scholarly journals Research on Auto-Scaling of Web Applications in Cloud: Survey, Trends and Future Directions

2019 ◽  
Vol 20 (2) ◽  
pp. 399-432 ◽  
Author(s):  
Parminder Singh ◽  
Pooja Gupta ◽  
Kiran Jyoti ◽  
Anand Nayyar

Cloud computing emerging environment attracts many applications providers to deploy web applications on cloud data centers. The primary area of attraction is elasticity, which allows to auto-scale the resources on-demand. However, web applications usually have dynamic workload and hard to predict. Cloud service providers and researchers are working to reduce the cost while maintaining the Quality of Service (QoS). One of the key challenges for web application in cloud computing is auto-scaling. The auto-scaling in cloud computing is still in infancy and required detail investigation of taxonomy, approach and types of resources mapped to the current research. In this article, we presented the literature survey for auto-scaling techniques of web applications in cloud computing. This survey supports the research community to find the requirements in auto-scaling techniques. We present a taxonomy of reviewed articles with parameters such as auto-scaling techniques, approach, resources, monitoring tool, experiment, workload, and metric, etc. Based on the analysis, we proposed the new areas of research in this direction.

2017 ◽  
Vol DC CPS 2017 (01) ◽  
pp. 11-21
Author(s):  
Okoye J. A. ◽  
Mbachu C. B

With cloud computing, web application providers can easily move their applications to cloud data centers. On-demand cloud elasticity allows cloud users to acquire or release computing resources on demand. For complex computational workloads, this makes auto-scaling of resources possible for providers especially under dynamic workload. In all cases, cost optimization for system resources and Quality of Service (QoS) remains the top concern. This paper discussed cloud computing as a smart alternative to legacy computing models. Its taxonomy, characteristics, Security Objectives, Service level agreements, benefits and challenges are presented. A conceptual framework for cloud collaboration among the various states of Nigeria is presented. Startups and other low scale enterprises will readily benefit from cloud based collaboration.


Author(s):  
VINITHA S P ◽  
GURUPRASAD E

Cloud computing has been envisioned as the next generation architecture of IT enterprise. It moves the application software and databases to the centralized large data centers where management of data and services may not be fully trustworthy. This unique paradigm brings out many new security challenges like, maintaining correctness and integrity of data in cloud. Integrity of cloud data may be lost due to unauthorized access, modification or deletion of data. Lacking of availability of data may be due to the cloud service providers (CSP), in order to increase their margin of profit by reducing the cost, CSP may discard rarely accessed data without detecting in timely fashion. To overcome above issues, flexible distributed storage, token utilizing, signature creations used to ensure integrity of data, auditing mechanism used assists in maintaining the correctness of data and also locating, identifying of server where exactly the data has been corrupted and also dependability and availability of data achieved through distributed storage of data in cloud. Further in order to ensure authorized access to cloud data a admin module has been proposed in our previous conference paper, which prevents unauthorized users from accessing data and also selective storage scheme based on different parameters of cloud servers proposed in previous paper, in order to provide efficient storage of data in the cloud. In order to provide more efficiency in this paper dynamic data operations are supported such as updating, deletion and addition of data.


Author(s):  
Romulo de Almeida Neves ◽  
Willian Massami Watanabe ◽  
Rafael Oliveira

Context: Widgets are reusable User Interfaces (UIs) components frequently delivered in Web applications.In the web application, widgets implement different interaction scenarios, such as buttons, menus, and text input.Problem: Tests are performed manually, so the cost associated with preparing and executing test cases is high.Objective: Automate the process of generating functional test cases for web applications, using intermediate artifacts of the web development process that structure widgets in the web application. The goal of this process is to ensure the quality of the software, reduce overall software lifecycle time and the costs associated with tests.Method:We elaborated a test generation strategy and implemented this strategy in a tool, Morpheus Web Testing. Morpheus Web Testing extracts widget information from Java Server Faces artifacts to generate test cases for JSF web applications. We conducted a case study for comparing Morpheus Web Testing with a state of the art tool (CrawlJax).Results: The results indicate evidence that the approach Morpheus Web Testing managed to reach greater code coverage compared to a CrawlJax.Conclusion: The achieved coverage values represent evidence that the results obtained from the proposed approach contribute to the process of automated test software engineering in the industry.


Author(s):  
Jayashree K ◽  
Babu R ◽  
Chithambaramani R

The Internet of Things (IoT) architecture has gained an increased amount of attention from academia as well as the industry sector as a significant methodology for the development of innovative applications and systems. Currently, the merging of this architecture with that of Cloud computing has been largely motivated by the need for various applications and infrastructures in IoT. In addition to this, the Cloud ascends as an eminent solution that would help solve various challenges that are faced by the IoT standard when varied physical devices. There are an excessive number of Cloud service providers the web along with many other services. Thus, it becomes critical to choose the provider who can be efficient, consistent, and suitable, and who can deliver the best Quality of Service (QoS). Thus, this chapter discusses QoS for cloud computing and IoT.


2014 ◽  
Vol 701-702 ◽  
pp. 1106-1111 ◽  
Author(s):  
Xin Zheng Zhang ◽  
Ya Juan Zhang

As information and processes are migrating to the cloud, Cloud Computing is drastically changing IT professionals’ working environment. Cloud Computing solves many problems of conventional computing. However, the new technology has also created new challenges such as data security, data ownership and trans-code data storage. We discussed about Cloud computing security issues, mechanism, challenges that Cloud service providers and consumers face during Cloud engineering. Based on concerning of security issues and challenges, we proposed several encryption algorithms to make cloud data secure and invulnerable. We made comparisons among DES, AES, RSA and ECC algorithms to find combinatorial optimization solutions, which fit Cloud environment well for making cloud data secure and not to be hacked by attackers.


The tradition of moving applications, data to be consumed by the applications and the data generated by the applications is increasing and the increase is due to the advantages of cloud computing. The advantages of cloud computing are catered to the application owners, application consumers and at the same time to the cloud datacentre owners or the cloud service providers also. Since IT tasks are vital for business progression, it for the most part incorporates repetitive or reinforcement segments and framework for power supply, data correspondences associations, natural controls and different security gadgets. An extensive data centre is a mechanical scale task utilizing as much power as a community. The primary advantage of pushing the applications on the cloud-based data centres are low infrastructure maintenance with significant cost reduction for the application owners and the high profitability for the data centre cloud service providers. During the application migration to the cloud data centres, the data and few components of the application become exposed to certain users. Also, the applications, which are hosted on the cloud data centres must comply with the certain standards for being accepted by various application consumers. In order to achieve the standard certifications, the applications and the data must be audited by various auditing companies. Few of the cases, the auditors are hired by the data centre owners and few of times, the auditors are engaged by application consumers. Nonetheless, in both situations, the auditors are third party and the risk of exposing business logics in the applications and the data always persists. Nevertheless, the auditor being a third-party user, the data exposure is a high risk. Also, in a data centre environment, it is highly difficult to ensure isolation of the data from different auditors, who may not be have the right to audit the data. Significant number of researches have attempted to provide a generic solution to this problem. However, the solutions are highly criticized by the research community for making generic assumptions during the permission verification process. Henceforth, this work produces a novel machine learning based algorithm to assign or grant audit access permissions to specific auditors in a random situation without other approvals based on the characteristics of the virtual machine, in which the application and the data is deployed, and the auditing user entity. The results of the proposed algorithm are highly satisfactory and demonstrates nearly 99% accuracy on data characteristics analysis, nearly 98% accuracy on user characteristics analysis and 100% accuracy on secure auditor selection process


Author(s):  
Deepika T. ◽  
Prakash P.

The flourishing development of the cloud computing paradigm provides several services in the industrial business world. Power consumption by cloud data centers is one of the crucial issues for service providers in the domain of cloud computing. Pursuant to the rapid technology enhancements in cloud environments and data centers augmentations, power utilization in data centers is expected to grow unabated. A diverse set of numerous connected devices, engaged with the ubiquitous cloud, results in unprecedented power utilization by the data centers, accompanied by increased carbon footprints. Nearly a million physical machines (PM) are running all over the data centers, along with (5 – 6) million virtual machines (VM). In the next five years, the power needs of this domain are expected to spiral up to 5% of global power production. The virtual machine power consumption reduction impacts the diminishing of the PM’s power, however further changing in power consumption of data center year by year, to aid the cloud vendors using prediction methods. The sudden fluctuation in power utilization will cause power outage in the cloud data centers. This paper aims to forecast the VM power consumption with the help of regressive predictive analysis, one of the Machine Learning (ML) techniques. The potency of this approach to make better predictions of future value, using Multi-layer Perceptron (MLP) regressor which provides 91% of accuracy during the prediction process.


2020 ◽  
Author(s):  
Dinesh Arpitha R ◽  
Sai Shobha R

Cloud computing is the computing technology which provides resources like software, hardware, services over the internet. Cloud computing provides computation, software, data access, and storage services that do not require end- user knowledge of the physical location and configuration of the system that delivers the services. Cloud computing enables the user and organizations to store their data remotely and enjoy good quality applications on the demand without having any burden associated with local hardware resources and software managements but it possesses a new security risk towards correctness of data stored at cloud. The data storage in the cloud has been a promising issue in these days. This is due to the fact that the users are storing their valuable data and information in the cloud. The users should trust the cloud service providers to provide security for their data. Cloud storage services avoid the cost storage services avoids the cost expensive on software, personnel maintains and provides better performance less storage cost and scalability, cloud services through internet which increase their exposure to storage security vulnerabilities however security is one of the major drawbacks that preventing large organizations to enter into cloud computing environment. This work surveyed on several storage techniques and this advantage and its drawbacks.


Author(s):  
R.Santha Maria Rani ◽  
Dr.Lata Ragha

Cloud computing provides elastic computing and storage resource to users. Because of the characteristic the data is not under user’s control, data security in cloud computing is becoming one of the most concerns in using cloud computing resources. To improve data reliability and availability, Public data auditing schemes is used to verify the outsourced data storage without retrieving the whole data. However, users may not fully trust the cloud service providers (CSPs) because sometimes they might be dishonest. Therefore, to maintain the integrity of cloud data, many auditing schemes have been proposed. In this paper, analysis of various existing auditing schemes with their consequences is discussed.  Keywords: — Third Party Auditor (TPA), Cloud Service Provider (CSP), Merkle-Hash Tree (MHT), Provable data Possession (PDP), Dynamic Hash Table (DHT).


T-Comm ◽  
2020 ◽  
Vol 14 (12) ◽  
pp. 72-79
Author(s):  
Aleksandr O. Volkov ◽  

For cloud service providers, one of the most relevant tasks is to maintain the required quality of service (QoS) at an acceptable level for customers. This condition complicates the work of providers, since now they need to not only manage their resources, but also provide the expected level of QoS for customers. All these factors require an accurate and well-adapted mechanism for analyzing the performance of the service provided. For the reasons stated above, the development of a model and algorithms for estimation the required resource is an urgent task that plays a significant role in cloud systems performance evaluation. In cloud systems, there is a serious variance in the requirements for the provided resource, as well as there is a need to quickly process incoming requests and maintain the proper level of quality of service – all of these factors cause difficulties for cloud providers. The proposed analytical model for processing requests for a cloud computing system in the Processor Sharing (PS) service mode allows us to solve emerging problems. In this work, the flow of service requests is described by the Poisson model, which is a special case of the Engset model. The proposed model and the results of its analysis can be used to evaluate the main characteristics of the performance of cloud systems.


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