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Although cloud storage services can bring users valuable convenience, they can be technically complex and intrinsically insecure. Therefore, this research explores the concerns of academic users regarding cloud security and technical issues and how such problems may influence their continuous use in daily life.

This qualitative study used a semi-structured interview approach comprising six main open-ended questions to explore the information security and technical issues for the continuous use of cloud storage services by 20 undergraduate students in Hong Kong.

The analysis revealed cloud storage service users' major security and technical concerns, particularly synchronization and backup issues, were the most significant technical barrier to the continuing personal use of cloud storage services.

Existing literature has focused on how cloud computing services could bring benefits and security and privacy-related risks to organizations rather than security and technical issues of personal use, especially in the Asian academic context.

The purpose of this article is to provide an overview of current uses of cloud computing (CC) services in libraries, address a gap identified in integrating cloud storage in IaaS level, and show how to use EC2 tools for easy backup and resource monitoring.

The article begins a literature review of CC uses in libraries, organized at the SaaS, PaaS and IaaS levels. The author presents his experience of integrating cloud storage services S3 and GCS. In addition, he also shows how to use virtual machine EC2 tools for backup and monitoring resources.

The article describes a case study of integrating cloud storage using S3 and GCS. S3 can be integrated with any program whether the program runs on cloud or locally, while GCS is only good for applications running on GAE. The limitation of the current GCS approach makes it hard to use for a stand‐alone cloud storage. The author also discusses virtual machines using EC2 and its related tools for backup, increase storage, and monitoring service. These services make system administration easier as compared to the traditional approach.

The article presents current CC uses in libraries at the SaaS, PaaS, and IaaS levels. CC services are changing quickly. For example, Google has stated that its APIs are experimental. Readers should be aware of this.

The author shows his experience of integrating cloud storage services. Readers can understand the similarities and differences between S3 and GCS. In addition, readers can learn the advantages and concerns associated with implementing cloud computing. Readers are encouraged to consider questions such as content, skills, costs, and security.

There are many uses of CC services in libraries. However, gaps are identified: in IaaS cloud storage, a few libraries used Amazon S3 and Microsoft Azure, but none explored using Google Cloud Storage (GCS); none provided implementation details, difficulties, and comparisons of S3 and GCS; and a few articles have briefly discussed implementations on Amazon EC2, but have not provided specific details about upgrade and backup. This article addresses those gaps.

This study's purpose is to propose an integrated model based on expectation-confirmation model (ECM), task-technology fit (TTF) model, and updated DeLone and McLean information system (IS) success model to examine whether quality factors and TTF as antecedents to physician beliefs can affect physicians' continuance intention of the cloud-based hospital information system (HIS) and performance impact.

Sample data for this study were collected from physicians at five hospitals in Taiwan. A total of 500 questionnaires were distributed, and 305 (61.0 percent) usable questionnaires were analyzed using structural equation modeling in this study.

This study verified that physicians' perceived information quality, system quality, general technical support service quality, and cloud storage service quality all positively caused their PU, confirmation, and perceived TTF in the cloud-based HIS, which together explained their satisfaction with the system, and subsequently led to their continuance intention of the system and performance impact.

First, IS-related and cloud-related quality factors are simultaneously taken into consideration within this study's research model, and empirical results reveal deep insights into quality evaluation in the field of physicians' cloud-based HIS continuance intention. Next, this study contributes to an understanding of TTF in explaining physicians' cloud-based HIS continuance intention that is difficult to explain with only their utilitarian perception of the system, and places emphasis upon physicians' perception of performance impact greatly driven by their perceived TTF and continuance intention of the system, thus the results can shed light on antecedents and outcome of physicians' cloud-based HIS continuance intention.

The purpose of this paper is to compare and evaluate the personal cloud storage products (PCSPs) in China and find the gap among them for promoting their service level. There are five representative products including Baidu cloud, Tencent cloud, Qihoo 360-cloud, Kingsoft cloud and Huawei DBank.

This study, first, extracts corresponding indicators based on the extant literature to evaluate PCSPs, and then collects the data about each index by investigation and the performance test, finally proposes a model to rank PCSPs, which applies analytic hierarchy process (AHP) to determine the indexed weights and the technique for order preference by similarity to ideal solution-grey relational analysis calculate evaluation score of each PCSP.

Among them, Qihoo 360-cloud gets the highest evaluation score contributed by large space, file editing and fast transmission speed. The rest are Kingsoft cloud, Baidu cloud, Huawei DBank and Tencent cloud in order. These storage products are all want of the addition or improvement of the online editing service similar as Google Docs.

AHP method is subjective, some of the data is incomplete, and some accidental error and systematic error exist in the actual testing process.

The findings can assist users in selecting more suitable products and offer cloud storage providers (CSPs) a general direction of improving their product performance.

Contributing to improve the overall level of the cloud storage services in China.

The study perfects the evaluation index system of the PCSP and fills the research gap in studying PCSPs in China, and expands the application field of the multiple criteria decision-making problems. This evaluation process and results have implied that CSPs in China should provide good services of large capacity, cooperation and security with the good internet environment of economical, high and stable speed by institutions and internet access providers.

The purpose of this paper is to define an evaluation model for cloud services to deal with the fuzzy information and propose a novel fuzzy evaluation method based on consistency intensity to analyze the quantitative value from the fuzzy information.

The cloud service evaluation framework is constructed, and different trusted indicators for the infrastructure services and the application services are designed, respectively. In the novel fuzzy evaluation method, the interval values can be aggregated by the Dempster-Shafer Theory and be transformed into the certain value by linguistic discount factor. The consistency intensity is proposed to determine the value of the linguistic discount factor, which can reflect the mainstream opinions in the assessment.

The proposed method can solve the problem on the analysis and synthesis of the fuzzy evaluation information. An instance of trust evaluation of cloud storage service is illustrated to verify that the proposed method can express the opinions of all evaluators more adequately.

A serial of experiments are carried out on NetLogo, and the results show that the proposed method is practical and efficient.

Instead of obtaining only the qualitative results by the multi-attribute decision-making method, the fuzzy evaluation method based on consistency intensity can obtain the quantitative results from the fuzzy information according to linguistic discount factor and consistency intensity.

Cloud computing becomes mobile when a mobile device tries to access the shared pool of computing resources provided by the cloud, on demand. Mobile applications may enrich their functionality by delegating heavy tasks to the clouds as the remote processing and storage have become possible by adding asynchronous behavior in the communication. However, developing mobile cloud applications involves working with services and APIs from different cloud vendors, which mostly are not interoperable across clouds. Moreover, by adding asynchronicity, mobile applications must rely on push mechanisms which are considered to be moderately reliable, and thus not recommended in scenarios that require high scalability and quality of service (QoS). To counter these problems, and the purpose of this paper, is to design a middleware framework, Mobile Cloud Middleware (MCM), which handles the interoperability issues and eases the use of process‐intensive services from smartphones by extending the concept of mobile host.

MCM is developed as an intermediary between the mobile and the cloud, which hides the complexity of dealing with multiple cloud services from mobiles. Several applications are presented to show the benefits of mobiles going cloud‐aware. Moreover, to verify the scalability of MCM, load tests are performed on the hybrid cloud resources using well known load balancing mechanisms like HAProxy and Tsung.

From the study it was found that it is possible to handle hybrid cloud services from mobiles by using MCM. The analysis demonstrated that the MCM shows reasonable performance levels of interaction with the user, thus validating the proof of concept. Moreover, MCM decreases the effort in developing mobile cloud applications and helps in keeping soft‐real time responses by using its asynchronous approach.

MCM fosters the utilization of different types of cloud services rather than the traditional mobile cloud services based on data synchronization. By offloading heavy tasks to the clouds, the framework extends the processing power and storage space capabilities of the constrained smart phones. The applications mentioned in the paper bring an added value by being success stories for mobile cloud computing domain in general.

The development of mobile applications in multiple clouds environment is a complex task because of the lack of platform standards in cloud computing and mobile computing. The source code involves various proprietary programming libraries for different platforms. However, functionalities are inevitably changed over time, as well as the platform. Therefore, a great deal of development effort is required, when changes need to be made at functional and platform level. This paper aims to propose SIMON, a framework that eases complexity of the development to support software evolution.

SIMON shields the developer from the complexity of mobile and cloud platforms in the development of mobile applications in multiple clouds environment. The framework uses model of application design to automate the development and support execution of mobile applications in system environment that needs integration to the number of data sources located on multiple clouds. The framework is composed of prefabricated components that support function changeability and platform adaptability.

The framework is examined with the development of a sample application. After it is evaluated with scenarios that involve changing at functional and platform levels, the result shows significant reducing of the development effort by comparing with the other approaches.

The framework facilitates the implementation of mobile applications in the software system that involves integration to multiple clouds, and it supports software evolution with lesser development effort.

The purpose of this paper is to use cloud storage in digital preservation by analyzing the pricing and data retrieval models. The author recommends strategies to minimize the costs and believes cloud storage is worthy of serious consideration.

Few articles have been published to show the uses of cloud storage in libraries. The cost is the main concern. An overview of cloud storage pricing shows a price drop once every one or one-and-a-half years. The author emphasize the data transfer-out costs and demonstrate a case study. Comparisons and analysis of S3 and Glacier have been conducted to show the differences in retrieval and costs.

Cloud storage solutions like Glacier can be very attractive for long-term digital preservation if data can be operated within the provider’s same data zone and data transfer-out can be minimized.

Institutions can benefit from cloud storage by understanding the cost models and data retrieval models. Multiple strategies are suggested to minimize the costs.

The paper is intended to bridge the gap of uses of cloud storage. Cloud storage pricing especially data transfer-out pricing charts are presented to show the price drops over the past eight years. Costs and analysis of storing and retrieving data in Amazon S3 and Glacier are discussed in details. Comparisons of S3 and Glacier show that Glacier has uniqueness and advantages over other cloud storage solutions. Finally strategies are suggested to minimize the costs of using cloud storage. The analysis shows that cloud storage can be very useful in digital preservation.

The purpose of this study is to measure the perceptions and use of cloud services by the students of the University of Dhaka, Bangladesh. The specific objective of this study is to know what perceptions students have about cloud services, why and how they use cloud for academic activities.

For understanding the use of cloud services among the students of Dhaka University, a quantitative survey was carried out to collect data. Printed questionnaires were distributed among the students in different departments and university library. Both open- and close-ended questions were included in the questionnaire. A total of 329 students responded in this survey and the response rate was 85.5%. The collected data were analyzed using Statistical Package for the Social Sciences.

Findings revealed that students are generally aware of cloud services and majority of the respondents use cloud for different purposes. Students used cloud for storage, back up and collaboration purposes and some of Google features are widely used by majority of the students for academic purposes.

To the best of authors’ knowledge, this is the first time an effort has been made to measure the use of cloud services among the students of University of Dhaka. This study will help to raise cloud service awareness among the students and encourage the authorities to adopt appropriate strategies and policies to resolve cloud adoption in university setting. Specially, Center of Excellence in Teaching and Learning of Dhaka University can take some initiatives in this case.

The concept of business process (BP) as a service is a new solution in enterprises for the purpose of using specific BPs. BPs represent combinations of software services that must be properly executed by the resources provided by a company’s information technology infrastructure. As the policy requirements are different in each enterprise, processes are constantly evolving and demanding new resources in terms of computation and storage. To support more agility and flexibility, it is common today for enterprises to outsource their processes to clouds and, more recently, to cloud federation environment. Ensuring the optimal allocation of cloud resources to process service during the execution of workflows in accordance with user policy requirements is a major concern. Given the diversity of resources available in a cloud federation environment and the ongoing process changes required based on policies, reallocating cloud resources for service processing may lead to high computational costs and increased overheads in communication costs.

This paper presents a new adaptive resource allocation approach that uses a novel algorithm extending the natural-based intelligent water drops (IWD) algorithm that optimizes the resource allocation of workflows on the cloud federation which can estimate and optimize final deployment costs. The proposed algorithm is implemented and embedded within the WokflowSim simulation toolkit and tested in different simulated cloud environments with different workflow models.

The algorithm showed noticeable enhancements over the classical workflow deployment algorithms taking into account the challenges of data transfer. This paper made a comparison between the proposed IWD-based workflow deployment (IWFD) algorithm with other proposed algorithms. IWFD presented considerable improvements in the makespan, cost and data transfer in most situations in the cloud federation environment.

An extension for WorkflowSim to support the implementation of BPs in a federation cloud space regarding BP policy. Optimize workflow execution performance in Federated clouds by means of IWFD algorithm.