Main differences between grids and clouds.

Clouds and grids compared

Let’s take a look at the main differences between grids and clouds.

	Grid computing	Cloud computing
What?	Grids enable access to shared computing power and storage capacity from your desktop	Clouds enable access to leased computing power and storage capacity from your desktop
Who provides the service?	Research institutes and universities federate their services around the world through projects such as EGI-InSPIRE and the European Grid Infrastructure.	Large individual companies e.g. Amazon and Microsoft and at a smaller scale, institutes and organisations deploying open source software such as Open Slate, Eucalyptus and Open Nebula.
Who uses the service?	Research collaborations, called "Virtual Organisations", which bring togetherresearchers around the world working in the same field.	Small to medium commercial businesses or researchers with generic IT needs
Who pays for the service?	Governments - providers and users are usually publicly funded research organisations, for example through National Grid Initiatives.	The cloud provider pays for the computing resources; the user pays to use them
Where are the computing resources?	In computing centres distributed across different sites, countries and continents.	The cloud providers private data centres which are often centralised in a few locations with excellent network connections and cheap electrical power.
Why use them?	- You don`t need to buy or maintain your own large computer centre       - You can complete more work more quickly and tackle more difficult problems.       - You can share data with your distributed team in a secure way.	- You don`t need to buy or maintain your own personal computer centre       - You can quickly access extra resources during peak work periods
What are they useful for?	Grids were designed to handle large sets of limited duration jobs that produce or use large quantities of data (e.g. the LHC and life sciences)	Clouds best support long term services and longer running jobs (E.g. facebook.com)
How do they work?	Grids are an open source technology. Resource users and providers alike can understand and contribute to the management of their grid	Clouds are a proprietary technology. Only the resource provider knows exactly how their cloud manages data, job queues, security requirements and so on.
Benefits?	- Collaboration: grid offers a federated platform for distributed and collective work. - Ownership : resource providers maintain ownership of the resources they contribute to the grid - Transparency: the technologies used are open source, encouraging trust and transparency. - Resilience: grids are located at multiple sites, reducing the risk in case of a failure at one site that removes significant resources from the infrastructure.	- Flexibility: users can quickly outsource peaks of activity without long term commitment - Reliability: provider has financial incentive to guarantee service availability (Amazon, for example, can provide user rebates if availability drops below 99.9%) - Ease of use: relatively quick and easy for non-expert users to get started but setting up sophisticated virtual machines to support complex applications is more difficult.
Drawbacks?	- Reliability: grids rely on distributed services maintained by distributed staff, often resulting in inconsistency in reliability across individual sites, although the service itself is always available. - Complexity: grids are complicated to build and use, and currently users require some level of expertise. - Commercial: grids are generally only available for not-for-profit work, and for proof of concept in the commercial sphere	- Generality: clouds do not offer many of the specific high-level services currently provided by grid technology. - Security: users with sensitive data may be reluctant to entrust it to external providers or to providers outside their borders. - Opacity: the technologies used to guarantee reliability and safety of cloud operations are not made public. - Rigidity: the cloud is generally located at a single site, which increases risk of complete cloud failure. - Provider lock-in: there’s a risk of being locked in to services provided by a very small group of suppliers.
When?	The concept of grids was proposed in 1995. The Open science grid (OSG) started in 1995 The EDG (European Data Grid) project began in 2001.	In the late 1990`s Oracle and EMC offered early private cloud solutions . However the term cloud computing didn't gain prominence until 2007.

Difference Between Grid Computing Vs. Distributed Computing

Difference Between Grid Computing Vs. Distributed Computing

Definition of Distributed Computing

Distributed Computing is an environment in which a group of independent and geographically dispersed computer systems take part to solve a complex problem, each by solving a part of solution and then combining the result from all computers. These systems are loosely coupled systems coordinately working for a common goal. It can be defined as

1. A computing system in which services are provided by a pool of computers collaborating over a network .
2. A computing environment that may involve computers of differing architectures and data representation formats that share data and system resources.

Definition of Grid Computing

The Basic idea between Grid Computing is to utilize the ideal CPU cycles and storage of million of computer systems across a worldwide network function as a flexible, pervasive, and inexpensive accessible pool that could be harnessed by anyone who needs it, similar to the way power companies and their users share the electrical grid. There are many definitions of the term: Grid computing:

1. A service for sharing computer power and data storage capacity over the Internet
2. An ambitious and exciting global effort to develop an environment in which individual users can access computers, databases and experimental facilities simply and transparently, without having to consider where those facilities are located. [RealityGrid, Engineering & Physical Sciences Research Council, UK 2001] http://www.realitygrid.org/information.html
3. Grid computing is a model for allowing companies to use a large number of computing resources on demand, no matter where they are located.
   www.informatica.com/solutions/resource_center/glossary/default.htm

Grid Computing Vs. Distributed Computing

Since 1980, two advances in technology has made distributed computing a more practical idea, computer CPU power and communication bandwidth. The result of these technologies is not only feasible but easy to put together large number of computer systems for solving complex computational power or storage requirements. But the numbers of real distributable applications are still somewhat limited, and the challenges are still significant (standardization, interoperability etc). 

As it is clear from the definition, traditional distributed computing can be characterized as a subset of grid computing. some of the differences between these two are

1. Distributed Computing normally refers to managing or pooling the hundreds or thousands of computer systems which individually are more limited in their memory and processing power. On the other hand, grid computing  has some extra characteristics. It is concerned to efficient utilization of a pool of heterogeneous systems with optimal workload management utilizing an enterprise's entire computational resources( servers, networks, storage, and information) acting together to create one or more large pools of computing resources. There is no limitation of users, departments or originations in grid computing.

2. Grid computing is focused on the ability to support computation across multiple administrative domains that sets it apart from traditional distributed computing. Grids offer a way of using the information technology resources optimally inside an organization involving virtualization of computing resources. Its concept of  support for multiple administrative policies and security authentication and authorization mechanisms enables it to be distributed over a local, metropolitan, or wide-area network.