It may be tempting to shrug cloudcomputing off as a passing fad, but that would be a big mistake. In an increasingly connected world, consumer behavior now penetrates every level of business and consumers have cast their vote: cloud technology is here to stay.
A cloud OS should provide the APIs that enable data and services interoper- ability across distributed cloud environments. Mature OSs provide a rich set of services to the applications so that each application does not have to invent important functions such as VM monitoring, scheduling, security, power management, and memory management. In addition, if APIs are built on open standards, it will help organizations avoid vendor lock-in and thereby creating a more flexible environment. For example, linkages will be required to bridge traditional DCs and public or private cloud environments. The flex- ibility of movement of data or information across these systems demands the OS to provide a secure and consistent foundation to reap the real advan- tages offered by the cloudcomputing environments. Also, the OS needs to make sure the right resources are allocated to the requesting applications. This requirement is even more important in hybrid cloud environments. Therefore, any well-designed cloud environment must have well-defined APIs that allow an application or a service to be plugged into the cloud eas- ily. These interfaces need to be based on open standards to protect customers from being locked into one vendor’s cloud environment.
Enterprises that move their IT to the cloud are likely to encounter challenges such as security, interoperability, and limits on their ability to tailor their ERP to their business processes. The cloud can be a revolutionary technology, especially for small start-ups, but the benefi ts wane for larger enterprises with more complex IT needs [ 10 ]. The cloud model can be truly disruptive if it can reduce the IT opera- tional expenses of enterprises. Traditional utility services provide the same resource to all consumers. Perhaps the biggest difference between the cloudcomputing ser- vice and the traditional utility service models lies in the degree to which the cloud services are uniquely and dynamically confi gured for the needs of each application and class of users [ 12 ]. Cloudcomputing services are built from a common set of building blocks, equivalent to electricity provider turbines, transformers, and distri- bution cables. Cloudcomputing does, however, differ from traditional utilities in several critical respects. Cloud providers compete aggressively with differentiated service offerings, service levels, and technologies. Because traditional ERP is installed on your servers and you actually own the software, you can do with it as you please. You may decide to customize it, integrate it to other software, etc. Although any ERP software will allow you to confi gure and set up the software the way you would like, “Software as a Service” or “SaaS” is generally less fl exible than the traditional ERP in that you can’t completely customize or rewrite the soft- ware. Conversely, since SaaS can’t be customized, it reduces some of the technical diffi culties associated with changing the software. Cloud services can be com- pletely customized to the needs of the largest commercial users. Consequently, we have often referred to cloudcomputing as an “enhanced utility” [ 12 ]. Table 9.2 [ 5 ] shows the E-skills study for information and communications technology (ICT) practitioners conducted by the Danish Technology Institute [ 5 ] that describes the
A health care system is a smart information system that can provide people with some basic health monitoring and physiological index analysis services. It is hard to share with isolated professional medical services such as PACs (picture archiving and communication systems), EHRs (electronic health records), and HISs (hospital information systems) without Internet-based technologies. Not long ago, this kind of system usually was implemented with a traditional MIS (management information system) mode, which is not capable of implementing sufficient health care services on a uniform platform, even though it may exploit several isolated Internet technolo- gies. Currently, cloudcomputing, as an emerging state-of-the-art informa- tion technology (IT) platform, can provide economical and on-demand services for customers. It provides characteristics of high performance and transparent features to end users that can fulfill the flexibility and scalabil- ity of service-oriented systems. Such a system can meet the infrastructure demand for the health care system. With the rapid progress of cloud capac- ity, increasing applications and services are provided as anything as a ser- vice (XaaS) mode (e.g., security as a service, testing as a service, database as a service, and even everything as a service)  . Google Docs, Amazon S3
The ﬁ rst step is the development phase. An App Provider implements a service following the guidelines described in chapter “ Empirical Qualitative Analysis of the Current CloudComputing Market for Logistics ” . The hard requirements are that RESTful interfaces and service calls must be implemented. Additionally, the BO- stack including BODs and Mini-BODS, of the Logistics Mall environment must also be used for communication and the BO Instance Repository must be used for storage of processed information and data shared by different apps of a process. Furthermore, an end-user and the service App has to contain the workbasket mechanism. Additionally, points are just suggestions to the provider, like the usage of the Java enterprise stack. The developers are free to choose their own pro- gramming language, but must make sure that their apps are executable within the cloud environment. This is ensured and veri ﬁ ed during the next phase of the Logistics Mall App Life-Cycle. The development phase ﬁ nishes with submitting the created App and integrating it into the Logistics Mall Marketplace (MMP). For the integration the app ’ s description, its price model and the date of availability are registered in the MMP. A Business App is only available until the speci ﬁ ed date. But ﬁ rst of all the App is not visible or purchasable for any customer as long as the Logistics Mall Veri ﬁ cation has not been successfully completed.
John McCarthy was a visionary in computer science; in the early 1960s he formulated the idea that computation may be organized as a public utility, like water and electricity. In 1992 Gordon Bell was invited to and delivered an address at a conference on parallel computations with the provocative title Massively parallel computers: why not parallel computers for the masses? ; he argued that one-of-a- kind systems are not only expensive to build, but the cost of rewriting applications for them is prohibitive. Google Inc. was founded by Page and Brin, two graduate students in computer science at Stanford University; in 1998 the company was incorporated in California after receiving a contribution of $100, 000 from the co-founder and chief hardware designer of Sun Microsystems, Andy Bechtolsheim. Amazon EC2 was initially released as a limited public beta cloudcomputing service on August 25, 2006. The system was developed by a team from Cape Town, South Africa. In October 2008 Microsoft announced the Windows Azure platform; in June 2010 the platform became commercially available. iCloud, a cloud storage and cloudcomputing service from Apple Inc., stores content such as music, photos, calendars, and documents and allows users to access it from Apple devices. The system was announced on June 6, 2011. In 2012 the Oracle Cloud was announced (see www.oracle.com/us/ corporate/features/oracle-cloud/index.html )
Relational databases are great for online transaction processing (OLTP) activities because they guarantee that transactions are processed successfully in order for the data to get stored in the database. In addition, relational databases have superior security features and a powerful querying engine. Over the last several years, NoSQL databases have soared in popularity mainly due to two reasons: the increasing amount of data being stored and access to elastic cloudcomputing resources. Disk solutions have become much cheaper and faster, which has led to companies storing more data than ever before. It is not uncommon for a company to have petabytes of data in this day and age. Normally, large amounts of data like this are used to perform analytics, data mining, pattern recognition, machine learning, and other tasks. Companies can leverage the cloud to provision many servers to distribute workloads across many nodes to speed up the analysis and then deprovision all of the servers when the analysis is finished.
Hadoop MapReduce and the LexisNexis HPCC platform are both scalable archi- tectures directed towards data-intensive computing solutions. Each of these system platforms has strengths and weaknesses and their overall effectiveness for any appli- cation problem or domain is subjective in nature and can only be determined through careful evaluation of application requirements versus the capabilities of the solution. Hadoop is an open source platform which increases its ﬂexibility and adaptability to many problem domains since new capabilities can be readily added by users adopt- ing this technology. However, as with other open source platforms, reliability and support can become issues when many different users are contributing new code and changes to the system. Hadoop has found favor with many large Web-oriented companies including Yahoo!, Facebook, and others where data-intensive computing capabilities are critical to the success of their business. Amazon has implemented new cloudcomputing services using Hadoop as part of its EC2 called Amazon Elastic MapReduce. A company called Cloudera was recently formed to provide training, support and consulting services to the Hadoop user community and to pro- vide packaged and tested releases which can be used in the Amazon environment. Although many different application tools have been built on top of the Hadoop platform like Pig, HBase, Hive, etc., these tools tend not to be well-integrated offer- ing different command shells, languages, and operating characteristics that make it more difﬁcult to combine capabilities in an effective manner.
In other cases, the loss of control of where your virtual IT infrastructure resides could open the way to other problematic situations. More precisely, the geographical location of a datacenter gen- erally determines the regulations that are applied to management of digital information. As a result, according to the specific location of data, some sensitive information can be made accessible to government agencies or even considered outside the law if processed with specific cryptographic techniques. For example, the USA PATRIOT Act 5 provides its government and other agencies with virtually limitless powers to access information, including that belonging to any company that stores information in the U.S. territory. Finally, existing enterprises that have large computing infra- structures or large installed bases of software do not simply want to switch to public clouds, but they use the existing IT resources and optimize their revenue. All these aspects make the use of a public computing infrastructure not always possible. Yet the general idea supported by the cloudcomputing vision can still be attractive. More specifically, having an infrastructure able to deliver IT services on demand can still be a winning solution, even when implemented within the private premises of an institution. This idea led to the diffusion of private clouds, which are similar to pub- lic clouds, but their resource-provisioning model is limited within the boundaries of an organization.
Cloudcomputing is one of today’s most attractive technology areas due to its many advantages like accessed IT resources with major cost / cash and flexibility. Various companies around the world adapting cloudcomputing as a means to increasing efficiency and reducing cost of their IT services. In this research paper efforts have been made to analyze the bility in business information system. uting. The main challenges are security and because all essential services are generally outsourced to a third party. The outsourcing makes it harder to rity and privacy, support data and service availability etc. Using public cloud model only in the business is very risky because of its security reasons and using private cloud only will not solve our purpose because in that case we will not be able to use advantages of public cloud model. To solve these security problems in business information system we can use hybrid cloudcomputing model where we can use advantages of public cloud and security of private cloud, in itive data of the company in the private storage cloud and less sensitive data in public storage cloud. This research paper focused upon the security problems in business information system. Research suggests a hybrid cloudcomputing model where converging advantages of public cloud and security of private cloud can be used.
In this section, authors present the model-driven software development approach for service-oriented integration solutions for SOA. As is evident, the technologies are constantly evolving. The technology evolution has serious impact in B2B context as it is more difficult to control the impact of change when external partners are involved. Rather than directly developing the cloud software services using available technologies, modeling them at a higher level of abstraction will decouple them from the undesired effects of technology change and enhance their longevity. An MDA based development of cloud SaaS (application) will enable defining these services in a technology- independent manner and will play a significant role in improving the quality of cloud software services, making them more robust, flexible and agile . Encapsulating business logic in a manner that is independent of the technical mechanisms will formally capture the essence of the applications; and will also make it possible to reuse them in a variety of contexts . Web service is a fundamental technology underlying the cloudcomputing paradigm; and is evolving too. Based on MDA approach, a formal, semantically rich platform independent model of the Web service capturing the information and functionality provided by it, may be defined which may then be used to generate the artifacts that support the service over some other set of technologies.
A critical feature to integrate in cloudcomputing design is to provide cloud customers with the aptitude to upload and use their own guest OS images which can be managed, prepared, and controlled by themselves. By taking advantage of such functionality, customers have increased control and we can reduce scenarios where the customer cannot choose what to run in the cloud. The number of cloud providers providing this kind of functionally is inadequate nowadays. To date, uploading such guest OS images in an encrypted fashion is not being provided by cloud providers at all. The security analysis presented in previous sections has shown that it is essential to encrypt the guest OS image from the very beginning even before uploading the guest OS to the cloud in order to ensure that neither the end users nor the cloud provider can have access to the OS when the VMs are powered off.
Virtualization is a technique in which a complete installation of one machine is run on another. As result, one virtual machine can be obtained where all software are running. This type of way also helps to run unique applications and different types of operating systems. Virtualization is very important for CloudComputing. All the services can be accessed through Virtualization from the cloud, for example the remote datacenter may be delivering the services in a virtualized format. Virtualization is advantageous due to several purposes:
This book comprehensively debates on the emergence of mobile cloudcomputing from cloudcomputing models. Various technological and architectural advancements in mobile and cloudcomputing have been reported. It has meticulously explored the design and architecture of computational offloading solutions in cloud and mobile cloudcomputing domains to enrich mobile user experience. Furthermore, to optimize mobile power consumption, existing solutions and policies toward green mobile computing, green cloudcomputing, green mobile networking, and green mobile cloudcomputing are briefly discussed. The book also presents numerous cloud and mobile resource allo- cation and management schemes to efficiently manage existing resources (hardware and software). Recently, integrated networks (e.g., WSN, VANET, MANET) have sig- nificantly helped mobile users to enjoy a suite of services. The book discusses existing architecture, opportunities, and challenges, while integrating mobile cloud comput- ing with existing network technologies such as sensor and vehicular networks. It also briefly expounds on various security and privacy concerns, such as application security, authentication security, data security, and intrusion detection, in the mobile cloud com- puting domain. The business aspects of mobile cloudcomputing models in terms of resource pricing models, cooperation models, and revenue sharing among cloud pro- viders are also presented in the book. To highlight the standings of mobile cloud comput- ing, various well-known, real-world applications supported by mobile cloudcomputing models are discussed. For example, the demands and issues while deploying resource- intensive applications, including face recognition, route tracking, traffic management, and mobile learning, are discussed. This book concludes with various future research directions in the mobile cloudcomputing domain to improve the strength of mobile cloudcomputing and to enrich mobile user experience.
It’s also critical to avoid thinking of cloudcomputing as a drive to reduce your operational headcount or costs. Although lowering costs is a valid business goal, it’s also a way of taking a lot of the day-to-day repetitive work out of your operations through automation. Automation enables IT staff to do something that adds benefi t to the business, allowing them more time to focus on projects rather than business as usual. This may sound like a well-used truism that is trotted out by management, and it is often overused to justify technology spending. However, if you think about the way the IT industry is moving—increasingly making use of lower-cost headcount to perform operational tasks, often through offshoring or outsourcing—you should see an opportunity to implement cloudcomputing as a way of developing your career and mov- ing up the stack to stay relevant in a changing world rather than being left to compete with a cheaper workforce.
In 1997, Professor Ramnath Chellappa of Emory University, defined cloudcomputing for the first time while a faculty member at the University of South California, as an important new “computing paradigm where the boundaries of computing will be determined by economic rationale rather than technical limits alone.” Even though the international IT literature and media have come forward since then with a large number of definitions, models and architectures for cloudcomputing, autonomic and utility computing were the foundations of what the community commonly referred to as “cloudcomputing”. In the early 2000s, companies started rapidly adopting this concept upon the realization that cloudcomputing could benefit both the Providers as well as the Consumers of services. Businesses started delivering computing functionality via the Internet, enterprise- level applications, web-based retail services, document-sharing capabilities and fully-hosted IT platforms, to mention only a few cloudcomputing use cases of the 2000s. The latest widespread adoption of virtualization and of service- oriented architecture (SOA) promulgated cloudcomputing as a fundamental and increasingly important part of any delivery and critical-mission strategy, enabling existing and new products and services to be offered and consumed more efficiently, conveniently and securely. Not surprisingly, cloudcomputing became one of the hottest trends in the IT armory, with a unique and complementary set of properties, such as elasticity, resiliency, rapid provisioning, and multi-tenancy.
In simplistic terms, cloudcomputing can be broken down to a browser based application that is hosted on a remote server. To the average user, that is all he or she really needs to know about cloudcomputing. But there is a lot more to it than just that. What cloudcomputing really represents is huge: it’s a way for small organizations to compete with much larger ones, it’s a way to save a lot of money and it’s a way to utilize energy efficiency in operations. Cloudcomputing as it relates to Internet technology is all around us. When we access our email, when we search for information, we are using the power of processing technology that exists at a distant location without us knowing about it. In fact, even the most basic computer applications require a network connection these days to do simple tasks. As an example, the thesaurus function within Microsoft Word (Jeff Kaplan, 16/08/2008) requires a network connection to look up alternative words. In effect, the cloud provides networked users with an extension of their own machine. As long as a user is connected to the internet, the power of cloudcomputing comes into play and many benefits can be reaped. One example would be processing power. Applications can be run on the fly from a terminal machine when processing power is not a concern; the only thing that users need to worry about would be their bandwidth connection and its reliability on the network. One of the biggest benefits would be storage. Server farms possess massive amounts of storage. An example of this would be the free email services that are available on the web. Often times these email services offer a large amount of storage to their users because it is cheap for them to do so by using the available space that is in the cloud. This is a characteristic that is to be noted, because the prevalence of cheap storage on server farms will benefit users immensely in the future. One major benefit of this is data loss prevention. With the cloud managing data across a multitude of networked computers the chance of data loss becomes less likely and is indeed a feature that cloudcomputing companies tout to their potential clients.
Flexibility, Reliability and More Storage - The data store on cloud are almost unlimited bandwidth and storage space and Remote cloud servers offer it. It’s easier to makes data backup and disaster recovery because the cloud data can be store a copy of these data at multiple redundant sites on the cloud provider’s network. During these process no need to spend large money so it less expensive. Cloudcomputing has increased the storage or Cloudcomputing provides a large storage, so we will not have to worry about the end of the store at the hard drive now.
Overview of cloudcomputing: Meaning of the terms cloud and cloudcomputing-cloud based service offerings-grid computing vs cloudcomputing-benefits of cloud model-limitations- legal issues-key characteristics of cloudcomputing-challenges for the cloud-The evolution of cloudcomputing.