Cloud-based Environment Research Articles

Towards Scalability for Federated Identity Systems for Cloud-Based Environments

As multi-tenant authorization and federated identity management systems for cloud computing matures, the provisioning of services using this paradigm allows maximum efficiency on business that requires access control. However, regarding scalability support, mainly horizontal, some characteristics of those approaches based on central authentication protocols are problematic. The objective of this work is to address these issues by providing an adapted sticky-session mechanism for a Shibboleth architecture using JASIG CAS. This alternative, compared with the recommended distributed memory approach, shown improved efficiency and less overall infrastructure complexity, as well as demanding less 58% of computational resources and improving throughput (requests per second) by 11%.

Preface to the December 2015 issue

We are glad to present the last issue of 2015, completing Volume 18 of the CLEI Electronic Journal. This issue is comprised by the following regular papers.The first paper, “Quality of Protection on WDM networks: A Recovery Probability based approach”, by M. D. Rodas-Brítez and D. P. Pinto-Roa, features a proposal of a new quality of protection (QoP) paradigm for Wavelength Division Multiplexing optical networks. The new approach is flexible, allowing the network administrator to define and select a set of protection levels, based on recovery probabilities which measure the degree of conflict among primary lightpaths sharing backup lightpaths. To show the interest of the approach, a Genetic Algorithm is used to design a routing strategy by multi-objectiveoptimization, minimizing the number of blocked requests, the number of services without protection, the total differences between the requested QoP and the assigned QoP, and the network cost.The second paper, “Towards Scalability for Federated Identity Systems for Cloud-Based Environments”, by A.A. Pereira, J. B. M. Sobral and C. M. Westphall, addresses scalability issues in identity management for cloud computing environments. The authors propose an adapted sticky-session mechanism, as an alternative approach to the more common distributed memory approach, and discuss the implications in therms of computational resources, throughput and overall efficiency. The following work, “Formal Analysis of Security Models for Mobile Devices, Virtualization Platforms, and Domain Name Systems”, by G. Betarte and C. Luna,tackles security models for security-critical applications in three areas: mobile devices, virtualization platforms, and domain name systems. The authors develop formalizations using the Calculus of Inductive Constructions, to study different usual variants of security models in these platforms and their properties.The last paper of this issue is “Digi-Clima Grid: image processing and distributed computing for recovering historical climate data”, by authors S. Nesmachnow, G. Usera and F. Brasileiro. This paper reports an experience of implementing semi-automatic techniques for digitalizing and recovering historical climate records applying parallel computing techniques over distributed computing infrastructures, which was applied to Uruguayan historical climate data.As we complete now the eighteenth year of continued existence of CLEIej, we thank the regional community for its continued support, and we encourage researchers working in computer science and its applications to consider submitting their work to CLEIej, as the the leading electronic, open access journal in Computer Science in Latin America.

On the potential applications of data mining for information security provision of cloud-based environments

An overview of several applications of techniques and models of data mining (DM) in applied information security systems is presented. Special focus is put on the new and actively developed area of cloud-based computing environments. Both the available and future applicabilities of models and techniques of artificial intelligence to IS problem solving are discussed.

Distributed cache replacement method for geospatial data using spatiotemporal locality-based sequence

Specific features of tile access patterns can be applied in a cache replacement strategy to a limited distributed high-speed cache for the cloud-based networked geographic information services (NGISs), aiming to adapt to changes in the access distribution of hotspots. By taking advantage of the spatiotemporal locality, the sequential features in tile access patterns, and the cache reading performance in the burst mode, this article proposes a tile sequence replacement method, which involves structuring a Least Recently Used (LRU) stack into three portions for the different functions in cache replacement and deriving an expression for the temporal locality and popularity of the relevant tile to facilitate the replacement process. Based on the spatial characteristics of both the tiles and the cache burst mode with regard to reading data, the proposed method generates multiple tile sequences to reflect spatiotemporal locality in tile access patterns. Then, we measure the caching value by a technique based on a weighted-based method. This technique draws on the recent access popularity and low caching costs of tile sequences, with the aim of balancing the temporal and spatial localities in tile access. It ranks tile sequences in a replacement queue to adapt to the changes in accessed hotspots while reducing the replacement frequency. Experimental results show that the proposed method effectively improves the hit rate and utilization rate for a limited distributed cache while achieving satisfactory response performance and high throughput for users in an NGIS. Therefore, it can be adapted to handle numerous data access requests in NGISs in a cloud-based environment.

Distributed FlowVisor: a distributed FlowVisor platform for quality of service aware cloud network virtualisation

Cloud-based virtual networking environments are required to provide fine-grained quality of service (QoS) control without sacrificing scalability. However, no single approach can currently achieve these two goals simultaneously. FlowVisor is a building block to virtualise networks with fine-grained QoS support; however, scalability issues caused by the OpenFlow protocol and the centralised control model are a major concern. This study introduces a distributed FlowVisor (DFVisor) platform to address these scalability issues. The proposed DFVisor uses a layered overlay mechanism to improve network addressing space and switch capacity. DFVisor uses a distributed synchronised two-level database system with a synchronisation mechanism to enable the centralised control functions in the current FlowVisor platform in distributed control modules within the virtual network controllers. Therefore it removes a single point of failure in the network and reduces the flow setup latency without sacrificing the centralised network configuration and management capabilities. More importantly, the proposed DFVisor platform enables an advanced push-based flow setup and statistics collection mechanism to address scalability issues caused by the current pull-based flow setup and statistics collection method. A DFVisor prototype and an evaluation of this distributed synchronised two-level database are presented, and key issues for future research are discussed.

차량 클라우드 환경에서 안전한 통신을 위한 프레임워크 설계

Vehicle cloud technology is a fusion technology of vehicle communication technology and cloud computing used in wired and wireless Internet, and has attracted attention as a new IT paradigm. It is expected that it would contribute to resolve the road traffic problem with effective communication by providing computer, sensor, communication, device, and resource. but security is necessary to apply vehicle cloud environment and it have to resolve security threats and various attacks occurred in wired and wireless vehicle environment. Therefore, in this paper, we designed security framework to provide secure communication between vehicle and vehicle, and vehicle and the Road side in the vehicle cloud environment. Safety and security of the vehicle environment was satisfied with the security requirements of the vehicle and cloud-based environment, and increased efficiency than the conventional vehicle network communication protocols.

The Voyage Home: New Mexico Libraries Migrate to WMS, OCLC's Cloud-Based ILS

Cloud-computing is causing a major shift in the way organizations manage their data. For libraries this shift entails the switch from stand-alone ILSs to cloud-based systems. The new generation of ILSs embraces this model. The University of New Mexico Libraries undertook the migration to OCLC's cloud-based ILS, WorldShare Management Services (WMS). The process required choosing the vendor, preparing the data for migration, and implementing workflows. Through this article the authors will look at each of these stages of the migration and describe the process along the way. They will conclude with a look at the major paradigm shift caused by moving to a cloud-based environment.

Porting bioinformatics applications from grid to cloud: A macromolecular surface analysis application case study

In this paper we describe our experience in exploiting different cloud-based environments for an actual use case taken from the bioinformatics domain – the molecular surfaces analysis - that identifies similarities and possible complementarities in the protein surfaces. The analysis of macromolecular surfaces is important since protein surface conformations drive many biological reactions. We developed a workflow that performs the macromolecular surfaces analysis and provides interesting results from a scientific point of view. An important issue is represented by the fact that it is highly compute-intensive, therefore it cannot be run on a single CPU system for meaningful use cases and a parallel infrastructure is required to obtain reasonable execution time. For a decade grid infrastructures have represented suitable solutions to achieve cost effective computational power for Bioinformatics applications. However, these solutions do not offer an adequate customisation of the computational environment (e.g. installing databases and configuring virtual network) due to the rigid organisation of the storage and computational sites. Running applications on customised machines obtained by user-defined images simplifies the computing model, decreases the failure rates and therefore reduces waiting times for production analysis with respect to the canonical grid computations. For these reasons a cloud-based approach is more suitable than a pure grid paradigm. We experimented using two cloud-based approaches, based on the Worker Node On Demand Service and on OpenStack, to run the molecular surfaces analysis use case and we compared the results in terms of performance, efficiency and efforts to build the computing model with respect to grid computing.

Energy-Efficient Networking Solutions in Cloud-Based Environments

The energy consumed by data centers hosting cloud services is increasing enormously. This brings the need to reduce energy consumption of different components in data centers. In this work, we focus on energy efficiency of the networking component. However, how different networking solutions impact energy consumption is still an open question. We investigate the state of the art in energy-efficient networking solutions in cloud-based environments. We follow a systematic literature review method to select primary studies. We create a metamodel based on the codes extracted from our primary studies using the Coding analytical method. Our findings show three abstraction levels of the proposed networking solutions to achieve energy efficiency in cloud-based environments: Strategy, Solution, and Technology. We study the historical trends in the investigated solutions and conclude that the emerging and most widely adopted one is the Decision framework .

CPU Provisioning Algorithms for Service Differentiation in Cloud-Based Environments

This work focuses on the design, analysis and evaluation of Dynamic Weighted Round Robin (DWRR) algorithms that can guarantee CPU service shares in clusters of servers. Our motivation comes from the need to provision multiple server CPUs in cloud-based data center environments. Using stochastic control theory we show that a class of DWRR policies provide the service differentiation objectives, without requiring any knowledge about the arrival and the service process statistics. The member policies provide the data center administrator with trade-off options, so that the communication and computation overhead of the policy can be adjusted. We further evaluate the proposed policies via simulations, using both synthetic and real traces obtained from a medium scale mobile computing application.

The Effect of Status Quo Bias on Cloud System Adoption

The cloud-based environment has been viewed as an elastic alternative to hosting information systems. Although a lot of attention is paid in cloud system applications, organizations in business are still skeptical of adopting cloud framework. The purpose of this study is to investigate the determinants on firms' reactions toward cloud systems adoption from status quo bias perspective. By using cloud enterprise resource planning (ERP) as a research target, data were collected from the leading manufacturing firms in Taiwan. The results indicate that institutional pressures, switching benefits, and switching costs have significant influence on perceived value. Switching benefits and switching costs are key determinants of perceived risk. Perceived value contributes towards organizational adoption intentions, while perceived risk has significant influence on organizational resistance. The findings provide a foundation for understanding the possible determinants of cloud systems adoption as well as valuable implications for organizations seeking to utilize cloud-based framework.

SECURITY ASPECTS OF CLOUD-BASED MOBILE LEARNING

The paper attempts to outline the security issues in the development and application of cloud-based mobile learning. A brief definition of the mobile learning, its components and related technologies and devices is given. The specific characteristics of social media, big data and cloud computing are summarized in relation with their integration in the mobile learning and its transformation to a cloud-based environment. The main security threats to this type of learning are pointed out and some recommendations for providing security learning are given are given.

User perceptions of the technology characteristics in a cloud-based collaborative learning environment: a qualitative study

The purpose of this study was to assess user perceptions of technology characteristics, which is a complicated construct in task technology fit model, in a cloud-based collaborative learning environment. For this purpose, cloud computing characteristics cited in the previous related research, were categorised into cost saving, ease of implementation, flexibility, mobility, scalability, sustainability, personalization, processing capabilities, agility, collaboration, usability, risk reduction, measured service, on demand self-service, and resource pooling. Interviews were then conducted with students who had some experience in using cloud-based applications for collaborative learning. Directed content analysis was performed using ATLAS.ti software to organise the coding process. The results of coding data showed that collaboration, mobility, and personalisation, which resulted from previous related literature, are also cited by a large number of participants in interviews as being significant characteristics of cloud-based collaborative learning applications. Organisational cost saving, ease of implementation, flexibility elasticity, scalability, sustainability, processing capabilities, agility, usability, risk reduction, measured service, on demand self-service, and resource pooling were not mentioned by any of the participants at all. However, easy monitoring and assessment, time control and saving, cost saving, accessibility, ease of use, and easy connection to other applications were new themes that emerged inductively during data analysis.

Clustering molecular dynamics trajectories for optimizing docking experiments.

Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR) model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand.

The cloud-based learning environment of educational institutions: the current developments

The purpose of the article is to describe the state of the art of cloud-based learning environment formation and current developments of its design, the main task – analyze of cloud-based learning tools and services use at the educational institutions in Ukraine, the object – the cloud-based learning environment, the subject – the cloud-based learning environment of educational institutions, the main research method is analysis and design.
 The current tendencies of cloud computing technologies use as the e-learning platform of educational institutions in Ukraine are described. The state of the art of cloud computing services application is revealed. The results of a survey of cloud-based learning tools and services use at the educational institutions in Ukraine are presented. The holistic trends of cloud-based learning environment development are described. The results of holistic learning modeling are reported. Perspective ways of cloud-based learning environment development at the educational institutions in Ukraine are exposed.

EXPLORING USERS’ ATTITUDES AND INTENTIONS TOWARD THE ADOPTION OF CLOUD COMPUTING IN SAUDI ARABIA: AN EMPIRICAL INVESTIGATION

Over the past few years, cloud computing has evolve d as one of the major advances in the field of Information Technology (IT) utilizing third-party s ervices. Therefore, trust in cloud vendors as well as the determination of potential risks, such as privacy a nd security issues, are crucial for ensuring the su ccessful adoption of an appropriate cloud. Prior research ha ve addressed the technical aspects of cloud-based environments, such as cloud virtualization, scalabi lity and security. Nevertheless, it is argued that the biggest obstacle of cloud computing is not technolo gical, rather it is perceptual or attitudinal. The adoption of cloud computing has been central to several scho larly research areas, particularly user acceptance. This study presents an extended Technology Acceptance Model (TAM), which integrates Trust (TR), Anxiety (ANX) and Perceived Risk (PR), to investigate users ’ attitudes and intentions toward the adoption of c loud computing. The proposed model was empirically examined using the Structural Equation Model (SEM) to analyze data gathered by a survey of both IT profes sionals and end users. The results herein suggested that trust, anxiety and PR can be successfully integrate d within the TAMs. Trust has demonstrated to have a strong positive influence on Perceived Ease of Use (PEOU), but it had no significant effects on Perceived Use fulness (PU). Both anxiety and PR were found to have significant negative effects on PEOU and PU. In addition, Behavioral Intention (BI) to use the cloud can be p redicted by trust, attitudes and PU, as PR was show n to have no significant effect on BI. The proposed model, including PR, trust and anxiety, has been demonstrated to be a true predictor of user intentions, toward t he use of cloud computing, within the context of Sa udi Arabia.

Dynamic scaffolding in a cloud-based problem representation system

Purpose– The purpose of this paper is to argue for the need to develop pre-service teachers’ problem solving ability, in particular, in the context of real-world complex problems.Design/methodology/approach– To argue for the need to develop pre-service teachers’ problem solving skills, the authors describe a web-based problem representation system that is embedded with levels of scaffolding to support the claim.Findings– The authors’ conceptualisation of this cloud-based environment is also very much aligned with the development of pre-service teachers’ systems thinking. Teacher learning itself is a complex system that involves many processes, mechanisms and interactions of elements, and the outcomes may be highly unpredictable (Opfer and Pedder, 2011). As a result of the complex nature of teacher learning, it would be meaningful to frame teacher learning as a complex system. An approach to enable pre-service teachers to be aware of this complexity is to situate them in a systems thinking context.Originality/value– This paper discusses a system which was developed for problem solving. The levels of adaptive scaffoldings embedded within the system is an innovation which is not found in other similar research projects.

Research of Automatic Software Test Platform with Virtualization Technology

This paper studies the software automatic test in virtual machine environment. The existing software automatic testing technology is not compatible for virtual machine. Cloud-based virtual environment provides a new means for the software test. A novel testing framework is proposed in this paper. The new technology combined cloud-based virtual environment and related the software automation tool. The fully test procedure are provided with test design, test develop, test execute and test result collection. The character for different application could be supported in this framework. The virtualization technology is used to test some applications and proved effective.

A Cloud-Based Environment for Collaborative Resources Management

The interaction between users and digital devices has deeply changed in the last decades. In particular, the so called desktop metaphor relied on assumptions which have been modified by the rise of new paradigms, such as Web 2.0 and Cloud Computing. This paper discusses the limits of the desktop metaphor and proposes a new interaction model, TablePlusPlus (T++), aimed at providing Web and Cloud users with interaction mechanisms fulfilling their needs, i.e., the possibility of handling activity contexts, collaborating with other users, and homogeneously managing heterogeneous objects. T++ tables provide a context-based environment which enables a homogeneous treatment of heterogeneous content items, enhanced by a table-level annotation mechanism supporting an abstract view over resources, which is missing in standard current desktop and collaborative environments. In order to evaluate the effectiveness of the proposed model, this work developed a prototype and tested it in two controlled experiments, whose results are definitely encouraging.

Cloud-scale genomic signals processing classification analysis for gene expression microarray data.

As microarray data available to scientists continues to increase in size and complexity, it has become overwhelmingly important to find multiple ways to bring inference though analysis of DNA/mRNA sequence data that is useful to scientists. Though there have been many attempts to elucidate the issue of bringing forth biological inference by means of wavelet preprocessing and classification, there has not been a research effort that focuses on a cloud-scale classification analysis of microarray data using Wavelet thresholding in a Cloud environment to identify significantly expressed features. This paper proposes a novel methodology that uses Wavelet based Denoising to initialize a threshold for determination of significantly expressed genes for classification. Additionally, this research was implemented and encompassed within cloud-based distributed processing environment. The utilization of Cloud computing and Wavelet thresholding was used for the classification 14 tumor classes from the Global Cancer Map (GCM). The results proved to be more accurate than using a predefined p-value for differential expression classification. This novel methodology analyzed Wavelet based threshold features of gene expression in a Cloud environment, furthermore classifying the expression of samples by analyzing gene patterns, which inform us of biological processes. Moreover, enabling researchers to face the present and forthcoming challenges that may arise in the analysis of data in functional genomics of large microarray datasets.