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
Objectives and Key Themes
This paper aims to provide a comparative analysis of cloud computing and grid computing, highlighting their similarities and differences. The analysis explores the evolution of cloud computing from grid computing and examines the distinct characteristics that define each paradigm.
- Comparison of Cloud and Grid Computing Architectures
- Analysis of the different service and deployment models within cloud computing
- Examination of the key differences in business models, resource management, and resource availability between cloud and grid computing.
- Exploration of the historical context and evolving popularity of these technologies.
- Discussion of the relationship between cloud computing and other relevant technologies such as utility computing and distributed systems.
Chapter Summaries
I. INTRODUCTION: This introductory chapter establishes the context for comparing cloud and grid computing. It highlights cloud computing's emergence as a trendsetting technology, emphasizing its evolution from grid computing. The chapter differentiates cloud computing from other areas by outlining its key characteristics: service-oriented, loosely coupled, fault-tolerant, business-model driven, and easily accessible. It then briefly introduces grid computing as the cooperation of multiple processors across machines to boost computational power, noting its longer history and continued use.
II. CLOUD, GRID AND DISTRIBUTED SYSTEM: This chapter delves into the overlapping nature of cloud computing with existing technologies like grid computing, utility computing, and distributed systems. It argues that cloud computing evolved from grid computing, shifting focus from resource delivery to a more service-oriented, economy-based model. Utility computing is presented as a business model, not a computing paradigm, implemented using various infrastructures including grids. The chapter uses a figure to illustrate the relationships between clouds and other relevant domains, placing cloud computing as the large-scale component within the service-oriented applications of Web 2.0.
III. CLOUD DEFINITION: This chapter acknowledges the lack of a universally agreed-upon definition for cloud computing, due to its diverse contributions and lack of centralized ownership. It presents several definitions from various authors and references, highlighting the inconsistencies and ongoing evolution of understanding concerning this technology. The chapter also mentions Gartner's definition of cloud computing as massively scalable IT capabilities provided as a service.
IV. CLOUD COMPUTING MODEL: This chapter explores the deployment and service models of cloud computing. The deployment models—public, private, community, and hybrid—are explained in detail, emphasizing their respective advantages, concerns (particularly security), and applications. The chapter also introduces the increasingly popular concept of Green Cloud Computing, aimed at reducing energy consumption through server consolidation and virtualization. The service models—Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), and Software-as-a-Service (SaaS)—are described, outlining their functionalities and applications, along with their advantages and limitations.
V. CLOUD ARCHITECTURE: This chapter focuses on the architecture of cloud computing, highlighting its ability to aggregate heterogeneous components like grids, clusters, and supercomputers to serve millions of users. It discusses how cloud architecture addresses the challenges of large-scale data processing, such as scaling machines on demand, distributing jobs, and managing resource allocation. The chapter concludes by showcasing some common applications effectively using cloud architecture, such as processing pipelines, batch processing systems, and websites.
VI. GRID COMPUTING: This chapter defines grid computing based on Ian Foster’s definition, highlighting its focus on coordinating resources without centralized control using standard protocols. It contrasts this with the cloud computing paradigm, which relies on next-generation data centers using virtualization. The chapter analyzes the changing popularity of various computing paradigms over time using data from Google Trends, illustrating the shift from cluster computing, to grid computing, and finally to the increasing dominance of cloud computing.
VII GRID ARCHITECTURE: This chapter presents the Amadeus environment as an example of grid architecture used for managing the execution of grid workflows. It details the components of Amadeus, including visualization and specification, planning and execution (using a QoS-aware workflow engine), and grid resources. The chapter also explains the workflow modelling process and the use of QoS constraints and services.
VIII. COMPARISON: This chapter provides a comprehensive comparison of cloud and grid computing, differentiating them across multiple aspects. A table is referenced to present a clear summary of the key differences. The chapter also uses Google Trends data to further illustrate the comparative popularity and growth of cloud computing against grid computing, dedicated servers, and virtualization. It summarizes the similarities, highlighting how the cloud can be seen as a scaled and democratized version of the grid.
IX. MAJOR DIFFERENCES BETWEEN GRID AND CLOUD: This chapter summarizes the key differences between grid and cloud computing, focusing on business models, resource management, resource provisioning, and resource availability. It explains the contrasting business models, the use of batch systems versus virtualization in resource management, and the different approaches to resource provisioning and availability. The chapter also points out the challenges of balancing resource utilization and energy consumption in cloud computing.
Keywords
Cloud computing, Grid computing, IaaS, PaaS, SaaS, Virtualization, Distributed Systems, Utility Computing, Service-Oriented Architecture, Resource Management, Business Models, Scalability, Fault Tolerance, Security.
Frequently Asked Questions: A Comparative Analysis of Cloud and Grid Computing
What is the main focus of this document?
This document provides a comprehensive comparison of cloud and grid computing, analyzing their similarities, differences, architectures, service models, and historical context. It explores the evolution of cloud computing from grid computing and examines the distinct characteristics that define each paradigm.
What are the key themes explored in this comparative analysis?
Key themes include a comparison of cloud and grid computing architectures, an analysis of cloud computing's service and deployment models, an examination of the key differences in their business models, resource management, and resource availability, an exploration of their historical context and evolving popularity, and a discussion of the relationship between cloud computing and other relevant technologies like utility computing and distributed systems.
What are the different deployment models discussed in relation to cloud computing?
The document details four cloud computing deployment models: public, private, community, and hybrid clouds. Each model's advantages, security concerns, and typical applications are explained. The increasingly important concept of Green Cloud Computing is also introduced.
What are the different service models discussed in relation to cloud computing?
The three main service models are Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), and Software-as-a-Service (SaaS). The document outlines their functionalities, applications, advantages, and limitations.
How does the document define cloud computing?
The document acknowledges the lack of a universally agreed-upon definition for cloud computing. It presents several definitions from various sources, highlighting inconsistencies and the ongoing evolution of understanding. It also mentions Gartner's definition: massively scalable IT capabilities provided as a service.
How does the document define grid computing?
Grid computing is defined based on Ian Foster's work, emphasizing its focus on coordinating resources without centralized control using standard protocols. This is contrasted with the cloud computing paradigm, which relies on next-generation data centers and virtualization.
What is the relationship between cloud computing and grid computing?
The document argues that cloud computing evolved from grid computing, shifting the focus from resource delivery to a more service-oriented, economy-based model. It highlights how cloud computing can be seen as a scaled and democratized version of grid computing.
What are the major differences between cloud and grid computing?
Key differences are summarized in terms of business models, resource management (batch systems vs. virtualization), resource provisioning, and resource availability. The contrasting approaches to balancing resource utilization and energy consumption are also discussed.
What architectural aspects of cloud computing are covered?
The document discusses how cloud architecture aggregates heterogeneous components (grids, clusters, supercomputers) to serve millions of users. It addresses challenges of large-scale data processing, including scaling machines on demand, distributing jobs, and managing resource allocation. Common applications such as processing pipelines, batch processing systems, and websites are showcased.
What is the historical context provided regarding cloud and grid computing?
The document analyzes the changing popularity of various computing paradigms over time using data from Google Trends, illustrating the shift from cluster computing to grid computing and the increasing dominance of cloud computing. It also places cloud computing within the broader context of Web 2.0 applications.
What are the key words associated with this document?
Cloud computing, Grid computing, IaaS, PaaS, SaaS, Virtualization, Distributed Systems, Utility Computing, Service-Oriented Architecture, Resource Management, Business Models, Scalability, Fault Tolerance, Security.
- Quote paper
- Er. Bijoy Boban (Author), 2013, Comparative analysis between Grid and Cloud computing, Munich, GRIN Verlag, https://www.grin.com/document/212932
