Do the differences include resource pooling, rapid elasticity, on demand resource provisioning?
Dear Dr. Dheeraj Rane ,
Just see this complete and modern hot reference:
Article Cloud IoT as a Crucial Enabler: a Survey and Taxonomy
Grid computing is where more than one computer coordinates to solve a problem together. Often used for problems involving a lot of number crunching, which can be easily parallelisable.
Cloud computing is where an application doesn't access resources it requires directly, rather it accesses them through something like a service. So instead of talking to a specific hard drive for storage, and a specific CPU for computation, etc. it talks to some service that provides these resources. The service then maps any requests for resources to its physical resources, in order to provide for the application. Usually the service has access to a large amount of physical resources, and can dynamically allocate them as they are needed.
In this way, if an application requires only a small amount of some resource, say computation, then the service only allocates a small amount, say on a single physical CPU (that may be shared with some other application using the service). If the application requires a large amount of some resource, then the service allocates that large amount, say a grid of CPUs. The application is relatively oblivious to this, and all the complex handling and coordination is performed by the service, not the application. In this way the application can scale well.
For example a web site written "on the cloud" may share a server with many other web sites while it has a low amount of traffic, but may be moved to its own dedicated server, or grid of servers, if it ever has massive amounts of traffic. This is all handled by the cloud service, so the application shouldn't have to be modified drastically to cope.
A cloud would usually use a grid. A grid is not necessarily a cloud or part of a cloud.
Cloud computing and grid computing are scalable. Scalability is accomplished through load balancing of application instances running separately on a variety of operating systems and connected through Web services. CPU and network bandwidth is allocated and de-allocated on demand. The system's storage capacity goes up and down depending on the number of users, instances, and the amount of data transferred at a given time.
Both computing types involve multitenancy and multitask, meaning that many customers can perform different tasks, accessing a single or multiple application instances. Sharing resources among a large pool of users assists in reducing infrastructure costs and peak load capacity. Cloud and grid computing provide service-level agreements (SLAs) for guaranteed uptime availability of, say, 99 percent. If the service slides below the level of the guaranteed uptime service, the consumer will get service credit for receiving data late.
The Amazon S3 provides a Web services interface for the storage and retrieval of data in the cloud. Setting a maximum limits the number of objects you can store in S3. You can store an object as small as 1 byte and as large as 5 GB or even several terabytes. S3 uses the concept of buckets as containers for each storage location of your objects. The data is stored securely using the same data storage infrastructure that Amazon uses for its e-commerce Web sites.
While the storage computing in the grid is well suited for data-intensive storage, it is not economically suited for storing objects as small as 1 byte. In a data grid, the amounts of distributed data must be large for maximum benefit.
A computational grid focuses on computationally intensive operations. Amazon Web Services in cloud computing offers two types of instances: standard and high-CPU.
Wireless grids edgeware wiglets and gridlets - a new class of edge applications for machine to machine, machine to people, and machine to application communication and resource sharing - further blur the lines between both traditional 'grid computing' and newly traditional - cloud computing. The first mistake most folks make is thinking either is all about - computing - when the critical issues are all about services and applications which can be mashed up across clouds and edge devices; more securely and easily if a grid is involved.
In simple Grid Mostly Works on Hardware part as located distributed over network mostly (heterogeneous) for solving big computational problems by (MP msgs passing/ different tech)
In cloud we are using remotely hardware mostly Cluster (Homogeneous) for personal / corporate work even we don't required high computational power (By different Services SaaS /PaaS / AaaS)
if you required more just mail me for big explanations ([email protected])
*** In cloud computing an application doesn't access resources it requires directly, it accesses them through something like a service.It talks to some service that provides resources such as CPU,Storage. The service then maps any requests for resources to its physical resources, in order to provide for the application.
*** Clouds are a large pool of easily usable and accessible virtualized resources (such as hardware, development platforms and/or services). These resources can be dynamically reconfigured to adjust to a variable load (scale), allowing also for an optimum resource utilization. This pool of resources is typically exploited by a pay peruse model in which guarantees are offered by the Infrastructure Provider by customized service level agreements.
*** Cloud is not free. It is a service, provided by different service providers and they charge according to your work done (not Free = Limited Services)
*** Cloud: Set diameter of a ball, material from pre-set types, height from which the ball is dropping, etc and ask for results
*** If an application requires only a small amount of some resource, say computation, then the service only allocates a small amount, say on a single physical CPU (that may be shared with some other application using the service). If the application requires a large amount of some resource, then the service allocates that large amount, say a grid of CPUs. The application is relatively oblivious to this, and all the complex handling and coordination is performed by the service, not the application. In this way the application can scale well.
** Grid computing is where more than one computer coordinates to solve a problem together. Often used for problems involving a lot of number crunching, which can be easily parallelisable.
** A Grid is a hardware and software infrastructure that clusters and integrates high-end computers, networks, databases, and scientific instruments from multiple sources to form a virtual supercomputer on which users can work collaboratively within virtual organisations
** Grid is Mostly free used by academic research etc.
** Grids are used as computing/storage platform.
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We start talking about cloud computing when it offers services. I would almost say that cloud computing is higher-level grid. Now I know these are not definitions, but maybe it will make it more clear.
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* As far as application domains go, grids require users (developers mostly) to actually create services from low-level functions that grid offers. Cloud will offer complete blocks of functionality that you can use in your application.
* Example (you want to create physical simulation of ball dropping from certain height): Grid: Study how to compute physics on a computer, create appropriate code, optimize it for certain hardware, think about paralellization, set inputs send application to grid and wait for answer
* I would say that if you created OS for grid, you would actually create cloud OS.
Grid and Cloud are two terms used in computing to refer to two types of resource sharing techniques where multiple computing devices and usually the Internet are involved.
Grid computing
Grid computing is a form of distributed computing where a virtual computing system is compiled by using many loosely connected computing devices to perform a large computing task. They are loosely connected because they can be from multiple administrative realms coupled to effectively combine computing resources to reach a general goal. The goal can typically be a single problem – usually a scientific of technical problem that requires a large amount of processing performed on a huge data set.
Cloud Computing
Cloud computing refers to any computing services provided by hosted systems over the Internet. The service provided can be one of the infrastructure, platform or software services. The salient feature of cloud computing is that the service is fully managed by the service provider and the user needs minimum facilities like a personal computer and the Internet to utilize the service. Due to the fact that the service providers host the services, the services are presented to the users in a simple way where they are not needed to understand how the services are provided.
Grid computing is a form of distributed system where many loosely connected computers are combined targeting to supply computing resources to reach a general goal.
Cloud computing is any computing service managed and provided by a service provider over the Internet.
Some characteristics of Cloud Computing:
- Common: multi-tenant infrastructure - not single or isolated tenancy. Accessible by thousands / millions of users
- Online Utility: pay-for-use pricing
- on Demand: immediate, infiite, invisable scaleability
Cloud is not necessarily a grid. Enterprise cloud computing focuses on business function and rapid delivery of business value
A Cloud normally requires a grid as its underlying infrastructure; however, i know of at lease one environment that offers Software-as-a-Service on a non-grid infrastructure.
Some services can be provided at a grid-level, such as Storage-as-Service, Network-as-a-Service etc. Cloud is a higher level option for consumers where services can be provided, such as (SaaS.). As others pointed out, the consumer can obtain services from a Cloud without knowing how the underlying grid allocates resources and on what kinds of physical infrastructure components it runs.
I find it unfortunate that people are using the term "Cloud" in the context of both high-level services such as SaaS and infrastructure. I have promoted the thinking that "Cloud" refers to services and "Grid" refers to underlying infrastructure; however, it seems that marketing wins again -- "Cloud" is a better buzzword.
To be frank, and no offense, but most of the answers to the grid v cloud question given on this list relate to - history - and not present industry best practice, nor latest research.
The TM Forum is about to release a white paper on 'Workplace as a Service' developed by the Enterprise Cloud Leadership Council, which the Syracuse University Wireless Grid Lab I direct contributed to. Reference Architectures, open specifications, next gen APIs are included in the doc. When available I will share a link back to this list, as well as a pointer to a soon-to-be-released related doc describing the WiGiT v0.2 open specification, which unites clouds of all types, and grids both wireless and traditional, with edge services and devices. Which, I humbly suggest, answers the question : )
I would love to read that paper. When and where will it be available?
Cloud computing:
Cloud is basically an extension to the object-oriented programming concept of abstraction. Here cloud means the Internet. For the end users it is just getting outputs for certain inputs, the complete process that lead to the outputs is purely invisible. Computing is based on virtualized resources which are placed over multiple servers in clusters.
Also within the “cloud computing” family, are what’s known as a SPI model SaaS, PaaS and IaaS. These are the services available on the cloud and do all the heavy lifting using someone else’s infrastructure. Cloud computing eliminates the costs and complexity of buying, configuring, and managing the hardware and software needed to build and deploy applications; these applications are delivered as a service over the Internet (the cloud).
Grid computing:
Grid systems are designed for collaborative sharing of resources. It can also be thought of as distributed and large-scale cluster computing. A Grid is basically the one that uses the processing capabilities of different computing units for processing a single task. The task is broken into multiple sub-tasks, each machine on a grid is assigned a task. As when the sub-tasks are completed they are sent back to the primary machine which takes care of the all the tasks. They are combined or clubbed together as an output.
Hi Mark, the TM Forum Enterprise Cloud Leadership Council's 'Workplace as a Service' White Paper has been released. While dated January 2013 it was only recently posted in final form.
The white paper details case studies of secure cloud to edge applications as a service, and discusses how persistent 'grids' can facilitate Bring Your Own Device secure workplace services Compute Infrastructure as a Service, Virtual Private Cloud, and Workplace as a Service concepts are also explored and compared; while all OASIS specs are illustrated to be - potentially virtualized and brought into a WPaaS framework.
As to how to get your hands on the White Paper; right now the answer is to join TM Forum; or if already a member, just download it.
We plan further publications referencing the white paper, and will add those to our own ResearchGate page when available. In the meantime, my Syracuse University WiGiT Lab's publication list includes several works also referenced in the White Paper, including the WiGiT v0.1 open specs. WiGiT v0.2 will be posted by the end of the month; and I will come back to this page and announce when that is up; as the v0.2 was developed essentially in sync with the TM Forum Enterprise Cloud Leadership Council.
Presently, we are engaged with TM Forum on next stage work, including defining open APIs which essentially will provide very lightweight shortcuts between cloud - and especially - wireless grids. More to come; and more to do!
http://wigit.ischool.syr.edu
grid computing is many to one (massive power) where as cloud computing one to many. This is the main difference what i feel and also cost wise cloud computing resources are very cheap when compare to grid computing resources.there are many definitions are given for both grid and cloud. for full details please contact 8008117775
Metaphorically speaking, both grid and cloud architectures turn on the light to your computing power. The first by rubbing many rocks, the second by using a single lighter.
Grid Computing
where resources are dedicated for one computational task and geographically distributed..
cloud computing:
where some services are used to access resources for ex. IAAS,PAAS,SAAS...and they are not built for one computational task..
Hi again, reviewing this very interesting thread I belatedly recall my promise to share some docs from the Enterprise Cloud Leadership Council of TM Forum; and from WiGiT.
Article Workplace as Service White Paper By Enterprise Cloud Leaders...
And here's another very closely related doc, the WiGiT Workplace as a Service Use Case
And to show I'm not making this all up, attached is the 'Single Sign On to Workplace as a Service for Cloud Mobility' presentation drat from TM Forum's Nice, France, May Catalyst project with Ericsson and other firms participating.
Wireless grids are the next wave, tying grids, clouds, and wireless systems together inside and outside of virtual organizations...
There are a few key differences. To me, the "authority" is where the biggest difference is. In CLOUD COMPUTING, the "authority" is a FOR-PROFIT entity, such as Amazon (i.e., AWS), MS Azure (Microsoft) , etc ... Google Apps. Well, Google might not be charging you for some (or any) services, but, nothing is free ! you are paying for it if you are using Google free cloud resources ... implicitly ... DROPBOX is a type of Cloud service (just storage, but, under the same category). In the end, they are enticing you with the free offerings, to eventually make you pay for higher-up services ... If you never sign on with the paying version, Oh well, its cost of doing business.
GRID computing aims to achieve a task by collectively pooling volunteering resources ... TERAGRID (which is a joint academically-originated grid funded by NSF initially) is an example. While the goal of this grid is not making money, they certainly have the utmost emphasis on PERFORMANCE. NASA's SETI program can be downloaded by any planet-caring individual in helping them find life outside earth ... So, it is a grid, with a lot less emphasis on PERFORMANCE, but, rather, POOLING MORE RESOURCES.
There's no need to get wrapped up in nomenclature. Grid is the name of a mostly-failed precursor to what we'd call SaaS today (perhaps a bit PaaS). Cloud is just remotely-provisioned, outsourced IT, with IaaS, PaaS and SaaS just describing layers of responsibility (from hardware to OS/platform to application/service). All of these might be subsumed in another name sometimes used: Utility Computing. The really interesting thing is that Grid was mostly a flop, even though it met some needs (a way to create a workflow that utilizes resources that are provided, even donated, by different organizational domains.) Not that you can't do workflow on any other infrastructure, and not that Cloud has to be commercial or that it can't span sites or organizations.
Historically, there are really just a couple principles that have enabled the current state of art. The use of virtualization is what enables IaaS, and the flexibility of that Cloud layer is often what the next layer is running on (PaaS is often provided on top of IaaS.) But PaaS has also happened because certain OS/middleware became very prevalent (namely LAMP, though with some variants.)
These days, "Grid" doesn't mean much - my organization, which provides shared academic HPC resources, sometimes uses the term, though PaaS would be apt as well. Globus's most widespread use is to automate file transfers. The CERN LHC Grid is really mostly a dedicated job/file/workflow automation/queueing system, which I wouldn't call a Grid at all...
In short Grid and Cloud are almost synonyms: common usage is too messy to claim much distinctiveness.
The document "Cloud Computing and Grid Computing 360-Degree Compared" by Ian Foster could shed some more light on this.
Although cloud and grid computing have much in common, but they remain two different concepts. The major difference between cloud computing and grid computing is in the architecture (modus-operandi). Cloud computing divides large tasks into chunks (small portions), disburse these portions across many machines for simultaneous processing, as well as then gather all of it. Grid computing uses the best resource available from the pool without breaking up tasks. Local resources undertake the processing at the grid site, and also wait in queue for access to the resource. In clouds, the location of the processing center remain hidden, but in grids this is transparent, and also users even have the option of selecting the location based on the list of available resources. Grids mainly operate in a project-oriented model, to address large-scale computing problems where Clouds mainly address internet-scale computing problems. Cloud computing and grid computing are not mutually exclusive, and also many organizations use both together to speed up tasks. For instance, organizations use grid computing when, select the best available resource to perform a task, but use cloud computing to execute the task faster using the different devices available within such resource.
Regardless of different implementation of these technologies, Grid computing performs well for scientific and workflow workloads and Cloud environments outperforms and suited well for workloads with small computing demands like transnational workloads.
Hello yet again,
My latest update on the research, innovation testbed,open specification and publication progress we have made around wireless grids; which is an increasingly valid answer to the question asked as to the difference between cloud and grid computing: they can both both be functions of a smart service system, for which they are highly complementary; and BOTH are necessary.
Our work over the past decade on small, dynamic (wireless) grids, across mobile phones, notebooks, laptops, sensor networks of Things has identified the necessary elements for wireless grids edgeware to interact readily with large scientific grids, which some of my Researchgate colleagues may have more experience with.
Similarly, when most folks think 'cloud' they are thinking of an Amazon Web Service or a Microsoft Azure - scale distributed computational platform as a a service, which bundles in infrastructure as a service as needed. Or, they think of a Salesforce.com, Box, or Dropbox storage application as a service.
Now, with microgrid/distributed generation systems of diverse combinations for conventional and alternative energy with demand response systems, the emergence of technically viable smaller scale systems is also advantageous for distributed power systems, green data centers, and other envrionmentally efficient energy solutions.
So my latest answer to the grid v cloud question is grid and cloud technologies and approaches can increasingly overlap and be virtually integrated to create secure, private smart service systems.
Those service systems are composed of and can operate on behalf of human, machine, and other Non-Person Entity user identities, employing cloud applications as a service in a grid. That is, cloud to edge, in the Internet of Things; with edgeware applications as I have defined them, as either wiglet (open/non-proprietary cloud to edge applications) or gridlet (proprietary). As long as open Application Programming Interfaces (APIs) are defined and role-based access control is ALWAYS enforced, then the number of downloads and uploads can be slashed and a more efficient and secure - grid - can be the space in which the workplace, or the entertainment center, exists.
Managing the risk of actually doing all that, securely in the Internet of Things, is the topic of my soon-to-be published book, which is co-authored by Dr. Tyson Brooks:
Cloud to Edgeware. Wireless Grid Applications, Architecture and Security for the “Internet of Things”, Lee W McKnight (Syracuse University School of Information Studies (iSchool), USA; MIT PhD & Innovation Instructor), Tyson T Brooks (Syracuse University, USA & US Department of Defense, USA) will be published this November by Imperial College Press/World Scientific Press. The book and elaborates on what I said here. To review the abstract, table of contents, or pre-order ; ) - see the attached link.
More broadly speaking, the GENI 'Global Environment for Networked Innovations' US federal research effort, and Internet2, are also hanging with the OGF (Open Grid Forum) open standards/services/software and specifications organization, for example in the gigabit city/applications effort USignite.org. Many of you may have interest in this effort.
Meaning, in other words, the real action is not on the 'cloud' or in the 'grid'; it is somewhere, virtually, in between; incorporating both secure wireless grids and virtual private cloud and especially hybrid cloud applications spanning public and private cloud services and technologies; and standards; with machine to machine communication across ad hoc heterogeneous software defined networks of cyberphysical systems; in the Internet of Things. Things which are accessible outside of this nascent environmnent in the Internet of Things, to be frank I consider intrinsically suspect as to their degree of information security and data protection. Which is not to say there are not a lote of holes and threats and risks to be managed also in a dynamic wireless grid.
Which is what is addressed in WiGiT v0.2 Open Specifications Technical Requirements for Wireless Grids; available at the attached link. WiGiT Technical Requirements v0.3 will be released later this spring as well as a number of updated use cases.
Which may inspire some of you to Build Your Own - Grid; or do you prefer to call it a Cloud; or a - Thing on the Internet of Things? : ) Sorry to be speaking in jargon/riddles, but honestly all the virtual pieces can be assembled a wide variety of ways now with social media-easy user interfaces to orders of magnitude enhanced security, privacy, and energy efficiency, with edgeware-enabled services and systems. than any existing system which is what makes these indeed - interesting times.
So, if you don;t want to wait for the book and are ready to build your own - cloud to grid system; then perhaps prepare your own WiGiT Use Case (Since WiGiT itself is a hyper-lightweight Virtual Organization, there is no entry barrier if you wish to - Build Your Own WiGiT Use Case); and/or contribute to WiGiT Technical requirement v0.4. (If interested, send me a note on researchgate and we can discuss further - all serious - students of the future - are welcome; especially since v0.4. So we will -still - be a long way from - 1 and have time to work out the kinks, and validate the new uses - together.
Finally, noting I am writing this lengthy message February 3, 2015, I note that every summer since 1998 I lecture for MIT's 'Technology, Organizations and Innovation: Putting Ideas to Work.' week-long professional education course. which is next offered June 22-26, 2015. In contrast to most other 'innovation' cheer-leading courses and analyses, we focus through deep real case analyses, on how almost impossibly difficult it is for a firm to successfully innovate to a sustainably profitable enhanced market position; and suggest survival mechanisms and cross-organizational dynamic innovation coalition strategies which - may - permit an innovator, and and an innovation, to succeed. So yes, at MIT, we teach every year that having the best technology does not guarantee success over inferior but better-positioned, politically or economically-supported solutions. I have been leading a day or a half a day of the course; with wireless grids and cloud 'edgeware' being a focus for at least the past five years.
If anyone is still reading this note...you are likely the right type to consider joining me at MIT next June - it is always tremendous fun for the students and the instructors, who learn a lot from you all too.
And yes, bringing wireless grid innovations along to the point of demonstrations such as what Syracuse University's NSF PFI WiGiT project did with Cisco, CSC/ServiceMesh Ericsson, Desutsche Telekom, Portugal Telecom, TOA Tech, UBS, and others at TM Forum's May 2013 'Management World Europe' for 'Single Sign-On to Workplace as a Service' illustrates both the challenges and the high degree of integration of cloud and grid edgeware approaches I am advocating. Of course this remains incomplete and very difficult to validate at scale, given the multiplicity of technologies, applications and services which we are integrating. In the May 2013 Nice demo, we were including a single-sign-on identity service, which is rather grid-like; as well as a hybrid cloud management platform, cloud services, and cloud to edge workplace as a service applications. The slides from that event are my final attachment. Enjoy! (And perhaps - see a few of you next June at MIT! : )
PS: Sorry for the too-long note; but as you all see I have - a lot - to say on this topic and feel the conventional views no longer match the virtual intersection points of cloud and grid technologies. Hence our suggested new vocabulary of edgeware wiglets and gridlets as new species of cloud to edge wireless grid applications, and related concepts.
An updated glossary will be available in v0.3 later this spring as well.
PPS: Very seriously, if you find some of what I am saying of interest and relevant to your own research interests - please contact me as we build momentum towards - v1.0; in cooperation with many other researchers and practitioners in real and virtual organizations. I will put you in touch with my students who are leading the coordination of this increasingly - virtually sprawling - distributed testbed.
http://www.worldscientific.com/worldscibooks/10.1142/9354
http://web.mit.edu/professional/short-programs/courses/technology_organizations_and_innovation_putting_ideas_to_work.html
Technical Report Open Specifications for Wireless Grids Technical Requirement...
Data TMForumSSOtoWPaaSnice5.13.13
Grid computing system is a widely distributed resource for a common goal. It is Brother of Cloud Computing and Sister of Supercomputer. We can think the grid is a distributed system connected to a single network. This types of computing work with the large volume of files. Basically, it is a cluster types system. So people call it cluster computing.
Source: https://www.cloudwebhostingtips.com/grid-computing-vs-cloud-computing-supercomputer/
Grid computer tends to be more geographically disperse and heterogeneous by nature. Grid network also has various types. A single grid is like dedicated connection but a common grid perform multiple tasks.
The size of the grid is large. So grid computing is like supercomputing. It consists of many network, computer, and middleware. Grid computer is dedicated to some specific function of the large volume of data. In the grid process, each task divided into a various process. All the process starts execution simultaneously on a different computer. As a result, very few seconds needs to execute and enjoy the flavor of supercomputing.
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