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.
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.
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.
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.
With the rapid development of cloud computing technologies, cloud gaming has gained wide attention from the industrial field. By executing the gaming software on the cloud and transiting the rendered game scenes back ...
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ISBN:
(纸本)9781509034840
With the rapid development of cloud computing technologies, cloud gaming has gained wide attention from the industrial field. By executing the gaming software on the cloud and transiting the rendered game scenes back to the client, game players can play games anywhere on any device. However, the centralized architecture of existing cloud gaming platforms causes serious network latency, which deteriorates user experience significantly. To reduce network latency and relieve the workload on the mobile client, we propose and implement a cloudlet-based mobile cloud gaining system design. By deploying the cloudlets in the nearby region of mobile users, we can provide computational resources to the mobile clients and complete tasks such as gaming state maintenance, game scene rendering, etc. The system can also reduce the gaming latency and the workload on the client greatly. We use the open-source cloud computing software to build a cloudlet system and develop an Android based cloud gaming client, which can receive and display gaming video streams, and map and upload the game operations. Finally, we conduct experimental evaluation of our mobile cloud gaming prototype. The results show that our proposed solution can significantly reduce the fraction of network latency.
Offloading computation-intensive tasks from mobile to nearby resource-rich surrogates, called edge servers, is proposed recently because traditional mobile cloud computing has a bottleneck of bandwidth and resource li...
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ISBN:
(纸本)9781538676721
Offloading computation-intensive tasks from mobile to nearby resource-rich surrogates, called edge servers, is proposed recently because traditional mobile cloud computing has a bottleneck of bandwidth and resource limitation for devices. The primary performance concern of offloading is how to maximize energy saving under task delay and task dependency limitation. Besides, edge servers that mobile perceived are changeable and heterogeneous in the process of offloading. In this paper, we formalize this problem, reduce it into knapsack problem and propose a task scheduling scheme, named TaSRD, including independent sub-task scheduling for tasks without dependencies and dependent sub-task scheduling for dependent tasks. We implement TaSRD and evaluate it by case study and simulation on CloudSim framework developed by Melbourne University. We use time model and energy model to measure results and recommend suitable parameters for TaSRD. The experimental results demonstrate that TaSRD can effectively save energy and reduce makespan for mobile while offloading tasks to edge servers.
The task assignment problem for multiple vessels cooperative driving is the key problem of the multiple vessels cooperative control. Due to the system showing multi-objective, multi-tasking and multi-constrained featu...
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ISBN:
(纸本)9781538619797;9781538619780
The task assignment problem for multiple vessels cooperative driving is the key problem of the multiple vessels cooperative control. Due to the system showing multi-objective, multi-tasking and multi-constrained features, a cooperative multi-task assignment model is proposed, which can transform multiple constraints task assignment problem into multiple constraints optimization problem based on the multiple vessels task assignment cost function. This method optimizes the results of task assignment by using genetic ant colony hybrid algorithm to search optimization solution globally. In the simulation experiment, it is compared with the genetic algorithm and the ant colony algorithm alone, and experimental results show that the method can optimize task assignment on the basis of satisfying these constraints.
Hyperspectral image(HSI) is often contaminated by mixed noise in the acquisition process. In this paper,a hyperspectral image low-rank restoration method based spectral-spatial total variation(LRSSTV) is proposed....
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ISBN:
(纸本)9781538619797;9781538619780
Hyperspectral image(HSI) is often contaminated by mixed noise in the acquisition process. In this paper,a hyperspectral image low-rank restoration method based spectral-spatial total variation(LRSSTV) is proposed. The spectral high correlation is exploited by low-rank representation and the sparse noise is represented by the l-norm. Furthermore,to remove the Gaussian noise and enhance the edge information,spectral-spatial adaptive total variation prior knowledge is utilized. Both simulated and real-world data experimental results show that the proposed method can work well in detail preservation and noise removal.
Recently, brain-computer interface has been applied to many fields such as steady-state visual evoked potential(SSVEP). However, in the conventional method, the frequency resolution is low due to the dependence of the...
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ISBN:
(纸本)9781538619797;9781538619780
Recently, brain-computer interface has been applied to many fields such as steady-state visual evoked potential(SSVEP). However, in the conventional method, the frequency resolution is low due to the dependence of the short-time Fourier transform on the analysis window length. Therefore, it is not possible to analyze a non-integer multiple signal, as a side-lobe will occur. We verified the precision of non-harmonics analysis,and proposed and attempted to analyze the change and stimulus of SSVEP. We found the frequency resolution to be improved exponentially.
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