1. INTRODUCTION
Cloud computing is the next natural step in the evolution of on-demand, information technology services and products. To a large extent cloud computing, will be based on virtualized resources. The idea of cloud computing is based on a, very fundamental principal of `reusability of IT capabilities`. The difference that cloud computing brings compared to traditional concepts of ?grid computing?, distributed computing, ?utility computing, or ?autonomic computing is to broaden horizons across organizational boundaries.
According to the IEEE Computer Society Cloud Computing is:
"A paradigm in which information is permanently stored in servers on the Internet and cached temporarily on clients that include desktops, Entertainment centers, table computers, notebooks, wall computers, handhelds, etc."
Though many cloud computing architectures and deployments are powered by grids, based on autonomic characteristics and consumed on the basis of utilities billing, the concept of a cloud is fairly distinct and complementary to the concepts of grid, SaaS , Utility Computing etc. In theory, cloud computing promises availability of all required hardware, software, platform, applications, infrastructure and storage with an ownership of just an internet connection. people can access the information that they need from any device with an Internet connection?including mobile and handheld phones?rather than being chained to the desktop. It also means lower costs, since there is no need to install software or hardware. Cloud computing used to posting and sharing photos on orkut, instant messaging with friends maintaining and upgrading business technology.
Need for Cloud Computing
What could we do with 1000 times more data and CPU power? One simple question. That?s all it took the interviewers to bewilder the confident job applicants at Google. This is a question of relevance because the amount of data that an application handles is increasing day by day and so is the CPU power that one can harness.
There are many answers to this question. With this much CPU power, we could scale our businesses to 1000 times more users. Right now we are gathering statistics about every user using an application. With such CPU power at hand, we could monitor every single user click and every user interaction such that we can gather all the statistics about the user. We could improve the recommendation systems of users. We could model better price plan choices. With this CPU power we could simulate the case where we have say 1,00,000 users in the system without any glitches.
There are lots of other things we could do with so much CPU power and data capabilities. But what is keeping us back. One of the reasons is the large scale
architecture which comes with these are difficult to manage. There may be many different problems with the architecture we have to support. The machines may
start failing, the hard drives may crash, the network may go down and many other such hardware problems. The hardware has to be designed such that the
architecture is reliable and scalable. This large scale architecture has a very expensive upfront and has high maintenance costs. It requires different resources
like machines, power, cooling, etc. The system also cannot scale as and when needed and so is not easily reconfigurable.
The resources are also constrained by the resources. As the applications become large, they become I/O bound. The hard drive access speed becomes a
limiting factor. Though the raw CPU power available may not be a factor, the amount of RAM available clearly becomes a factor. This is also limited in this
context. If at all the hardware problems are managed very well, there arises the software problems. There may be bugs in the software using this much of data.
The workload also demands two important tasks for two completely different people. The software has to be such that it is bug free and has good data processing algorithms to manage all the data.
The cloud computing works on the cloud - so there are large groups of often low-cost servers with specialized connections to spread the data-processing chores among them. Since there are a lot of low-cost servers connected together, there are large pools of resources available. So these offer almost unlimited computing resources. This makes the availability of resources a lesser issue. The data of the application can also be stored in the cloud. Storage of data in the cloud has many distinct advantages over other storages. One thing is that data is spread evenly through the cloud in such a way that there are multiple copies of the data and there are ways by which failure can be detected and the data can be rebalanced on the fly. The I/O operations become simpler in the cloud
such that browsing and searching for something in 25GB or more of data becomes simpler in the cloud, which is nearly impossible to do on a desktop.
The cloud computing applications also provide automatic reconfiguration of the resources based on the service level agreements. When we are using applications out of the cloud, to scale the application with respect to the load is a mundane task because the resources have to be gathered and then provided to the users. If the load on the application is such that it is present only for a small amount of time as compared to the time its working out of the load, but occurs frequently, then scaling of the resources becomes tedious. But when the application is in the cloud, the load can be managed by spreading it to other available nodes by making a copy of the application on to them. This can be reverted once the load goes down. It can be done as and when needed. All these are done automatically such that the resources maintain and manage themselves.
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