Cloud Computing Vs. Grid Computing: How Do They Differ?

Grid computing was something everyone talked about as "the next big thing" until it was replaced by the term, cloud computing. As some technology enthusiasts predicted, cloud computing did not spell the end of grid computing. It still exists outside the world of buzzwords and news bytes. Before we delve into how they differ, let us quickly refresh our minds with their definitions.

Grid Computing

The concept of grid computing is not new. In a way, it is nothing but parallel or distributed computing; however, the difference lies in the scale and complexity! So imagine parallel processing at a level where instead of sharing one or more resources, each and every computing resource is shared among all the computers within the network (as if they form an interconnected grid). Now imagine that the grid can consist of several different authorized heterogeneous systems, even owned by different organizations! It would be like a huge supercomputer with unmatched processing power, memory capacity and data storage capacity suitable for the most complex computations, but really it is just a network of interconnected computers. As far as the user of a grid computer is concerned, he/she is just using the local computer (now a supercomputer owing to the grid links) unaware of the links contributing to the power and enormous complexity of the network grid or cluster to which that machine belongs.

Cloud Computing

Cloud computing in fact evolved from grid computing and belongs to the same paradigm of load sharing within virtualized resources and providing on-demand computing power in a dynamically scalable fashion. Just as it sounds from their definitions, both cloud computing and grid computing are overlapping concepts. The key emphasis with the Internet-based cloud computing paradigm however, remains in achieving economies of scale in terms of the computing infrastructure utilization. Cloud computing is a buzzword today, mostly because of its commercial viability with regard to businesses being able to offload overburdened IT infrastructures with value-added capabilities. Now you might wonder, if both grid and cloud computing share the same vision of achieving greater computing scalability, are they just fancy technical jargon describing the same technology? Not really. So, how do they differ? Let us study the points of contrast between grid computing and cloud computing.

Grid Computing Vs. Cloud Computing

	Grid Computing	Cloud Computing
Business Model	Typically, grid infrastructures are accessed by multiple, heterogeneous organizations or project teams that typically share a common goal and need access to a virtual supercomputer to work on a single task or a single set of tasks. However, the users or project sponsors would have to bear the enormous cost of setting up and maintaining and monitoring the grid. When compared to accessing a cloud infrastructure that charges only as per consumption of resources, the set-up costs of a grid along with the cost of ownership of resources (like network administration, maintenance staff, etc.) are likely to be phenomenally high.	A customer accessing a cloud infrastructure or service will pay the cloud provider on a pay-per-use basis. The business model relies on optimizing utilization such that the cost makes sense for the customer as well as brings profits to the provider. We can perhaps associate it to the use of utilities such as electricity, gas, etc., or purchasing in bulk, but only when there's a requirement or demand. The benefit is in achieving economies of scale. It's independent of whether the task requires computational power or increased storage capacity. The customer is ideally not involved with the building or maintenance of the cloud infrastructure or services. This feature of abstraction is common to both grid computing and cloud computing.
Computing Model	Grid computing does not have universal standards with regard to configuration of systems and software. Some software and most algorithms and codes require major restructuring in order to use all the benefits of "parallel processing" available with grid computing. Even data communication protocols are grid-specific. Since most resources are being shared, network congestion control, fairness in allocation, reduction in latency, etc., are factors governing the development of grid protocols. Standard protocols are just not agile or flexible to support grid infrastructures.	Cloud computing has a more commercial focus and is therefore, more flexible when compared to the grid model. For example, expansion of a business requiring more resources is as easy as informing your provider to avail their seamless and mostly automated expansion services. Even writing a new code etc., becomes less time-consuming with the use of generic software. Existing protocols such as Web Services (WSDL, SOAP), and some advanced Web 2.0 technologies such as REST, RSS, AJAX, etc., can be utilized in cloud-based systems.
Security	We have already seen that the grid infrastructure comprises diverse configurations and platforms. Hence, the security for such a system would be a consideration right from the setting up of the grid. Important factors considered are authentication (single sign-on), authorization, credential, conversion, auditing, and delegation. Typically, a grid infrastructure has operational autonomy which ensures greater security controls and protocols. However, providing a security layer to a grid infrastructure is a time-consuming process.	For obvious reasons (relative homogeneity of cloud systems), cloud security models are relatively simpler and less secure than that of grid computing. It is a matter of mutual understanding where the provider ensures protection of the customer's data and applications. Private cloud (where the infrastructure is dedicated to a single customer) and community cloud (cloud infrastructure shared between a finite set of multiple customers) are effective ways to restrict access to authorized, limited number of users. Cloud infrastructure typically use Web forms (over Secured Sockets Layer (SSL)) to create and manage account information for end-users. Encrypted communications ensure secure identity and password management.
Some Potential Issues	- Is there a possibility of lesser complexity in building grids? - Is there a possibility of developing ubiquitous standards for grid infrastructure?	- Does the cloud provider have a disaster management and recovery mechanism in place to deal with loss of customer's data? - Is there a backup/contingency plan in case of disasters to ensure business continuity? - What if the cloud provider exits the business or is acquired by another company, what happens to the customer's data and cloud operations?
Examples	- The European Organization for Nuclear Research (CERN) is one of the leading organizations running major grid computing initiatives including analyzing chemical compounds in the search for potential drugs for diseases such as avian flu. - SETI (Search for Extraterrestrial Intelligence) @Home project is one of the earliest grid initiatives that downloads and analyzes data from radio telescope. Participants simply need to download and run a program to join the grid network.	- Salesforce.com, Google App Engine, Microsoft Azure, and Amazon EC2 are famous cloud providers in the public domain (they provide services to anyone who needs them over the public Internet). - Other service providers include the open source AbiCloud, Elastichosts and NASA's Nebula platform.

From the above discussion of contrasting factors between grid computing and cloud computing, it is clear that it's not a simple matter of choosing one over the other. The trade-offs involved relate to which functionality is most suitable over the other. It seems as though cloud computing is more suited to businesses looking to derive value out of their IT operations in a streamlined fashion. The agility that comes with utilizing services from the cloud complements its scalability. The grid computing paradigm on the other hand, has been the traditional arena of funded scientific research although there are emerging instances of its use in biomedical, financial and industrial research. It now finds applications in weather modeling and weapons test simulations. In fact, web serving (serving requests of website content from users located all over the world) is an example of a commercial application that benefits from the grid infrastructure.

Both computing paradigms are revolutionary; however, they're both still immature. Their scalable properties are as promising as is their ability to provide on-demand resources. However, both are struggling to battle their inherent weaknesses and emerge as viable commercial options for businesses. Experts across the board agree that while cloud computing will not replace grids, they might merge and few even imagine the possibility of a World Wide Grid! By Preeti Sunil