satisfaction and has certain resilience to intentional noncooperation.
Sensor as a Service(SaaS) is introduced by providing ubiquitous sensing services along with prosperity of Internet of Things (IoT) [1]. It comprises billions of mobile devices equipped with sensors which can sense, co...
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ISBN:
(纸本)9781538676721
Sensor as a Service(SaaS) is introduced by providing ubiquitous sensing services along with prosperity of Internet of Things (IoT) [1]. It comprises billions of mobile devices equipped with sensors which can sense, communicate and compute. With more capabilities, devices could share some computation tasks which are used to be taken by the cloud servers or the edge servers. To achieve the most benefit of energy consumption and delay, we propose Dynamic Least-cost Task Scheduling(DLCTS) mechanism for enabling on-demand ubiquitous sensing service by leveraging edge computing which brings compute and storage resources on or close to devices. Through virtualization of sensors required in a region, we could adapt task assignment by changing mappings between virtual sensors and devices dynamically to the movement of devices and incidents. Simulation results show that the proposed algorithm achieves great cost performance without paying extra expense of quality and decision-making time. And it proves that the scheme is suitable for densely-distributed devices and large-scaled for multiple sensing tasks.
Traditional approaches to apply tabu search method typically require formulating an algorithmic structure for each individual problem. Based on algebraic specifications, the paper presents a unified and mechanical fra...
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Health care industry is one of the largest and most fragmented industries in the US with almost 600,000 different providers that vary greatly in terms of size, staffing patterns, and organizational structures. This pa...
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ISBN:
(纸本)9781467390880
Health care industry is one of the largest and most fragmented industries in the US with almost 600,000 different providers that vary greatly in terms of size, staffing patterns, and organizational structures. This paper evaluates the operational efficiency of 1228 health projects from National Institutes of Health in New York State, USA using Data Envelopment Analysis. Special emphasis was placed on investigating the environmental variables which exert significant influence to the project performance. Finally, recommendations to management's use of DEA results were given.
The full polarimetric information of the target from polarized Synthetic Aperture Radar (POLSAR) enables us to implement recognition and classification of remote sensing images more effectively. Based on the analysis ...
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SERVQUAL model has been used to measure service quality in different industries. In most cases, this model was validated by confirmatory factor analysis approach. The objective of this research is to validate SERVQUAL...
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Protein is an important molecule that performs a wide range of functions in biological systems. The GOR algorithm is one of the most successful computational methods to predict secondary structure from protein sequenc...
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This paper analyzes the complexity of Internet innovation using scale-free network theory. The evolutionary model has also been numerically simulated. The conclusion is that the model has small-world and scale-free fe...
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ISBN:
(纸本)9781538619797;9781538619780
This paper analyzes the complexity of Internet innovation using scale-free network theory. The evolutionary model has also been numerically simulated. The conclusion is that the model has small-world and scale-free features. The small-world effect shows that there is a wide range of high efficiency Internet resource integration. Scale-free features indicate that a few core nodes become central. Therefore, we should not only see the characteristics to enhance the positive effect of innovation performance, but also avoid the risk of lockin and vulnerability.
Most Web browsers are designed for visual interaction, which receive input and render webpage content via a graphical and visual mode. For people with visual disabilities, access to the Web is very difficult. In this ...
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computing resource utilization of applications may vary over time and inappropriate static resource provision would cause resource wastage or performance loss. Auto scaling based on instant demand is a simple solution...
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ISBN:
(纸本)9781509034840
computing resource utilization of applications may vary over time and inappropriate static resource provision would cause resource wastage or performance loss. Auto scaling based on instant demand is a simple solution but it also introduces latency of scaling. An accurate resource demand prediction algorithm is able to eliminate the side effects of scaling. To address this issue, we present CRUPA, a resource utilization prediction algorithm based on a time series analysis model (ARIMA) combined with Docker container technique. We also design a comparison experiment to evaluate the proposed algorithm and its average forecast error is only 6.5% in the short term, which is much lower than the most common model based on threshold (16.9%) on the same dataset. The result shows that CRUPA not only has high prediction accuracy but also scales the resource well.
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