Cloud Computing Taxonomies: Benefits and Challenges

2017 ◽  
Vol DC CPS 2017 (01) ◽  
pp. 11-21
Author(s):  
Okoye J. A. ◽  
Mbachu C. B
Keyword(s):  
Cloud Computing ◽  
Web Application ◽  
Cost Optimization ◽  
Service Level ◽  
Cloud Data ◽  
On Demand ◽  
Cloud Data Centers ◽  
Cloud Elasticity ◽  
Auto Scaling ◽  
Cloud Users

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.

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
Keyword(s):  
Cloud Computing ◽  
Web Application ◽  
Web Applications ◽  
Service Providers ◽  
Cloud Service ◽  
Cloud Data ◽  
Cloud Data Centers ◽  
The Cost ◽  
Auto Scaling

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.

Cloud Load Balancing Algorithms: A Comparative Assessment

2019 ◽  
Vol 16 (9) ◽  
pp. 3989-3994
Author(s):  
Jaspreet Singh ◽  
Deepali Gupta ◽  
Neha Sharma
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Data Centers ◽  
Research Area ◽  
Comparative Assessment ◽  
Cloud Services ◽  
Cloud Data ◽  
Cloud Data Centers ◽  
Cloud Users

Nowadays, Cloud computing is developing quickly and customers are requesting more administrations and superior outcomes. In the cloud domain, load balancing has turned into an extremely intriguing and crucial research area. Numbers of algorithms were recommended to give proficient mechanism for distributing the cloud user’s requests for accessing pool cloud resources. Also load balancing in cloud should provide notable functional benefits to cloud users and at the same time should prove out to be eminent for cloud services providers. In this paper, the pre-existing load balancing techniques are explored. The paper intends to provide landscape for classification of distinct load balancing algorithms based upon the several parameters and also address performance assessment bound to various load balancing algorithms. The comparative assessment of various load balancing algorithms will helps in proposing a competent load balancing technique for intensify the performance of cloud data centers.

Design and Implement of Auto-Scaling System Based on Eucalyptus Cloud-Computing Platform

2012 ◽  
Vol 546-547 ◽  
pp. 1433-1438 ◽  
Author(s):  
Wei Wei Wang ◽  
Jing Li ◽  
Yuan Yuan Guo ◽  
Hu Song ◽  
Xin Chun Liu
Keyword(s):  
Cloud Computing ◽  
Service Level ◽  
Network Resources ◽  
Computing Platform ◽  
On Demand ◽  
Computing Services ◽  
Cloud Computing Services ◽  
Auto Scaling ◽  
Demand Service

On-demand service is one of the most important characteristics of cloud computing. Cloud-computing services should dynamically and timely deliver computing resources, storage resources and network resources etc. to consumers according to user needs, and service level should be able to meet quality of service. Users only need to pay on demand; otherwise they have to maintain sufficient resources just in order to meet peak requirements, which can be costly. In this paper, we present the design and implementation of Auto-Scaling system and illustrate its system architecture, components and scaling algorithm. Finally, we test the system and the results show that it can be capable of handling sudden load surges, delivering resources to users on demand, saving cost for users and improving resource utilization.

Resource and Energy Efficient Virtual Machine Migration in Cloud Data Centers

2017 ◽  
pp. 210-238
Author(s):  
Subrat Kumar Dhal ◽  
Harshit Verma ◽  
Sourav Kanti Addya
Keyword(s):  
Cloud Computing ◽  
Data Centers ◽  
Cloud Model ◽  
Service Level Agreement ◽  
Optimal Solution ◽  
Service Level ◽  
Virtual Machine Migration ◽  
Cloud Data ◽  
Cloud Data Centers ◽  
Selection Algorithms

Cloud computing service has been on the rise over the past few decades, which has led to an increase in the number of data centers, thus consuming more amount of energy for their operation. Moreover, the energy consumption in the cloud is proportional to the resource utilization. Thus consolidation schemes for the cloud model need to be devised to minimize energy by decreasing the operating costs. The consolidation problem is NP-complete, which requires heuristic techniques to get a sub-optimal solution. The authors have proposed a new consolidation scheme for the virtual machines (VMs) by improving the host overload detection phase. The resulting scheme is effective in reducing the energy and the level of Service Level Agreement (SLA) violations both, to a considerable extent. For testing the performance of implementation, a simulation environment is needed that can provide an environment of the actual cloud computing components. The authors have used CloudSim 3.0.3 simulation toolkit that allows testing and analyzing Allocation and Selection algorithms.

scholarly journals Multilevel classification of security threats in cloud computing

2017 ◽  
Vol 7 (1.5) ◽  
pp. 253
Author(s):  
N. Srinivasu ◽  
O. Sree Priyanka ◽  
M. Prudhvi ◽  
G. Meghana
Keyword(s):  
Cloud Computing ◽  
Web Application ◽  
Service Level Agreement ◽  
Service Level ◽  
Security Threats ◽  
Security Threat ◽  
Security Issues ◽  
Network Applications ◽  
Storage Network ◽  
Multilevel Classification

Cloud Security was provided for the services such as storage, network, applications and software through internet. The Security was given at each layer (Saas, Paas, and Iaas), in each layer, there are some security threats which became the major problem in cloud computing. In Saas, the security issues are mainly present in Web Application services and this issue can be overcome by web application scanners and service level agreement(SLA). In Paas, the major problem is Data Transmission. During transmission of data, some data may be lost or modified. The PaaS environment accomplishes proficiency to some extent through duplication of information. The duplication of information makes high accessibility of information for engineers and clients. However, data is never fully deleted instead the pointers to the data are deleted. In order to overcome this problem the techniques that used are encryption[12], data backup. In Iaas the security threat that occurs in is virtualization and the techniques that are used to overcome the threats are Dynamic Security Provisioning(DSC), operational security procedure, for which Cloud Software is available in the market, for e.g. Eucalyptus, Nimbus 6.

Multidimensional Resource Scheduling in Cloud Data Centers

2014 ◽  
Vol 1008-1009 ◽  
pp. 1513-1516
Author(s):  
Hai Na Song ◽  
Xiao Qing Zhang ◽  
Zhong Tang He
Keyword(s):  
Cloud Computing ◽  
Data Centers ◽  
Bin Packing ◽  
Virtual Machines ◽  
Three Dimensional ◽  
Resource Scheduling ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Cloud Data ◽  
Cloud Data Centers

Cloud computing environment is regarded as a kind of multi-tenant computing mode. With virtulization as a support technology, cloud computing realizes the integration of multiple workloads in one server through the package and seperation of virtual machines. Aiming at the contradiction between the heterogeneous applications and uniform shared resource pool, using the idea of bin packing, the multidimensional resource scheduling problem is analyzed in this paper. We carry out some example analysis in one-dimensional resource scheduling, two-dimensional resource schduling and three-dimensional resource scheduling. The results shows that the resource utilization of cloud data centers will be improved greatly when the resource sheduling is conducted after reorganizing rationally the heterogeneous demands.

Modeling And Analyzing Cloud Auto-Scaling Mechanism Using Stochastic Well-Formed Coloured Nets

2021 ◽  
Author(s):  
Mohamed M. Ould Deye ◽  
Mamadou Thiongane ◽  
Mbaye Sene
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Service Level ◽  
The State ◽  
Service Level Agreements ◽  
Auto Scaling

Auto-scaling is one of the most important features in Cloud computing. This feature promises cloud computing customers the ability to best adapt the capacity of their systems to the load they are facing while maintaining the Quality of Service (QoS). This adaptation will be done automatically by increasing or decreasing the amount of resources being leveraged against the workload’s resource demands. There are two types and several techniques of auto-scaling proposed in the literature. However, regardless the type or technique of auto-scaling used, over-provisioning or under-provisioning problem is often observed. In this paper, we model the auto-scaling mechanism with the Stochastic Well-formed coloured Nets (SWN). The simulation of the SWN model allows us to find the state of the system (the number of requests to be dispatched, the idle times of the started resources) from which the auto-scaling mechanism must be operated in order to minimize the amount of used resources without violating the service-level agreements (SLA).

Slicing, Tokenization, and Encryption Based Combinational Approach to Protect Data-at-Rest in Cloud Using TF-Sec Model

2020 ◽  
Vol 17 (12) ◽  
pp. 5296-5306
Author(s):  
N. Keerthana ◽  
Viji Vinod ◽  
Sudhakar Sengan
Keyword(s):  
Cloud Service ◽  
Service Level ◽  
Cloud Services ◽  
Erasure Coding ◽  
Cloud Data ◽  
Data Usage ◽  
Dispersion Technique ◽  
Definition Of ◽  
The Given ◽  
Cloud Users

Data in the Cloud, which applies to data as a cloud service provider (CSP), transmits stores, or manages it. The company will enforce the same definition of data usage while the data is resident within the enterprise and thus extend the required cryptographic security criteria to data collected, exchanged, or handled by CSP. The CSP Service Level Agreements cannot override the cryptographic access measures. When the data is transferred securely to CSP, it can be securely collected, distributed, and interpreted. Data at the rest position applies to data as it is processed internally in organized and in the unstructured ways like databases and file cabinets. The Data at the Rest example includes the use of cryptography for preserving the integrity of valuable data when processed. For cloud services, computing takes multiple forms from recording units, repositories, and many unstructured items. This paper presents a secure model for Data at rest. The TF-Sec model suggested is planned for use with Slicing, Tokenization, and Encryption. The model encrypts the given cloud data using AES 256 encryption, and then the encrypted block is sliced into the chunks of data fragments using HD-Slicer. Then it applies tokenization algorithm TKNZ to each chunk of data, applies erasure coding technique to tokens, applies the data dispersion technique to scramble encrypted data fragments, and allocates to storage nodes of the multiple CSP. In taking the above steps, this study aims to resolve the cloud security problems found and to guarantee the confidentiality of their data to cloud users due to encryption of data fragments would be of little benefit to a CSP.

A Comprehensive Survey on Techniques Based on TPM for Ensuring the Confidentiality in Cloud Data Centers

2019 ◽  
pp. 446-458
Author(s):  
Arun Fera M. ◽  
M. Saravanapriya ◽  
J. John Shiny
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Research Work ◽  
Computing Systems ◽  
Trusted Platform Module ◽  
Cloud Data ◽  
Secure Storage ◽  
Comprehensive Survey ◽  
Cloud Data Centers ◽  
Trusted Platform

Cloud computing is one of the most vital technology which becomes part and parcel of corporate life. It is considered to be one of the most emerging technology which serves for various applications. Generally these Cloud computing systems provide a various data storage services which highly reduces the complexity of users. we mainly focus on addressing in providing confidentiality to users' data. We are proposing one mechanism for addressing this issue. Since software level security has vulnerabilities in addressing the solution to our problem we are dealing with providing hardware level of security. We are focusing on Trusted Platform Module (TPM) which is a chip in computer that is used for secure storage that is mainly used to deal with authentication problem. TPM which when used provides a trustworthy environment to the users. A detailed survey on various existing TPM related security and its implementations is carried out in our research work.

Resource Allocation Policies in Cloud Computing Environment

2017 ◽  
pp. 115-132 ◽  
Author(s):  
Suvendu Chandan Nayak ◽  
Sasmita Parida ◽  
Chitaranjan Tripathy ◽  
Prasant Kumar Pattnaik
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Resource Utilization ◽  
Service Level Agreement ◽  
Service Level ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
On Demand ◽  
Different Types ◽  
Cloud Datacenter

The basic concept of cloud computing is based on “Pay per Use”. The user can use the remote resources on demand for computing on payment basis. The on-demand resources of the user are provided according to a Service Level Agreement (SLA). In real time, the tasks are associated with a time constraint for which they are called deadline based tasks. The huge number of deadline based task coming to a cloud datacenter should be scheduled. The scheduling of this task with an efficient algorithm provides better resource utilization without violating SLA. In this chapter, we discussed the backfilling algorithm and its different types. Moreover, the backfilling algorithm was proposed for scheduling tasks in parallel. Whenever the application environment is changed the performance of the backfilling algorithm is changed. The chapter aims implementation of different types of backfilling algorithms. Finally, the reader can be able to get some idea about the different backfilling scheduling algorithms that are used for scheduling deadline based task in cloud computing environment at the end.

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