Research on the Application of Big Data and Cloud Computing Technology in Smart Campus

The current education field is experiencing an innovation driven by big data and cloud technologies,and these advanced technologies play a central role in the construction of smart campuses.Big data technology has a wide range of applications in student learning behavior analysis,teaching resource management,campus safety monitoring,and decision support,which improves the quality of education and management efficiency.Cloud computing technology supports the integration,distribution,and optimal use of educational resources through cloud resource sharing,virtual classrooms,intelligent campus management systems,and Infrastructure-as-a-Service(IaaS)models,which reduce costs and increase flexibility.This paper comprehensively discusses the practical application of big data and cloud computing technologies in smart campuses,showing how these technologies can contribute to the development of smart campuses,and laying the foundation for the future innovation of education models.

The Benefits of Using Google Cloud Computing for Developing Distributed Applications

IT as a dynamic filed changes very rapidly; efficient management of such systems for the most of the companies requires handling tremendous complex situations in terms of hardware and software setup. Hardware and software itself changes quickly with the time and keeping them updated is a difficult problem for the most of the companies; the problem is more emphasized for the companies having large infrastructure of IT facilities such as data centers which are expensive to be maintained. Many applications run on the company premises which require well prepared staff for successfully maintaining them. With the inception of Cloud Computing many companies have transferred their applications and data into cloud computing based platforms in order to have reduced maintaining cost, easier maintenance in terms of hardware and software, reliable and securely accessible services. The benefits of building distributed applications using Google infrastructure are conferred in this paper.

Hybrid Approach for Cost Efficient Application Placement in Fog-Cloud Computing Environments

Fog computing has recently developed as a new paradigm with the aim of addressing time-sensitive applications better than with cloud computing by placing and processing tasks in close proximity to the data sources.However,the majority of the fog nodes in this environment are geographically scattered with resources that are limited in terms of capabilities compared to cloud nodes,thus making the application placement problem more complex than that in cloud computing.An approach for cost-efficient application placement in fog-cloud computing environments that combines the benefits of both fog and cloud computing to optimize the placement of applications and services while minimizing costs.This approach is particularly relevant in scenarios where latency,resource constraints,and cost considerations are crucial factors for the deployment of applications.In this study,we propose a hybrid approach that combines a genetic algorithm(GA)with the Flamingo Search Algorithm(FSA)to place application modules while minimizing cost.We consider four cost-types for application deployment:Computation,communication,energy consumption,and violations.The proposed hybrid approach is called GA-FSA and is designed to place the application modules considering the deadline of the application and deploy them appropriately to fog or cloud nodes to curtail the overall cost of the system.An extensive simulation is conducted to assess the performance of the proposed approach compared to other state-of-the-art approaches.The results demonstrate that GA-FSA approach is superior to the other approaches with respect to task guarantee ratio(TGR)and total cost.

Adaptive Application Offloading Decision and Transmission Scheduling for Mobile Cloud Computing

Offloading application to cloud can augment mobile devices' computation capabilities for the emerging resource-hungry mobile application, however it can also consume both much time and energy for mobile device offloading application remotely to cloud. In this paper, we develop a newly adaptive application offloading decision-transmission scheduling scheme which can solve above problem efficiently. Specifically, we first propose an adaptive application offloading model which allows multiple target clouds coexisting. Second, based on Lyapunov optimization theory, a low complexity adaptive offloading decision-transmission scheduling scheme has been proposed. And the performance analysis is also given. Finally, simulation results show that,compared with that all applications are executed locally, mobile device can save 68.557% average execution time and 67.095% average energy consumption under situations.

Improving Performance of Cloud Computing and Big Data Technologies and Applications

Cloud computing technology is changing the development and usage patterns of IT infrastructure and applications. Virtualized and distributed systems as well as unified management and scheduling has greatly im proved computing and storage. Management has become easier, andOAM costs have been significantly reduced. Cloud desktop technology is develop ing rapidly. With this technology, users can flexibly and dynamically use virtual ma chine resources, companies＇ efficiency of using and allocating resources is greatly improved, and information security is ensured. In most existing virtual cloud desk top solutions, computing and storage are bound together, and data is stored as im age files. This limits the flexibility and expandability of systems and is insufficient for meetinz customers＇ requirements in different scenarios.

Impact of Coronavirus Pandemic Crisis on Technologies and Cloud Computing Applications

In light of the coronavirus disease 2019(COVID-19)outbreak caused by the novel coronavirus,companies and institutions have instructed their employees to work from home as a precautionary measure to reduce the risk of contagion.Employees,however,have been exposed to different security risks because of working from home.Moreover,the rapid global spread of COVID-19 has increased the volume of data generated from various sources.Working from home depends mainly on cloud computing(CC)applications that help employees to efficiently accomplish their tasks.The cloud computing environment(CCE)is an unsung hero in the COVID-19 pandemic crisis.It consists of the fast-paced practices for services that reflect the trend of rapidly deployable applications for maintaining data.Despite the increase in the use of CC applications,there is an ongoing research challenge in the domains of CCE concerning data,guaranteeing security,and the availability of CC applications.This paper,to the best of our knowledge,is the first paper that thoroughly explains the impact of the COVID-19 pandemic on CCE.Additionally,this paper also highlights the security risks of working from home during the COVID-19 pandemic.

Edge Cloud Selection in Mobile Edge Computing(MEC)-Aided Applications for Industrial Internet of Things(IIoT)Services

In many IIoT architectures,various devices connect to the edge cloud via gateway systems.For data processing,numerous data are delivered to the edge cloud.Delivering data to an appropriate edge cloud is critical to improve IIoT service efficiency.There are two types of costs for this kind of IoT network:a communication cost and a computing cost.For service efficiency,the communication cost of data transmission should be minimized,and the computing cost in the edge cloud should be also minimized.Therefore,in this paper,the communication cost for data transmission is defined as the delay factor,and the computing cost in the edge cloud is defined as the waiting time of the computing intensity.The proposed method selects an edge cloud that minimizes the total cost of the communication and computing costs.That is,a device chooses a routing path to the selected edge cloud based on the costs.The proposed method controls the data flows in a mesh-structured network and appropriately distributes the data processing load.The performance of the proposed method is validated through extensive computer simulation.When the transition probability from good to bad is 0.3 and the transition probability from bad to good is 0.7 in wireless and edge cloud states,the proposed method reduced both the average delay and the service pause counts to about 25%of the existing method.

Cloud Computing at a Cross Road: Quality and Risks in Higher Education

The key determinants of cloud computing provide a convincing argument for HEIs and its stakeholders to adopt the innovation. These benefits reflect the essential quality characteristics of the cloud, such as Broad network Access;Measured Service;On-demand Self-Service;Rapid Elasticity;and Resource Pooling. However, there are also risks associated with the cloud, leading to non-adoption, such as Confidence, Privacy, Security, Surety and Trust. Understanding the impact of these factors can support multiple stakeholders, such as students, lecturers, senior managers and admins in their adoptive decision of CC in their respected institutions. Using the Multiview 3 (MV3) methodology, a research model was proposed to explore the key qualities and risks that determine the adoption or non-adoption of CC by UK HEIs from multiple perspectives. An exploratory qualitative study was conducted on 32 University stakeholders across 2 UK Universities. The findings suggest that security, privacy and trust are the key determinants to non-adoption as participants felt that the cloud cannot fully guarantee the safeguarding of sensitive information. Determinants to cloud adoption include improving relationships between students and teachers via collaborative tools, in addition to proposing cloud apps for mobile devices for accessing virtual learning materials and email securely off-campus. In conclusion, University stakeholders are still at a cross-road when it comes to cloud adoption, but future advances of the cloud may help to steer their decision to adopt this innovative technology given its overwhelming potential.

Mobile Cloud Computing and Applications

In 2010, cloud computing gained momentum. Cloud computing is a model for real-time, on-demand, pay-for-use network access to a shared pool of configurable computing and storage resources. It has matured from a promising business concept to a working reality in both the private and public IT sectors. The U.S. government, for example, has requested all its agencies to evaluate cloud computing alternatives as part of their budget submissions for new IT investment.

Design of ECC based Secured Cloud Storage Mechanism for Transaction Rich Applications

Cloud computing is the highly demanded technology nowadays.Due to the service oriented architecture,seamless accessibility and other advantages of this advent technology,many transaction rich applications are making use of it.At the same time,it is vulnerable to hacks and threats.Hence securing this environment is of at most important and many research works are being reported focusing on it.This paper proposes a safe storage mechanism using Elliptic curve cryptography(ECC)for the Transaction Rich Applications(TRA).With ECC based security scheme,the security level of the protected system will be increased and it is more suitable to secure the delivered data in the portable devices.The proposed scheme shields the aligning of different kind of data elements to each provider using an ECC algorithm.Analysis,comparison and simulation prove that the proposed system is more effective and secure for the Transaction rich applications in Cloud.

A multi-feature-based intelligent redundancy elimination scheme for cloud-assisted health systems

Redundancy elimination techniques are extensively investigated to reduce storage overheads for cloud-assisted health systems.Deduplication eliminates the redundancy of duplicate blocks by storing one physical instance referenced by multiple duplicates.Delta compression is usually regarded as a complementary technique to deduplication to further remove the redundancy of similar blocks,but our observations indicate that this is disobedient when data have sparse duplicate blocks.In addition,there are many overlapped deltas in the resemblance detection process of post-deduplication delta compression,which hinders the efficiency of delta compression and the index phase of resemblance detection inquires abundant non-similar blocks,resulting in inefficient system throughput.Therefore,a multi-feature-based redundancy elimination scheme,called MFRE,is proposed to solve these problems.The similarity feature and temporal locality feature are excavated to assist redundancy elimination where the similarity feature well expresses the duplicate attribute.Then,similarity-based dynamic post-deduplication delta compression and temporal locality-based dynamic delta compression discover more similar base blocks to minimise overlapped deltas and improve compression ratios.Moreover,the clustering method based on block-relationship and the feature index strategy based on bloom filters reduce IO overheads and improve system throughput.Experiments demonstrate that the proposed method,compared to the state-of-the-art method,improves the compression ratio and system throughput by 9.68%and 50%,respectively.

Development of a web-platform for mining applications

‘‘Web ground control"(web GC) provides users with instantaneous access to mine design applications anywhere, at any time, through a web browser.Utilizing a web-based multiple-tier architecture, users are able to easily access ground control designs, perform on-demand calculations in the field, as well as facilitate project collaborations across multiple users, devices, and operating systems.Currently, the web GC platform contains five ground control related design applications previously developed and distributed by the US National Institute of Occupational Safety and Health(NIOSH), that is, analysis of roof bolt stability(ARBS), analysis of longwall pillar stability(ALPS), analysis of retreat mining stability(ARMPS), analysis of retreat mining stability–highwall mining(ARMPS-HWM), and analysis of horizontal stress in mining(AHSM).With respect to design decisions made by the web GC development team, the web GC platform will be able to further integrate future mine design applications providing the mining industry with one of a kind umbrella suite of ground control related software available at ones fingertips.The following paper provides a detailed overview on the current state of the web GC platform with discussions ranging from back-end database development and design to the front-end user-platform interface.Based on current progress in platform development as well as beta testing results, the web GC platform is scheduled for release in the fall of 2018.

＂Smart Cafe＂： A Mobile Local Computing System Based On Indoor Virtual Cloud

With network developing and virtualization rising, more and more indoor environment （POIs） such as care, library, office, even bus and subway can provide plenty of bandwidth and computing resources. Meanwhile many people daily spending much time in them are still suffering from the mobile device with limited resources. This situation implies a novel local cloud computing paradigm in which mobile device can leverage nearby resources to facilitate task execution. In this paper, we implement a mobile local computing system based on indoor virtual cloud. This system mainly contains three key components： 1）As to application, we create a parser to generate the ＂method call and cost tree＂ and analyze it to identify resource- intensive methods. 2） As to mobile device, we design a self-learning execution controller to make offtoading decision at runtime. 3） As to cloud, we construct a social scheduling based application-isolation virtual cloud model. The evaluation results demonstrate that our system is effective and efficient by evaluating CPU- intensive calculation application, Memory- intensive image translation application and I/ O-intensive image downloading application.

Dependable Deployment Method for Multiple Applications in Cloud Services Delivery Network

The mutual-interference phenomenon among multiple applications delivered as services through Cloud Services Delivery Network(CSDN)influences their QoS seriously.In order to deploy multiple applications dependably and efficiently,we propose the Multiple Applications Co-Exist(MACE)method.MACE classifies multiple applications into different types and deploys them using isolation to some extent.Meanwhile,resource static allocation,dynamic supplement and resource reserved mechanism to minimize mutual-interference and maximize resource utilization are designed.After MACE is applied to a real large-scale CSDN and evaluated through 6-month measurement,we find that the CSDN load is more balanced,the bandwidth utilization increases by about 20%,the multiple applications'potential statistical multiplexing ratio decreases from 12% to 5%,and the number of complaint events affecting the dependability of CSDN services caused by multiple applications'mutual-interference has dropped to 0.Obviously,MACE offers a tradeoff and improvement for the dependability and efficiency goals of CSDN.

Cloud-Based Access Control to Preserve Privacy in Academic Web Application

Emerging cloud computing has introduced new platforms for developing enterprise academic web applications, where software, platforms and infrastructures are published to the globe as services. Software developers can build their systems by multiple invocations of these services. This research is devoted to investigating the management and data flow control over enterprise academic web applications where web services and developed academic web application are constructing infrastructure-networking scheme at the application level. Academic web services are invoked over http port and using REST based protocol;thus traditional access control method is not enough to control the follow of data using host and port information. The new cloud based access control rules proposed here are to be designed and implemented to work at this level. The new proposed access control architecture will be a web service gateway, and it published itself as a service (SaaS). We used three case studies to test our moodle and then we apply JSON parsers to perceive web service description file (WSDL file) and supply policies according to data are to be allowed or denied based on user roll through our parsing.

E-Learning during COVID-19 Outbreak: Cloud Computing Adoption in Indian Public Universities

In the COVID-19 pandemic situation,the need to adopt cloud computing(CC)applications by education institutions,in general,and higher education(HE)institutions,in particular,has especially increased to engage students in an online mode and remotely carrying out research.The adoption of CC across various sectors,including HE,has been picking momentum in the developing countries in the last few years.In the Indian context,the CC adaptation in the HE sector(HES)remains a less thoroughly explored sector,and no comprehensive study is reported in the literature.Therefore,the aim of the present study is to overcome this research vacuum and examine the factors that impact the CC adoption(CCA)by HE institutions(HEIs)in India.The scope of the study is limited to public universities(PUs)in India.There are,in total,465 Indian PUs and among these 304 PUs,(i.e.,65%PUs)are surveyed using questionnaire-based research.The study has put forth a novel integrated technology adoption framework consisting of the Technology Acceptance Model(TAM),Technology-Organization-Environment(TOE),and Diffusion of Innovation(DOI)in the context of the HES.This integrated TAM-TOE-DOI framework is utilized in the study to analyze eleven hypotheses concerning factors of CCA that have been tested using structural equation modelling(SEM)and confirmatory factor analysis(CFA).The findings reveal that competitive advantage(CA),technology compatibility(TC),technology readiness(TR),senior leadership support,security concerns,government support,and vendor support are the significant contributing factors of CCA by Indian PUs.The study contends that whereas the rest of the factors positively affect the PUs’intention towards CCA,security concerns are a significant reason for the reluctance of these universities against adopting CC.The findings demonstrated the application of an integrated TAM-TOE-DOI framework to assess determining factors of CCA in Indian PUs.Further,the study has given useful insights into the successful CCA by Indian PUs,which will facilitate eLearning and remote working during COVID-19 or similar outbreak.

Spring Cloud云原生应用开发与实现

随着云计算的发展,计算资源供给方式发生了革命性变化。为了让所开发的应用能更好地利用计算资源,云原生应用应运而生。首先介绍云计算和云原生概念与分布式框架Spring Cloud及其相关组件;其次展示了如何以云原生的理念和开发方式构建一个云原生应用架构,包括集中配置中心、API Getaway网关、服务消费和负载均衡器、服务熔断与降级、分布式链路追踪等模块;最后以此应用为例,介绍其在打包、部署时的部分规划,以充分利用计算资源。相较于传统开发方式,采用云原生理念可最大化地利用计算资源,提高应用弹性,降低开发成本。

Reliable cloud storage system for mobile devices using personal computer

In recent years,the use of mobile devices such as smart phones,tablet PCs,etc.is rapidly increasing.In case of these mobile devices,the storage space is limited due to their characteristics.To make up for the limited space of storage in mobile devices,several methods are being researched.Of these,cloud storage service(CSS),one of cloud computing services,is an efficient solution to compensate such limited storage space.CSS is a service of storing files to the storage and thus getting access to stored files through networks(Internet)at anytime,anywhere.As for the existing CSS,users store their personally important files in the cloud storage,not in their own computers.It may cause security problems such as the leaking of information from private files or the damaging to the information.Thus,we propose a cloud storage system which can solve the security problem of CSS for mobile devices using the personal computer.Our system is deigned to store and manage files through the direct communication between mobile devices and personal computer storages by using the software as a service(SaaS),one of computing services,instead of directly storing files into cloud storages.

Studies and Practices on Cloud-Based Practical Teaching Unified Services System and Teaching Mode

Traditional practical teaching has problems on low reusability, high cost and low collaboration ability. To solve these problems, this paper proposes a solution that is to build and use a novel practical teaching platform based on cloud computing. By utilizing advanced information technology, for example, cloud computing, this solution can present a unified service system providing practical teaching resource management, innovation resource management and knowledge management both inside and outside class. Moreover, an instance implementing the cloud-based practical teaching unified services system, Yun Hai, would be detailedly discussed in this paper. The system deployment, resource configuration and matched practice teaching mode will be presented. Yun Hai is independently developed by State Key Laboratory of Networking and Switching Technology and has been deployed and employed in many institutions. To verify the effectiveness of this teaching platform, we take Data Mining, a representative course of computer science, as an example, and analyze how the system would perform when applied to such course which contains cross-disciplinary knowledges. The practice indicates that this teaching system and practical teaching mode can improve convenience and flexibility on practical teaching resource. This kind of one-stop service can contribute to the overall teaching quality improvement.