Introduction The Greek myths tell of creatures plucked from the surface of the Earth and enshrined as constellations in the night sky. Something similar is happening today in the world of computing. In general, there is a shift in the geography of computation. What is cloud computing exactly? While there is a lack of precise scientific definitions for many of these terms, general definitions can be given. Cloud computing is an emerging paradigm in the computer industry where the computing is moved to a cloud of computers.
It has become one of the buzz words of the industry. It includes everything that sits in the bottom layer, i. Cloud computing ties together all these entities and delivers them as a single integrated entity under its own sophisticated management. It came partly from the cloud-like symbol used to represent the complexities of the networks in the schematic diagrams.
Itrepresents all the complexities of the network which may include everything from cables, routers, servers, data centers and all such other devices. Computing started off with the mainframe era.
They were dependent on the computer administrators to give them permission or to fix their problems. They had no way of staying up to the latest innovations. The personal computer was a rebellion against the tyranny of centralized computing operations. There was a kind of freedom in the use of personal computers. But this was later replaced by server architectures with enterprise servers and others showing up in the industry. This made sure that the computing was done and it did not eat up any of the resources that one had with him.
All the computing was performed at servers. Internet grew in the lap of these servers. With cloud computing we have come a full circle. We come back to the centralized computing infrastructure. But this time it is something which can easily be accessed via the internet and something over which we have all the control. Cloud computing- The Concept Cloud computing is Internet "cloud" based development and use of computer technology "computing".
It is a style of computing in which dynamically scalable and often virtualized resources are provided as a service over the Internet. Users need not have knowledge of, expertise in, or control over the technology infrastructure "in the cloud" that supports them. The concept incorporates infrastructure as a service IaaS , platform as a service PaaS and software as a service SaaS as well as Web 2. Examples of SaaS vendors include Salesforce. The term cloud is used as a metaphor for the Internet, based on how the Internet is depicted in computer network diagrams, and is an abstraction for the complex infrastructure it conceals.
Indeed many cloud computing deployments as of depend on grids, have autonomic characteristics and bill like utilities — but cloud computing can be seen as a natural next step from the grid-utility model. Some successful cloud architectures have little or no centralized infrastructure or billing systems whatsoever, including peer-to-peer networks like Bit Torrent and Skype and volunteer computing like 2.
The services are accessible anywhere that has access to networking infrastructure. The Cloud appears as a single point of access for all the computing needs of consumers.
Commercial offerings need to meet the quality of service requirements of customers and typically offer service level agreements. Open standards are critical to the growth of cloud computing and open source software has provided the foundation for many cloud computing implementations. Many cloud-computing offerings have adopted the utility computing model, which is analogous to how traditional utilities like electricity are consumed, while others are billed on a subscription basis.
Sharing "perishable and intangible" computing power among multiple tenants can improve utilization rates, as servers are not left idle, which can reduce costs significantly while increasing the speed of application development. A side effect of this approach is that "computer capacity rises dramatically" as customers do not have to engineer for peak loads.
Adoption has been enabled by "increased high-speed bandwidth" which makes it possible to receive the same response times from centralized infrastructure at other sites. Consumption is billed on a utility e. Other benefits of this time sharing style approach are low barriers to entry, shared infrastructure and costs, low management overhead and immediate access to a broad range of applications. Users can generally terminate the contract at any time thereby avoiding return on investment risk and uncertainty and the services are often covered by service level agreements with financial penalties.
According to Nicholas Carr the strategic importance of information technology is diminishing as it becomes standardized and cheaper. He argues that the cloud computing paradigm shift is similar to the displacement of electricity generators by electricity grids early in the 20th century.
History The Cloud is a term with a long history in telephony, which has in the past decade, been adopted as a metaphor for internet based services, with a common depiction in network diagrams as a cloud outline. The underlying concept dates back to when John McCarthy opined that "computation may someday be organized as a public utility"; indeed it shares characteristics with service bureaus which date back to the s.
The term cloud had already come into commercial use in the early s to refer to large ATM networks. By the turn of the 21st century, the term "cloud computing" had started to appear, although most of the focus at this time was on Software as a service SaaS.
In , Salesforce. They applied many technologies of consumer web sites like Google and Yahoo! They also provided the concept of "On demand" and "SaaS" with their real business and successful customers.
The key for SaaS is being customizable by customer alone or with a small amount of help. Flexibility and speed for application development have been drastically welcomed and accepted by business users. It has fine grained user permissions and access privileges.
Map Reduce Map Reduce is a software framework developed at Google in to support parallel computations over large multiple petabyte data sets on clusters of commodity computers.
It is a programming model and an associated implementation for processing and generating large data sets. Many of the real world tasks are expressible in this model. Programs written in this functional style are automatically parallelized and executed on the cloud. This allows programmers without any experience with parallel and distributed systems to easily utilize the resources of a largely distributed system. The user of the MapReduce library expresses the computation as two functions: Map and Reduce.
The MapReduce library groups together all intermediate values associated with the same intermediate key I and passes them to the Reduce function. It merges together these values to form a possibly smaller set of values. Typically just zero or one output value is produced per Reduce invocation.
The intermediate values are supplied to the user's reduce function via an iterator. This allows us to handle lists of values that are too large to fit in memory. MapReduce achieves reliability by parceling out a number of operations on the set of data to each node in the network; each node is expected to report back periodically with completed work and status updates.
If a node falls silent for longer than that interval, the master node records the node as dead, and sends out the node's assigned work to other nodes. Individual operations use atomic operations for naming file outputs as a double check to ensure that there are not parallel conflicting threads running; when files are renamed, it is possible to also copy them to another name in addition to the name of the task allowing for side-effects.
It is designed to provide efficient, reliable access to data using large clusters of commodity hardware. It provides fault tolerance while running on inexpensive commodity hardware, and it delivers high aggregate performance to a large number of clients. Files are divided into chunks of 64 megabytes, which are only extremely rarely overwritten, or shrunk; files are usually appended to or read. Other design decisions select for high data throughputs, even when it comes at the cost of latency.
The nodes are divided into two types: one Master node and a large number of Chunkservers. Chunkservers store the data files, with each individual file broken up into fixed size chunks hence the name of about 64 megabytes, similar to clusters or sectors in regular file systems.
Each chunk is assigned a unique bit label, and logical mappings of files to constituent chunks are maintained. Each chunk is replicated several times throughout the network, with the minimum being three, but even more for files that have high demand or need more redundancy.
The Master server doesn't usually store the actual chunks, but rather all the metadata associated with the chunks, such as the tables mapping the bit labels to chunk locations and the files they make up, the locations of the copies of the chunks, what processes are reading or writing to a particular chunk, or taking a "snapshot" of the chunk pursuant to replicating it usually at the instigation of the Master server, when, due to node failures, the number of copies of a chunk has fallen beneath the set number.
All this metadata is kept current by the Master server periodically receiving updates from each chunk server "Heart-beat messages". Permissions for modifications are handled by a system of time-limited, expiring "leases", where the Master server grants permission to a process for a finite period of time during which no other process will be granted permission by the Master server to modify the chunk. The modified chunkserver, which is always the primary chunk holder, then propagates the changes to the chunkservers with the backup copies.
The changes are not saved until all chunkservers acknowledge, thus guaranteeing the completion and atomicity of the operation. Programs access the chunks by first querying the Master server for the locations of the desired chunks; if the chunks are not being operated on if there are no outstanding leases , the Master replies with the locations, and the program then contacts and receives the data from the chunkserver directly.
As opposed to many file systems, it's not implemented in the kernel of an Operating System but accessed through a library to avoid overhead. Hadoop Hadoop is a framework for running applications on large cluster built of commodity hardware. The Hadoop framework transparently provides applications both reliability and data motion.
Hadoop implements the computation paradigm named MapReduce which was explained above. The application is divided into many small fragments of work, each of which may be executed or re-executed on any node in the cluster. In addition, it provides a distributed file system that stores data on the compute nodes, providing very high aggregate bandwidth across the cluster. Both MapReduce and the distributed file system are designed so that the node failures are automatically handled by the framework.
Hadoop has been implemented making use of Java. All of these components are themselves collected into a JAR which is usually referred to as the job file. To execute a job, it is submitted to a jobTracker and then executed. Tasks in each phase are executed in a fault-tolerant manner. If node s fail in the middle of a computation the tasks assigned to them are re-distributed among the remaining nodes. Since we are using MapReduce, having many map and reduce tasks enables good load balancing and allows failed tasks to be re-run with smaller runtime overhead.
It has a single master server or a jobTracker and several slave servers or taskTrackers, one per node in the cluster. The jobTracker is the point of interaction between the users and the framework. Users submit jobs to the jobTracker, which puts them in a queue of pending jobs and executes them on a first-come first-serve basis. The jobTracker manages the assignment of MapReduce jobs to the taskTrackers. Hadoop is a framework which has received a wide industry adoption.
Hadoop is used along with other cloud computing technologies like the Amazon services so as to make better use of the resources. There are many instances where Hadoop has been used. Amazon makes use of Hadoop for processing millions of sessions which it uses for analytics. This is made use of in a cluster which has about 1 to nodes.
The New York Times made use of Hadoop for large scale image conversions. Yahoo uses Hadoop to support research for advertisement systems and web searching tools. They also use it to do scaling tests to support development of Hadoop. Cloud Computing Services Even though cloud computing is a pretty new technology, there are many companies offering cloud computing services.
Amazon has an expertise in this industry and has a small advantage over the others because of this. Microsoft has good knowledge of the fundamentals of cloud science and is building massive data centers. IBM, the king of business computing and traditional supercomputers, teams up with Google to get a foothold in the clouds. Google is far and away the leader in cloud computing with the company itself built from the ground up on hardware.
It involves four different services. It is designed to make web- scale computing easier for developers. It provides on-demand processing power. Amazon EC2's simple web service interface allows you to obtain and configure capacity with minimal friction. It provides you with complete control of your computing resources and lets you run on Amazon's proven computing environment.
Amazon EC2 reduces the time required to obtain and boot new server instances to minutes, allowing you to quickly scale capacity, both up and down, as your computing requirements change. Amazon EC2 changes the economics of computing by allowing you to pay only for capacity that you actually use. Amazon EC2 presents a true virtual computing environment, allowing you to use web service interfaces to requisition machines for use, load them with your custom application environment, manage your network's access permissions, and run your image using as many or few systems as you desire.
To set up an Amazon EC2 node we have to create an EC2 node configuration which consists of all our applications, libraries, data and associated configuration settings. There are also several stock instances of Amazon AMIs available which can be customized and used. We can then start, terminate and monitor as many instances of the AMI as needed. Amazon EC2 enables you to increase or decrease capacity within minutes.
You can commission one, hundreds or even thousands of server instances simultaneously. Thus the applications can automatically scale itself up and down depending on its needs. You have root access to each one, and you can interact with them as you would any machine. You have the choice of several instance types, allowing you to select a configuration of memory, CPU, and instance storage that is optimal for your application.
Amazon EC2 offers a highly reliable environment where replacement instances can be rapidly and reliably commissioned.
Amazon EC2 provides web service interfaces to configure firewall settings that control network access to and between groups of instances. You will be charged at the end of each month for your EC2 resources actually consumed. So charging will be based on the actual usage of the resources. It offers services for storage of data in the cloud. It provides a high-availability large-store database.
It provides a simple SQL-like language. It has been designed for interactive online use. S3 is storage for the Internet. S3 provides a simple web services interface that can be used to store and retrieve any amount of data, at any time, from anywhere on the web.
It gives any developer access to the same highly scalable, reliable, fast, inexpensive data storage infrastructure that Amazon uses to run its own global network of web sites. Amazon S3 allows write, read and delete of objects containing from 1 byte to 5 gigabytes of data each. The number of objects that you can store is unlimited. Each object is stored in a bucket and retrieved via a unique developer-assigned key.
A bucket can be located anywhere in Europe or the Americas but can be accessed from anywhere. Authentication mechanisms are provided to ensure that the data is kept secure from unauthorized access. Objects can be made private or public, and rights can be granted to specific users for particular objects. Also the S3 service also works with a pay only for what you use method of payment.
By using SQS, developers can simply move data between distributed components of their applications that perform different tasks, without losing messages or requiring each component to be always available. With SQS, developers can create an unlimited number of SQS queues, each of which can send and receive an unlimited number of messages.
It is simple, reliable, secure and scalable. This service works in close conjunction with the Amazon S3 and EC2, collectively providing the ability to store, process and query data sets in the cloud. These services are designed to make web-scale computing easier and more cost-effective to developers.
Traditionally, this type of functionality is accomplished with a clustered relational database, which requires a sizable upfront investment and often requires a DBA to maintain and administer them. Amazon SDB provides all these without the operational complexity.
It requires no schema, automatically indexes your data and provides a simple API for storage and access. App Engine applications are easy to build, easy to maintain, and easy to scale as your traffic and data storage needs grow. You can serve your app using a free domain name on the appspot. You can share your application with the world, or limit access to members of your organization. App Engine costs nothing to get started.
Sign up for a free account, and you can develop and publish your application at no charge and with no obligation. A free account can use up to MB of persistent storage and enough CPU and bandwidth for about 5 million page views a month. Google App Engine makes it easy to build an application that runs reliably, even under heavy load and with large amounts of data.
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Dry: A Memoir Augusten Burroughs. Related Audiobooks Free with a 30 day trial from Scribd. Seminar report on cloud computing 1. Cloud Computing B. Sachikanta Dash Mr. I sincerely thank my thesis guide, prof. Sameer kumar Das for his guidance, help and motivation.
Apart from the subject of our research, I learnt a lot from him, which I erasure, will be useful in different stage of our life. Sachikanta Dash for his review and many helpful comments. Finally, this thesis would not have been possible without the confidence, endurance and support of our family.
Jagan Mohan Bishoyi 4. This new paradigm of computing has an immense potential in it to be used in the field of e-governance and in rural development perspective in the developing country like India.
Guided By: Submitted By: Mr. No: 5. Introduction: Cloud computing is Internet-based computing, whereby shared resources, software, and information are provided to computers and other devices on demand, like the electricity grid. Cloud computing is a paradigm shift following the shift from mainframe to client—server in the early s. Details are abstracted from the users, who no longer have need for expertise in, or control over, the technology infrastructure "in the cloud" that supports them.
What Is Cloud Computing? Cloud computing is Internet based computing where virtual shared servers provide software, infrastructure, platform, devices and other resources and hosting to customers on a pay-as-you-use basis. All information that a digitized system has to offer is provided as a service in the cloud computing model. Users can access these services available on the "Internet cloud" without having any previous know-how on managing the resources involved.
Thus, users can concentrate more on their core business processes rather than spending time and gaining knowledge on resources needed to manage their business processes. Cloud computing customers do not own the physical infrastructure; rather they rent the usage from a third-party provider. This helps them to avoid huge. They consume resources as a service and pay only for resources that they use.
Most cloud computing infrastructures consist of services delivered through common centers and built on servers. Sharing resources amongst can improve, as servers are not unnecessarily left idle, which can reduce costs significantly while increasing the speed of application development.
Architecture: Cloud architecture, the systems architecture of the software systems involved in the delivery of cloud computing, typically involves multiple cloud components communicating with each other over application programming interfaces, usually web services.
Cloud computing sample architecture This resembles the UNIX philosophy of having multiple programs each doing one thing well and working together over universal interfaces.
Complexity is controlled and the resulting systems are more manageable than their monolithic counterparts. The two most significant components of cloud computing architecture are known as the front end and the back end. The front end is the part seen by the client, i. An example of SaaS is a site that allows you to create, save and access documents online. Utility computing: The predecessor of cloud computing, utility computing provides the ability to access storage and virtual servers on demand.
Cloud-based web services: Similar to Saas, web services in the cloud allow you to offer services online, such as credit card processing services, employee payroll processing or viewing an interactive map. An MSP example includes an email virus-scanning service. IaaS infrastructure as a service : IaaS refers to computer infrastructure e. A data center that offers outsourced software and servers may use IaaS for its operations. Types of Cloud Computing: Public cloud: Public clouds are made available to the general public by a service provider who hosts the cloud infrastructure.
Generally, public cloud providers like Amazon AWS, Microsoft and Google own and operate the infrastructure and offer access over the Internet.
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