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.

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).

Service Quality and Perceived Value of Cloud Computing-Based Service Encounters

2019 ◽  
pp. 234-247
Author(s):  
Eges Egedigwe
Keyword(s):  
Cloud Computing ◽  
Community Colleges ◽  
Service Quality ◽  
Competitive Environment ◽  
Service Encounters ◽  
Institutional Level ◽  
Computing Services ◽  
Key Stakeholders ◽  
Cloud Computing Services

Cloud computing-based technology is becoming increasingly popular as a way to deliver quality education to community colleges, universities, and other organizations. At the same time, compared with other industries, colleges have been slow on implementing and sustaining cloud computing services on an institutional level because of budget constraints facing many large community colleges, in addition to other obstacles. Faced with this challenge, key stakeholders are increasingly realizing the need to focus on service quality as a measure to improve their competitive position in today's highly competitive environment. Considering the amount of study done with cloud computing in education, very little has been done in examining the needs and the satisfactions of the instructor customer. The purpose of this chapter is to examine the expectations and perceptions of instructors' usage of cloud computing based technology on overall quality of service (QoS) in their respective institutions of higher education.

Cloud-Based Platforms and Infrastructures

2017 ◽  
pp. 47-90
Author(s):  
Marcus Tanque
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Cloud Service ◽  
Resource Provisioning ◽  
Virtual Networks ◽  
Network Resources ◽  
Computing Services ◽  
Service Models ◽  
Cloud Computing Services ◽  
Shared Network

Cloud computing consists of three fundamental service models: infrastructure-as-a-service, platform-as-a service and software-as-a-service. The technology “cloud computing” comprises four deployment models: public cloud, private cloud, hybrid cloud and community cloud. This chapter describes the six cloud service and deployment models, the association each of these services and models have with physical/virtual networks. Cloud service models are designed to power storage platforms, infrastructure solutions, provisioning and virtualization. Cloud computing services are developed to support shared network resources, provisioned between physical and virtual networks. These solutions are offered to organizations and consumers as utilities, to support dynamic, static, network and database provisioning processes. Vendors offer these resources to support day-to-day resource provisioning amid physical and virtual machines.

Optimal Management of Cloud Centers with Different Arrival Modes for Cloud Computing Environment

2012 ◽  
Vol 2 (3) ◽  
pp. 86-97
Author(s):  
Veena Goswami ◽  
Sudhansu Shekhar Patra ◽  
G. B. Mund
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Service Level Agreement ◽  
Service Level ◽  
Finite Buffer ◽  
Web Browser ◽  
Computing Paradigm ◽  
Computing Services ◽  
Multi Server

Cloud computing is a new computing paradigm in which information and computing services can be accessed from a Web browser by clients. Understanding of the characteristics of computer service performance has become critical for service applications in cloud computing. For the commercial success of this new computing paradigm, the ability to deliver guaranteed Quality of Services (QoS) is crucial. Based on the Service level agreement, the requests are processed in the cloud centers in different modes. This paper analyzes a finite-buffer multi-server queuing system where client requests have two arrival modes. It is assumed that each arrival mode is serviced by one or more Virtual machines, and both the modes have equal probabilities of receiving service. Various performance measures are obtained and optimal cost policy is presented with numerical results. The genetic algorithm is employed to search the optimal values of various parameters for the system.

SLA (Service Level Agreement) Driven Orchestration Based New Methodology for Cloud Computing Services

2013 ◽  
Vol 660 ◽  
pp. 196-201 ◽  
Author(s):  
Muhammad Irfan ◽  
Zhu Hong ◽  
Nueraimaiti Aimaier ◽  
Zhu Guo Li
Keyword(s):  
Cloud Computing ◽  
Computer Science ◽  
Service Providers ◽  
Service Level Agreement ◽  
Cloud Service ◽  
Service Level ◽  
Cloud Services ◽  
Computing Services ◽  
Cloud Service Providers ◽  
Cloud Computing Services

Cloud Computing is not a revolution; it’s an evolution of computer science and technology emerging by leaps and bounds, in order to merge all computer science tools and technologies. Cloud Computing technology is hottest to do research and explore new horizons of next generations of Computer Science. There are number of cloud services providers (Amazon EC2), Rackspace Cloud, Terremark and Google Compute Engine) but still enterprises and common users have a number of concerns over cloud service providers. Still there is lot of weakness, challenges and issues are barrier for cloud service providers in order to provide cloud services according to SLA (Service Level agreement). Especially, service provisioning according to SLAs is core objective of each cloud service provider with maximum performance as per SLA. We have identified those challenges issues, as well as proposed new methodology as “SLA (Service Level Agreement) Driven Orchestration Based New Methodology for Cloud Computing Services”. Currently, cloud service providers are using “orchestrations” fully or partially to automate service provisioning but we are trying to integrate and drive orchestration flows from SLAs. It would be new approach to provision cloud service and deliver cloud service as per SLA, satisfying QoS standards.

scholarly journals An Analytical Framework of a Deployment Strategy for Cloud Computing Services: A Case Study of Academic Websites

2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
Chi-Hua Chen ◽  
Hui-Fei Lin ◽  
Hsu-Chia Chang ◽  
Ping-Hsien Ho ◽  
Chi-Chun Lo
Keyword(s):  
Cloud Computing ◽  
Analytical Framework ◽  
Service Level ◽  
Network Behavior ◽  
Analytic Framework ◽  
Deployment Strategy ◽  
Computing Services ◽  
Cloud Computing Services ◽  
Hierarchy Process

Cloud computing has become a popular topic for exploration in both academic and industrial research in recent years. In this paper, network behavior is analyzed to assess and compare the costs and risks associated with traditional local servers versus those associated with cloud computing to determine the appropriate deployment strategy. An analytic framework of a deployment strategy that involves two mathematical models and the analytical hierarchy process is proposed to analyze the costs and service level agreements of services involving using traditional local servers and platform as service platforms in the cloud. Two websites are used as test sites to analyze the costs and risks of deploying services inGoogle App Engine(GAE) (1) the website ofInformation and Finance of Management(IFM) at theNational Chiao Tung University(NCTU) and (2) the NCTU website. If the examined websites were deployed in GAE, NCTU would save over 83.34% of the costs associated with using a traditional local server with low risk. Therefore, both the IFM and NCTU websites can be served appropriately in the cloud. Based on this strategy, a suggestion is proposed for managers and professionals.

An Energy-efficient Virtual Machine Placement Algorithm based Service Level Agreement in Cloud Computing Environments

2017 ◽  
Vol 2 (6) ◽  
pp. 1-6
Author(s):  
Arash Mazidi ◽  
Elham Damghanijazi ◽  
Sajad Tofighy
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Service Level Agreement ◽  
Service Level ◽  
Model Management ◽  
Time Data ◽  
Computing Services ◽  
Cloud Computing Services ◽  
Placement Algorithm ◽  
Leading Enterprises

The cloud computing has given services to the users throughout the world during recent years. The cloud computing services have been founded according to ‘As-Pay-You-Go’ model and some leading enterprises give these services. The giving these cloud-computing services has been developed every day and these requirements necessitate for more infrastructures and Internet providers (IPs). The nodes of data centers consume a lot of energy in cloud structure and disseminate noticeable amount of carbon dioxide into the environment. We define a framework and structure for cloud environment of efficient energy in the present paper. We examine the present problems and challenges based on this structure and then present and model management algorithms and source allocation in cloud computing environment in order to manage energy in addition to considering Service Level Agreement. The proposed algorithm has been implemented by cloudsim simulator where the obtained results from simulation of real-time data indicate that the proposed method is superior to previous techniques in terms of energy consumption and observance of Service Level Agreement. Similarly, number of live migration of virtual machines and quantity of transferred data has been improved.

Cloud-Based Platforms and Infrastructures

2019 ◽  
pp. 84-126
Author(s):  
Marcus Tanque
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Cloud Service ◽  
Resource Provisioning ◽  
Virtual Networks ◽  
Network Resources ◽  
Computing Services ◽  
Service Models ◽  
Cloud Computing Services ◽  
Shared Network

Cloud computing consists of three fundamental service models: infrastructure-as-a-service, platform-as-a service and software-as-a-service. The technology “cloud computing” comprises four deployment models: public cloud, private cloud, hybrid cloud and community cloud. This chapter describes the six cloud service and deployment models, the association each of these services and models have with physical/virtual networks. Cloud service models are designed to power storage platforms, infrastructure solutions, provisioning and virtualization. Cloud computing services are developed to support shared network resources, provisioned between physical and virtual networks. These solutions are offered to organizations and consumers as utilities, to support dynamic, static, network and database provisioning processes. Vendors offer these resources to support day-to-day resource provisioning amid physical and virtual machines.

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