Trusted cloud broker for estimating the reputation of cloud providers in federated cloud environment

2021 ◽  
Author(s):  
C. Muralidharan ◽  
R. Anitha
Keyword(s):  
Cloud Environment ◽  
Cloud Broker ◽  
Cloud Providers

scholarly journals CAM-D: A Description Method for Multi-Cloud Marketplace Application

2020 ◽  
Vol 2020 (2) ◽  
pp. 51-61
Author(s):  
Huynh Hoang Long
Keyword(s):  
Complex System ◽  
Individual Component ◽  
Software Components ◽  
Cloud Environment ◽  
Cloud Application ◽  
Cloud Providers ◽  
Multi Cloud

Multi-cloud Marketplace facilitates to create adiverse ecosystem for cloud software and cloud resourceservices provided by many stakeholders. To leverage theadvantage of multi-cloud environment, cloud application couldbe a composition of software components which are able tobe distributed across various cloud providers. So the cloudapplication is therefore a complex system. Consequently, animportant key problem remained in research is to definemulti-cloud application in a particular form and to constructhis description. In this paper, we particularly focus ondeveloping a description method that can be taken to tacklethe lack of description for multi-cloud application by designingdescription templates for CAM which was developed in[1][2][3], called CAM-D. A completed application descriptioncan be synthesized from individual component descriptions.Our experimentation is expressed through the transformationof CAM-D template to TOSCA specification illustrated by casestudy. In addition, we also develop an flattening algorithm toassist in mapping to TOSCA.

scholarly journals BSS: a brokering model for service selection using integrated weighting approach in cloud environment

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Sameer Singh Chauhan ◽  
Emmanuel S. Pilli ◽  
R. C. Joshi
Keyword(s):  
Service Management ◽  
Service Selection ◽  
Cloud Service ◽  
Cloud Services ◽  
Total Weight ◽  
Cost Models ◽  
Reversal Problem ◽  
Cloud Broker ◽  
Subjective Weight ◽  
Cloud Providers

AbstractCloud providers shares their resources and services through collaboration in order to increase resource utilization, profit and quality of services. The offered services with different access patterns, similar characteristics, varied performance levels and cost models create a heterogeneous service environment. It becomes a challenging task for users to decide a suitable service as per their application requirements. Cloud broker, an inter-mediator is required in service management to help both cloud providers and users. Cloud broker has to store all the information related to services and feedback of users on those services in order to provide the best services to end-users. Brokering model for service selection (BSS) has been proposed which employs integrated weighting approach in cloud service selection. Subjective and objective weights of QoS attributes are combined to compute integrated total weight. Subjective weight is obtained from users’ feedback on QoS attributes of a cloud service while objective weight is computed from benchmark tested data of cloud services. Users’ feedback and preferences given to QoS parameters are employed in subjective weight computation. Objective weight is computed using Shannon’s Entropy method. Total weight is obtained by combining subjective and objective weights. BSS method is employed to rank cloud services. Simulation with a case study on real dataset has been done to validate the effectiveness of BSS. The obtained results demonstrate the consistency of model for handling rank reversal problem and provides better execution time than other state-of-the art solutions.

Model-Based Application Deployment on Cloud Computing

2019 ◽  
Vol 10 (2) ◽  
pp. 110-127 ◽  
Author(s):  
Aouat Asmaa ◽  
Deba El Abbassia ◽  
Benyamina Abou EL Hassan ◽  
Benhamamouch Djilali
Keyword(s):  
Cloud Computing ◽  
The Internet ◽  
Cloud Environment ◽  
Model Driven Engineering ◽  
Model Driven ◽  
On Demand ◽  
Model Based ◽  
Cloud Providers ◽  
Application Deployment ◽  
Scientific Challenge

Cloud Computing refers to a set of technologies and systems that provide various types of resources (computing, storage, software, etc.) on demand, through the Internet or Intranet. Thanks to these advantages many Cloud providers are available and is increasing. These cloud providers offer different PaaS platforms that must each be configured in its own appropriate way to deploy applications in the cloud. Cloud Computing is based on heterogeneity principles, which allows many configurations and sizing choices. This implies that the developer must master all deployment methods in order to benefit from all suppliers. The development and deployment of applications in the Cloud offers a new scientific challenge in terms of expression and taking into account variability. The purpose of the author's work is to propose a deployment method and implement it to automate the process of deploying applications in a cloud environment based on model-driven engineering, to configure and provision applications to be deployed in the cloud.

scholarly journals Managing the CERN Batch System with Kubernetes

2020 ◽  
Vol 245 ◽  
pp. 07048
Author(s):  
Luis Fernandez Alvarez ◽  
Olga Datskova ◽  
Ben Jones ◽  
Gavin McCance
Keyword(s):  
Open Source ◽  
Batch Service ◽  
Resource Usage ◽  
Cloud Environment ◽  
Operational Model ◽  
Batch System ◽  
Wide Range ◽  
Cloud Providers ◽  
The Impact ◽  
Usage Efficiency

The CERN Batch Service faces many challenges in order to get ready for the computing demands of future LHC runs. These challenges require that we look at all potential resources, assessing how efficiently we use them and that we explore different alternatives to exploit opportunistic resources in our infrastructure as well as outside of the CERN computing centre. Several projects, like BEER, Helix Nebula Science Cloud and the new OCRE project, have proven our ability to run batch workloads on a wide range of non-traditional resources. However, the challenge is not only to obtain the raw compute resources needed but how to define an operational model that is cost and time efficient, scalable and flexible enough to adapt to a heterogeneous infrastructure. In order to tackle both the provisioning and operational challenges it was decided to use Kubernetes. By using Kubernetes we benefit from a de-facto standard in containerised environments, available in nearly all cloud providers and surrounded by a vibrant ecosystem of open-source projects. Leveraging Kubernetes’ built-in functionality, and other open-source tools such as Helm, Terraform and GitLab CI, we have deployed a first cluster prototype which we discuss in detail. The effort has simplified many of the existing operational procedures we currently have, but has also made us rethink established procedures and assumptions that were only valid in a VM-based cloud environment. This contribution presents how we have adopted Kubernetes into the CERN Batch Service, the impact its adoption has in daily operations, a comparison on resource usage efficiency and the experience so far evolving our infrastructure towards this model.

Sniffers Over Cloud Environment

2018 ◽  
pp. 122-149
Author(s):  
Thangavel M ◽  
Narmadha N ◽  
Deepika B
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Storage Space ◽  
Cloud Environment ◽  
Multiple Users ◽  
Cloud Providers ◽  
User Data

Cloud computing is a technology for complex computing, it eliminates the need to have computing hardware, storage space and software. Multi tenancy is considered as important element in which same resources will be shared by multiple users. The users are named as tenants in the cloud environment. The tenants may run their applications in their own cloud environment which will have some vulnerability. These vulnerabilities will cause some attacks to the tenant virtual machine. In general, the cloud providers will not provide that much security to the cloud tenants. So, it is the duty of the tenant to make some countermeasures to avoid these attacks. In a cloud environment, there may be multiple tenants in that there is a possible of malicious tenant also present in the cloud environment. The attacker will do sniffing attack by monitoring all the user traffic. In the cloud, it is a fact that all the user data will resides in same hardware so the attacker monitor the activities of all the user and observes the type of traffic.

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