of resources within Clouds. They have also presented a vision for the creation of global Cloud exchange for trading services. They have discussed some representative platforms for Cloudcomputing covering the state-of-the-art. In particular, authors have presented various Cloud efforts in practice from the market oriented perspective to reveal its emerging potential for the creation of third-party services to enable the successful adoption of Cloudcomputing, such as meta-negotiation infrastructure for global Cloud exchanges and provide high performance content delivery via `Storage Clouds'.
Cloudcomputing encourages libraries and their users to participate in a network and community of libraries by enabling them to reuse information and socialize around information. The Cloudcomputing techniques and methods applied to libraries, not only can improve the quality of services and utilization of resources, but also can make more extensive use of cloudcomputing to our work life (Bhattacharjee and Purkayastha, 2013). Cloudcomputing simplifies management of collective resources use, remote access for multiple user selection, providing the necessary tools at some point of the training process. Collections of resources may be accessed through "Software as Services (SaaS)" (Deka and Chandra, 2016). When library systems are deployed as open cloud solutions then the library community itself can step up to create extensions to their core services and more importantly share them throughout the community using cloud solutions. Libraries can get out of the business of technology and focus on collection building, patron services and innovation. Servers can be decommissioned and no longer require replacement every five years (or less). Staff no longer has to maintain the complex software stack necessary to run local systems and worry about compatibility of the stack during upgrades. Instead technical skills can be re-deployed for extending cloud services into their environment and their environment into other cloud services (Matt, 2010).
As far as the end user is concerned, it does not matter how the service is provided. Cloudcomputing services are scalable, via dynamic provisioning of resources on a fine grained, self-service basis near real-time, without users having to engineer for peak loads. This requirement particularly manifests in Mobile CloudComputing due to the intrinsic limitations of mobile devices. For example, the iPhone 4s is equipped with 800 MHz CPU, 512 MB RAM allowing about 8 hrs of talk time and 14.4 Mbps speed on HSDPA 4G network .Compared to today‟s PC and server platforms, these devices still cannot run compute-intensive applications. Thus, an elastic application model is required to solve the fundamental processing problem.
CloudComputing is seen as a technology that uses the internet and central server to maintain data, software and applications.  posit that, cloudcomputing enables task distribution in large number by collecting large amount of information stored in personal computer and other tools by integrating and putting them on public cloud for serving users. Cloudcomputing can also be seen as service model for computing resources that can be accessed in a flexible, elastic, on demand way with low management effort. It helps to integrate large quantity of information resources stored in Personal Computers, mobile phones and other equipments by putting them on the public cloud for serving users.
Today world cloudcomputing is very vital role play in technology fields, we know the recent growth of cloudcomputing has expressed its existing in possibility to reshape the current information technology either field software and new deigned hardware. As we say that cloudcomputing is a technology that expends the internet and central remote servers holding data and application as well. So much benefits, cloudcomputing extends users a more flexible and easy way to find calculation and storage resources on the requirement. The Cloudcomputing have been also manifested by the emergence of Mobile cloudcomputing. We access any information from mobile ends. Mobile devices such as smart phone, tablet, etc. are more and more getting an essential role play in human life. Mobile users collect various services go through different mobile applications, like iPhone apps, google apps, game apps, etc.; those services run on devices. The rapid development of mobile computing gets a very powerful in the growth of IT technology as well as commerce and industry fields . In current and future the mobile cloudcomputing will be a main division of the development of cloudcomputing. Mobile cloudcomputing trusts on a machine-to-machine computing model, mobile device contract work out their computing chores to the cloud . Mobile user wants the internet without the limitation of fixed equipments. Mobile cloudcomputing offers ‘any time anywhere‘ concept and provides mobility services to the user. The requirement for the mobile application services is also increasing day to day, which demand much more resources to be allowed in to make the user experience more improve and easily available services.
The researcher sought to understand the age range of his respondents and educational levels in relation to acceptability of cloudcomputing. Head of the institutions libraries who were interviewed were not asked about their age and highest educational qualification because they are not directly involved with the users. Therefore, age is not relevant to the study and as a prerequisite for appointment to head an academic library, one of the requirement is having a Doctor of philosophy in related discipline. Details in table 4.1 shows that most of the librarians representing 31.1 percent (n=28 of 90) of respondents are in the age bracket of 26-30years, 25.6 percent (n=23 of 90) respondents are within the age bracket of 30-35years and 24.4 percent (n=22 of 90) respondents in the age bracket of 36 and above. The age brackets of 21- 25 represent 11 percent of the total number of respondents (n=12.2 of 90). The least age bracket of the employees are less than 21 years with 6.7 percent (n=6 of 90). This is important age category because it constituted the very active working population. Previous studies by Harvey (2017) established that the young adults were classified as aged between 21 to 45 years. In addition, young adults are more sensitive towards acceptance of technological innovations than those within 46 years and above Pepra-mensah (2010).
Soft modularity presents a number of challenges. It increases the difficulty of debugging; for example, a call to a module with an infinite loop will never return. There could be naming conflicts and wrong context specifications. The caller and the callee are in the same address space and may misuse the stack (e.g., the callee may use registers that the caller has not saved on the stack, and so on). A strongly typed language may enforce soft modularity by ensuring type safety at compile or at run time, it may reject operations or function classes that disregard the data types, or it may not allow class instances to have their classes altered. Soft modularity may be affected by errors in the run-time system, errors in the compiler, or by the fact that different modules are written in different programming languages. The Client-Server Paradigm. The ubiquitous client-server paradigm is based on enforced modularity; this means that the modules are forced to interact only by sending and receiving messages. This paradigm leads to a more robust design where the clients and the servers are independent modules and may fail separately. Moreover, the servers are stateless; they do not have to maintain state information. The server may fail and then come up without the clients being affected or even noticing the failure of the server. The system is more robust since it does not allow errors to propagate. Enforced modularity makes an attack less likely because it is difficult for an intruder to guess the format of the messages or the sequence numbers of segments when messages are transported by Transport Control Protocol (TCP).
“E-learning,” which is based on the Internet technology, provides a new choice different from the past—the limitation of time and space—and learn- ers require staying together in a regulation time, for the comportment of learning. “E-learning” is a process of studying through the digital media resources for learners, and these media include the Internet, computers, satellite broadcasts, tapes, videos, interactive TVs, and CDs . Recently, the technology of the network service in software and hardware becomes more mature, and the “e-learning” industry becomes a main promoter of the movement, which says: “lives old, learns old.” In response to this concept, the distance learning pattern combined with the computer technology is get- ting more and more attention now; there are too many instances about the combine computer and multimedia technology to enumerate. But, with the development of wireless network technology, mobile networks such as WiFi, 3G, and WiMAX are getting universal; thus, the volume of mobile device is smaller than before. Therefore, the use of mobile devices such as smart- phone is becoming the trend now (Laisheng and Zhengxia 2011). But there are many platforms for mobile devices; if we design different platforms for each application, it will face many constraints and limits, and waste much time on maintenance and series of tests for different devices. With the devel- opment of Web service applications, many programs transform the execu- tion environment from the desktop into the Web world, for example, e-mail service that has been used many years through the Web service; users can arrange and back up their contact list and mails, do not need to remember the settings about POP3/SMTP (Pocatilu and Boja 2009), and even reinstall your computer system, which causes loss of the mails saved in the computer.
Virtualisation technology appeared several years ago; it comes in many types, all focusing on control and usage schemes that emphasise efficiency. This efficiency is seen as a single terminal being able to run multiple machines or a single task run- ning over multiple computers via idle computing power. Adoption within data cen- tres and adoption by service providers is increasing rapidly and encompasses different proprietary virtualisation technologies. Again, the lack of standardisation poses a barrier to an open standards cloud that is interoperable with other clouds, and a broad array of computing and information resources is fundamentally imple- mentable. As the availability of requested resources by users poses a crucial param- eter for the adequacy of the service provided, one of the major deployments of the cloud application paradigm is the virtual data centres (VDC), utilised by service providers  by enabling a virtual infrastructure (Fig. 6.6) in a distributed manner in various remotely hosted locations worldwide to provide accessibility  and backup services and ensure reliability in case of a potential single site failure. In the case of resource saturation or resource dismissal, where a certain location-based resource cannot be accessed, the VDC claims the resource in order to enable avail- ability to potential requests/users. Additionally, these services with globally assigned operations require faster response time by distributing workload requests to multiple VCDs using certain scheduling and load-balancing methodologies. Therefore, as an optimal approach to resource availability, a k-rank model  can be applied in order to rank the requests and resources and create outsourcing ‘connectivity’ to potential request.
Enterprises often don’t have the required expertise to build cloud-based solutions. The average medium-to-large company that has been in business for more than a few years typically has a collection of applications and services spanning multiple eras of application architecture from mainframe to client-server to commercial-off the-shelf and more. The majority of the skills internally are specialized around these different architectures. Often the system administrators and security experts have spent a lifetime working on physical hardware or on-premises virtualization. Cloud architectures are loosely coupled and stateless, which is not how most legacy applications have been built over the years. Many cloud initiatives require integrating with multiple cloud-based solutions from other vendors, partners, and customers. The methods used to test and deploy cloud-based solutions may be radically different and more agile than what companies are accustomed to in their legacy environments. Companies making a move to the cloud should realize that there is more to it than simply deploying or paying for software from a cloud vendor. There are significant changes from an architectural, business process, and people perspective. Often, the skills required to do it right do not exist within the enterprise.
Thus providing Infrastructure as a Service essentially means that the cloud provider assembles the building blocks for providing these services, including the computing resources hardware, networking hardware and storage hardware. These resources are exposed to the consumers through a request management system which in turn is integrated with an automated provisioning layer. The cloud system also needs to meter and bill the customer on various chargeback models. The concept of virtualization enables the provider to leverage and pool resources in a multi-tenant model. Thus, the features provided by virtualization resource pooling, combined with modern clustering infrastructure, enable efficient use IT resources to provide high availability and scalability, increase agility, optimize utilization, and provide a multi-tenancy model.
There is the organizer to make a summary of all RSSs of all users by filtering out duplicated ones, and then the collector will fetch the RSS updates and the original content from the feed content SPs. In particular, for each active subscribing user, the cloud virtualizes a smart agent called subFC to monitor the user RSS requirement, as well as the wireless link quality, and then to decide how to request the RSS content and how to push content to the mobile user. Due to the elastic computation of dynamic resource allocation of cloudcomputing, FCs with subFCs is working with optimal performance adaptively to the user demands.
Above all, this book emphasizes problem solving through cloudcomputing. At times you might face a simple problem and need to know only a simple trick. Other times you might be on the wrong track and need some background information to get oriented. Still other times, you might face a bigger problem and need direction and a plan. You will find all of these in this book. We provide a short description of the overall structure of a cloud here, to give the reader an intuitive feel for what a cloud is. Most readers will have some experience with virtualization. Using virtualization tools, you can create a virtual machine with the operating system install soft- ware, make your own customizations to the virtual machine, use it to do some work, save a snap- shot to a CD, and then shut down the virtual machine. An Infrastructure as a Service (IaaS) cloud takes this to another level and offers additional convenience and capability.
The past decades have witnessed the success of centralized comput- ing infrastructures in many application domains. Then, the emergence of the Internet brought numerous users of remote applications based on the technologies of distributed computing. Research in distributed computing gave birth to the development of grid computing. Though grid is based on distributed computing, the conceptual basis for grid is somewhat different. Computing with grid enabled researchers to do computationally intensive tasks by using limited infrastructure that was available with them and with the support of high processing power that could be provided by any third party, and thus allowing the researchers to use grid computing, which was one of the first attempts to provide computing resources to users on payment basis. This technology indeed became popular and is being used even now. An associated problem with grid technology was that it could only be used by a certain group of people and it was not open to the public. Cloud com- puting in simple terms is further extension and variation of grid computing, in which a market-oriented aspect is added. Though there are several other important technical differences, this is one of the major differences between grid and cloud. Thus came cloudcomputing, which is now being used as a public utility computing software and is accessible by almost every person through the Internet. Apart from this, there are several other properties that make cloud popular and unique. In cloud, the resources are metered, and a user pays according to the usage. Cloud can also support a continuously varying user demands without affecting the performance, and it is always available for use without any restrictions. The users can access cloud from any device, thus reaching a wider range of people.
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
Only few academic solutions exist, but the growing interest in the subject opti- mization of Business Processes with connection to the cloud can be ascertained. They are primarily focused on innovative ideas, which are realized in the context of a project and eventually lead to a ﬁ nished product on the market. The scienti ﬁ c sector provides the following solutions or un ﬁ nished projects aside from the LPD. The Institute of Databases and Information Systems from the University of Ulm presented their Cloud based BPM Solution clavii BPM Cloud  on the CeBIT 2013. With the help of this solution, every user can work with personalized Process views and make changes to the model. Those changes are immediately published to all other users which are affected by the changes. The personalization is achieved by abstraction of the Business Processes (depending on the ﬁ eld of duty, the necessary activities are shown and the other activities are hidden or grouped). The complexity of Business Processes can be reduced through the selection of various views. Furthermore, it is possible to change a graph based process visualization (BPMN 2.0) in a form based, a textual to an ADEPT 24 -visualization. The clavii BPM Cloud facilitates case based Process changes at runtime. The solution offers a Process modeler and Process execution is planned. The solution emerged from the science project proView  from the University of Ulm, where the concepts of the Process abstraction were taken from .
Bob Evans, senior vice president at Oracle, further wrote some revealing facts in his blog post at Forbes, clearing away all doubts people may have had in their minds. You may like to consider some interesting facts in this regard. Almost eight years ago, when cloud terms were not yet established, Oracle started developing a new generation of application suites (called Fusion Applications) designed for all modes of cloud deployment. Oracle Database 12c, which was released just recently, supports the cloud deployment framework of major data centers today and is the outcome of development efforts of the past few years. Oracle’s software as a service (SaaS) revenue has already exceeded the $1 billion mark, and it is the only company today to offer all levels of cloud services, such as SaaS, platform as a service (PaaS), and infrastructure as a service (IaaS). Oracle has helped over 10,000 customers to reap the beneﬁts of the cloud infrastructure and now supports over 25,000 users globally. One may argue that this could not have been possible if Larry Ellison hadn’t appreciated cloudcomputing. Sure, we may understand the dilemma he must have faced as an innovator when these emerging technologies were creating disruption in the business (www.forbes.com/sites/oracle/2013/01/18/oracle-cloud-10000- customers-and-25-million-users/).
CloudComputing is a set of IT Services that are provided to a customer over a network and these services are delivered by third party provider who owns the infrastructure. The central data storage is the key facility of the cloudcomputing it is of prominent importance to provide the security. The art and science of concealing the messages to introduce secrecy in information security is recognized as cryptography. Security goals of data cover three points namely: Availability, Confidentiality, and Integrity. The proposed mechanism choose symmetric cryptosystem as solution as it has the speed and computational efficiency to handle encryption of large volumes of data. In symmetric cryptosystems, the longer the key length, the stronger the encryption. The AES algorithm is most frequently used encryption algorithm. This algorithm is based on several substitutions, permutations and linear transformations, each executed on data blocks of 16 byte whereas no possible attack against AES algorithm exists. Therefore, AES algorithm remains the preferred encryption standard for governments, banks and high security systems around the world. In this paper, a new mechanism is proposed to protect the healthcare data in the cloud using AES algorithm. The proposed system has a double layer protection in which the Electronic Health Records are stored in the cloud. In one layer the Encryption or Decryption will be done and in the other layer the Splitting or Merging of the ciphertext will be done. Thus, data security can be improved in cloudcomputing. As the proposed system is in the development stage, the actual results will be shared in future publication.
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.
CloudComputing is a technology that uses the internet and central remote servers to maintain data and applications. Cloudcomputing allows consumers and businesses to use applications without installation and access their personal files at any computer with internet access. This technology allows for much more efficient computing by centralizing data storage, processing and bandwidth. The continuous increase in the volume and detail of data captured by organizations, such as the rise of social media, Internet of Things (IoT), and multimedia, has produced an overwhelming flow of data in either structured or unstructured format. Data creation is occurring at a record rate , referred to herein as big data, and has emerged as a widely recognized trend. Big data is eliciting attention from the academia, government, and industry. Bigdata are characterized by three aspects:(a) data are numerous