Cloud computing is the current most trendy and social technology that has been launched on the network world which can also be called as a reincarnation or evolution of Grid computing, so the Clouds are considered as a new generation of Grid computing. These Clouds consist of data centres which are owned by individual institute, organisations or companies. The homogeneity within each data centre in the infrastructure is the main feature for the cloud computing compared to grid computing. Cloud Computing has become another most used word on internet after Web 2.0. There are many definitions for Cloud computing and there seems to be no consensus on what a Cloud is. Cloud Computing is not a completely new concept, it has intricate connection to the relatively new but thirteen year established Grid Computing paradigm and other relevant technologies such as utility computing, cluster computing, and distributed systems when we go through the structure and working of a Cloud.
Table of Contents
I. INTRODUCTION
II. CLOUD, GRID AND DISTRIBUTED SYSTEM
III. CLOUD DEFINITION
IV. CLOUD COMPUTING MODEL
IV.1 DEPLOYMENT MODEL
IV.2 SERVICE MODEL
V. CLOUD ARCHITECTURE
VI. GRID COMPUTING
VII. GRID ARCHITECTURE
VIII. COMPARISON
IX. MAJOR DIFFERENCES BETWEEN GRID AND CLOUD
X. CONCLUSION
Objectives and Topics
The primary objective of this paper is to provide a comprehensive comparative analysis between Cloud computing and Grid computing. The research explores the technological evolution of these paradigms, identifies their functional similarities and differences, and evaluates how they are assembled and utilized in modern distributed systems.
- Architectural distinctions between Cloud and Grid infrastructures.
- Evaluation of deployment and service models (IaaS, PaaS, SaaS).
- Business models and resource management strategies.
- Performance and scalability challenges in large-scale environments.
Excerpt from the Book
IX. MAJOR DIFFERENCES BETWEEN GRID AND CLOUD
Business Models. While in Grid business models are usually based on bilateral agreements between academic institutions, provision of resource in Clouds requires more differentiated business models as discussed next. Currently, we observe several types of business models ranging from resource providers who only provide computing resources (e. g., Amazon, Tsunamic Technologies), over SaaS providers who sell their own resources together with their own software services (e. g., GoogleApps, Salesforce.com) to companies that attempt to run a mixed approach, i. e., they allow users to create their own services but at the same time offer their own services (Sun N1 Grid, Microsoft Azure).
Resource Management. Resource management represents another major difference between Grids and Clouds. While Grids rely on batch systems, utilization of virtualization technologies represents the resource management solution for the Clouds.
Resource Provision Models. As already discussed in previous sections Grid resource provisioning models are based on virtual organisations where the relationships are established offline. In Clouds usage of SLAs, compliance, and trust management is essential.
Resource Availability. In Grids resource sharing relies on the best effort manner, sometimes resources are not available and sometimes there are plenty of resources which are idle. Clouds rely on massive elasticity in Clouds. Challenging issues in Clouds are to find the balance between wasting resources due to the virtualization overhead and standby modes of devices on the one hand, and pooling of resources to facilitate efficient consumption of resources and reducing energy consumption on the other.
Summary of Chapters
I. INTRODUCTION: Provides an overview of Cloud computing as an evolution of Grid computing and highlights the fundamental differences in their service-oriented nature.
II. CLOUD, GRID AND DISTRIBUTED SYSTEM: Discusses the overlapping definitions between various computing paradigms and explores the backbone infrastructure of Cloud computing.
III. CLOUD DEFINITION: Analyzes the lack of a standardized definition for Cloud computing by referencing various industry perspectives and definitions from 2008.
IV. CLOUD COMPUTING MODEL: Breaks down the specific deployment models (Public, Private, Community, Hybrid) and service models (IaaS, PaaS, SaaS).
V. CLOUD ARCHITECTURE: Examines the composition of Cloud architectures and addresses the difficulties associated with large-scale data processing.
VI. GRID COMPUTING: Recaps the definition of Grid computing and uses Google search trends to show the historical shift in popularity between computing paradigms.
VII. GRID ARCHITECTURE: Details the Amadeus environment and its use of QoS-aware Grid workflows for high-performance computing applications.
VIII. COMPARISON: Compares Grid and Cloud computing across various parameters and explains the scale-based differences in their client-server models.
IX. MAJOR DIFFERENCES BETWEEN GRID AND CLOUD: Summarizes key distinctions in business models, resource management, provision models, and resource availability.
X. CONCLUSION: Finalizes the analysis by suggesting that Cloud computing will realize the original dreams of Grid computing while highlighting the need for further research.
Keywords
Cloud Computing, Grid Computing, Distributed Systems, Virtualization, IaaS, PaaS, SaaS, Resource Management, Scalability, QoS, Business Models, Data Centers, High Performance Computing, Distributed Infrastructure.
Frequently Asked Questions
What is the core focus of this research paper?
The paper provides a comparative analysis between Cloud computing and Grid computing to understand their technological relationship, differences in deployment, and their respective architectural frameworks.
What are the primary themes discussed in the work?
The work explores system architectures, service models, business strategies, and resource management techniques used in both Grid and Cloud environments.
What is the main objective of the comparative analysis?
The goal is to differentiate these two often-confused paradigms, helping the tech community understand how they can evolve and accelerate the transition from prototypes to production-ready systems.
Which scientific methodology is applied?
The paper employs a comparative study approach, evaluating existing definitions, architectural components, and empirical trends like Google search popularity to contrast the two models.
What topics are covered in the main section?
The main sections cover Cloud models, service models, the architectural components of both Grids and Clouds, and a detailed parameter-based comparison table.
Which keywords best characterize this publication?
Keywords include Cloud Computing, Grid Computing, Scalability, Resource Management, Virtualization, and Distributed Infrastructure.
How does the author define the relationship between Grid and Cloud?
The author argues that Cloud computing has evolved from Grid computing, utilizing it as a backbone but shifting the focus toward economy-based services and mass scalability.
What role does the Amadeus environment play in this study?
Amadeus serves as a practical example of a Grid architecture utilized for managing execution workflows in specialized applications like medical surgery preparations.
- Quote paper
- Er. Bijoy Boban (Author), 2013, Comparative analysis between Grid and Cloud computing, Munich, GRIN Verlag, https://www.grin.com/document/212932
