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 cloud computing 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 ]. Cloud computing services are built from a common set of building blocks, equivalent to electricity provider turbines, transformers, and distri- bution cables. Cloud computing 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 cloud computing 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
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The cloud is not only an enabler for enterprises but it is a great enabler for cyber-criminals as well for two reasons. First, cloud computing is still very immature and lacking standards at this time. There are not a lot of engineers with years of hands-on experience securing applications in the cloud. The end result is that many cloud services are being deployed by today’s corporations without the necessary security and controls and are very vulnerable to all kinds of attacks and breaches. The second reason why the cloud is an enabler for cyber-criminals is that the cloud vendors are a huge target because they house compute resources and data for a large number of companies. The cloud providers typically provide high levels of perimeter security, but it is up to the companies deploying their services to build the appropriate level of application security. For example, an Infrastructure as a Service (IaaS) cloud provider like Amazon Web Services (AWS) has world-class secure data centers, white papers on how to build highly secure services on its platform, and provides a suite of application programming interfaces (APIs), making it easier to design for security. However, it is up to the architects building the software on AWS to encrypt the data, manage the keys, implement good password policies, and so forth.
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Many definitions have been introduced for the last years to define exactly what “cloud Computing” are: According to Buyya et al.  have defined it as follows: “Cloud is a parallel and distributed computing system consisting of a collection of interconnected and virtualized computers that are dynamically provisioned and presented as one or more unified computing resources based on service- level agreements (SLA) established through negotiation between the service provider and consumers.” The National Institute of Standards and Technology (NIST)  characterizes cloud computing as “a pay-per-use model for enabling available, convenient, on-demand network access to a shared pool of configurable computing resources (e.g. networks, servers, storage, applications, services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.” Vaquero et al.  have stated “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-per-use model in which guarantees are offered by the Infrastructure Provider by means of customized Service Level Agreements.” definition proposed by the U.S. National Institute of Standards and Technology (NIST):”Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction”.
As an emerging state-of-the-art technology, cloud computing has been applied to an extensive range of real-life situations. Health care service is one of such important application fields. We developed a ubiquitous health care system, named HCloud, after comprehensive evaluation of requirements of health care applications. It is provided based on a cloud computing plat- form with characteristics of loose coupling algorithm modules and powerful parallel computing capabilities that compute the details of those indicators for the purpose of preventive health care service. First, raw physiological sig- nals are collected from the body sensors by wired or wireless connections and then transmitted through a gateway to the cloud platform, where storage and analysis of the health status are performed through data-mining tech- nologies. Last, results and suggestions can be fed back to the users instantly for implementing personalized services that are delivered via a heteroge- neous network. The proposed system can support huge physiological data storage; process heterogeneous data for various health care applications, such as automated electrocardiogram (ECG) analysis; and provide an early warn- ing mechanism for chronic diseases. The architecture of the HCloud platform for physiological data storage, computing, data mining, and feature selections is described. Also, an online analysis scheme combined with a Map-Reduce parallel framework is designed to improve the platform’s capabilities. Performance evaluation based on testing and experiments under various conditions have demonstrated the effectiveness and usability of this system.
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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 cloud computing 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.
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Several different surveys on cloud computing in the logistics sector have been conducted in the past few months and published as studies. One of them was an online survey conducted by the software provider INFORM GmbH which showed that 68.3 % of the surveyed companies are ready right now to use cloud computing for logistics tasks — only 12.7 % have actually done it. The reasons for this are a lack of familiarity with the topic (29.5 %) and the security concerns mentioned by almost half of the surveyed companies. The possibility of having to rely on an external service provider was a barrier to using cloud technology for 13 % of the surveyed companies. The lack of industry-speci ﬁ c solutions was an obstacle for another 5 %. There seems to be a wide range of reasons. Flexible access (38 %), reduction in operating costs (25 %), faster implementation times for business processes (18 %), platform independence (12 %), and access to IT resources that would not be possible without cloud computing (7 %) were identi ﬁ ed as the ben- e ﬁ ts. According to the respondents, cloud computing solutions can be used for the communication between vendors and customers, controlling suppliers, and man- aging supply chain events. 25
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This book comprehensively debates on the emergence of mobile cloud computing from cloud computing models. Various technological and architectural advancements in mobile and cloud computing have been reported. It has meticulously explored the design and architecture of computational offloading solutions in cloud and mobile cloud computing domains to enrich mobile user experience. Furthermore, to optimize mobile power consumption, existing solutions and policies toward green mobile computing, green cloud computing, green mobile networking, and green mobile cloud computing 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 cloud computing 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 cloud computing 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 cloud computing domain to improve the strength of mobile cloud computing and to enrich mobile user experience.
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Virtualization has been used successfully since the late 1950s. A virtual memory based on paging was first implemented on the Atlas computer at the University of Manchester in the United Kingdom in 1959. In a cloud computing environment a VMM runs on the physical hardware and exports hardware- level abstractions to one or more guest operating systems. A guest OS interacts with the virtual hardware in the same way it would interact with the physical hardware, but under the watchful eye of the VMM which traps all privileged operations and mediates the interactions of the guest OS with the hardware. For example, a VMM can control I/O operations to two virtual disks implemented as two different sets of tracks on a physical disk. New services can be added without the need to modify an operating system. User convenience is a necessary condition for the success of the utility computing paradigms. One of the multiple facets of user convenience is the ability to run remotely using the system software and libraries required by the application. User convenience is a major advantage of a VM architecture over a traditional operating system. For example, a user of the Amazon Web Services (AWS) could submit an Amazon Machine Image (AMI) containing the applications, libraries, data, and associated configuration settings. The user could choose the operating system for the application, then start, terminate, and monitor as many instances of the AMI as needed, using the Web Service APIs and the performance monitoring and management tools provided by the AWS.
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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 cloud computing 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.
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Cloud computing isn’t network computing. With network computing, applications are hosted on a single company’s server and accessed over the company’s network. Cloud computing is a lot bigger than that. It encompasses multiple companies, multiple servers, and multiple networks .Plus, unlike network computing, cloud services and storage are accessible from anywhere in the world over an internet connection; with network computing, access is over the company’s network only. For our purposes, the cloud is a large group of interconnected computers. These computers can be personal computers or network servers; they can be public or private. For example, Google hosts a cloud that consists of both smallish PCs and larger servers. Google’s cloud is a private one (that is, Google owns it) that is publicly accessible (by Google's users).
It is foreseen that cloud computing could become a disruptive technology for mobile multimedia applications and services . In order to meet mul- timedia’s QoS requirements in cloud computing for multimedia services over the Internet and mobile wireless networks, Zhu et al.  proposed a multimedia cloud computing framework that leverages cloud computing to provide multimedia applications and services over the Internet. The prin- cipal conceptual architecture is shown in Figure 1.5. Zhu et al. addressed multimedia cloud computing from multimedia-aware cloud (media cloud) and cloud-aware multimedia (cloud media) perspectives. The media cloud (Figure 1.5a) focuses on how a cloud can perform distributed multimedia processing and storage and QoS provisioning for multimedia services. In a media cloud, the storage, CPU, and GPU are presented at the edge (i.e., MEC) to provide distributed parallel processing and QoS adaptation for various types of devices. The MEC stores, processes, and transmits media data at the edge, thus achieving a shorter delay. In this way, the media cloud, composed of MECs, can be managed in a centralized or peer-to-peer (P2P) manner. The cloud media (Figure 1.5b) focuses on how multimedia ser- vices and applications, such as storage and sharing, authoring and mashup, adaptation and delivery, and rendering and retrieval, can optimally utilize cloud computing resources to achieve better quality of experience (QoE). As depicted in Figure 1.5b, the media cloud provides raw resources, such as hard disk, CPU, and GPU, rented by the media service providers (MSPs) to serve users. MSPs use media cloud resources to develop their multime- dia applications and services, for example, storage, editing, streaming, and delivery.
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technology enables a vendor’s cloud software to automatically move data from a piece of hardware that goes bad or is pulled offline to a section of the system or hardware that is functioning or operational. Therefore, the client gets seam- less access to the data. Separate backup systems, with cloud disaster recov- ery strategies, provide another layer of dependability and reliability. Finally, cloud computing also promotes a green alternative to paper-intensive office functions. It is because it needs less computing hardware on premise, and all computing-related tasks take place remotely with minimal computing hard- ware requirement with the help of technological innovations such as virtual- ization and multitenancy. Another viewpoint on the green aspect is that cloud computing can reduce the environmental impact of building, shipping, hous- ing, and ultimately destroying (or recycling) computer equipment as no one is going to own many such systems in their premises and managing the offices with fewer computers that consume less energy comparatively. A consolidated set of points briefing the benefits of cloud computing can be as follows: 1. Achieve economies of scale: We can increase the volume output or pro-
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are number of challenges that requires to be carefully addressed. In our paper, we present a survey of cloud computing and state- of-the-art research challenges. Our aim is to provide a better understanding of cloud computing and focus on the research ongoing in this tremendously flourishing arena of computer science.
It’s also critical to avoid thinking of cloud computing 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 cloud computing 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.
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for giving data security so Mobile Cloud Computing might be comprehensively recognized by different customers in future. It moreover suggested an instrument to give arrangement, get the opportunity to control similarly as uprightness to versatile customers. The handling capacity of convenient structures is improved by Cloud enlisting. Mobile phones can rely upon conveyed processing to perform computationally genuine exercises, for instance, looking data mining, etc. The use of flexible circulated registering vanquishes execution related tangles for instance exchange speed, amassing point of confinement and battery life, similarly as condition related issues for instance openness, flexibility and heterogeneity. Dispersed registering is changing the Internet handling establishment. Since by far many organizations are access from cloud over Internet, MCC has been introduced. The security hazard has pushed toward getting to be obstruction in the brisk improvement and generous usage of flexible conveyed processing perspective. The security perils have advanced toward getting to be catches in the quick flexibility of the versatile appropriated figuring perspective. Basic undertakings have been submitted in research affiliations and the insightful network to build secure versatile appropriated processing circumstances and systems. This paper reviews the possibility of adaptable conveyed figuring similarly as problems of security normal inside the setting of convenient application & disseminated registering. The standard vulnerabilities in structures with possible game plans are discussion about here.
In 1997, Professor Ramnath Chellappa of Emory University, defined cloud computing 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 cloud computing, autonomic and utility computing were the foundations of what the community commonly referred to as “cloud computing”. In the early 2000s, companies started rapidly adopting this concept upon the realization that cloud computing 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 cloud computing use cases of the 2000s. The latest widespread adoption of virtualization and of service- oriented architecture (SOA) promulgated cloud computing 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, cloud computing 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.
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There’s growing sentiment among many cloud experts that ultimately hybrid adoption will be most ad- vantageous for many organizations. Warrilow says “for some time Gartner has advised that hybrid is the most likely scenario for most organiza- tions.” Staten agrees with the notion for two reasons. First, “some appli- cations and data sets simply aren’t a good fit with the cloud,” he says. This might be due to application architec- ture, degree of business risk (real or perceived), and cost, he says. Second, rather than making a cloud-or-no- cloud decision, “it’s more practical and effective to leverage the cloud for what makes the most sense and other deployment options where they make the most sense,” he says. In terms of strategy, Staten recommends regularly analyzing deployment decisions. “As cloud services mature, their applica- bility increases,” he says.
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Case in point? Six in 10 channel firms say that cloud has generally strengthened their customer relationships, with just 15% claiming it has weakened them and roughly a quarter that said that their client bonds have remained the same. This is encouraging news given the fact that many in the channel have feared publicly that cloud would drive a wedge between them and their customers. There’s been rampant apprehension about such ill effects as a resurgence in vendor direct sales and end user customers choosing a self-‐service model for their IT solutions, i.e. procuring SaaS applications over the Internet. And while both of these trends are happening to a certain extent, CompTIA data suggest not at such dire expense to most of the channel, especially those that have reached a high level of cloud maturity today and intend to remain committed. That said, not all channel firms that adopt cloud will engender more good will with customers; some may simply have a customer set that is not cloud-‐ friendly, others may not gain sufficient expertise to provide value, etc.
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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.
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Lean agile development methodologies and the cloud model complement each other very well. Cloud services take pride in meeting user requirements rapidly, delivering applications whenever and to whatever extent they are needed. Agile methods give high credence to user collaboration in requirements discovery. The lean agile system of software development aims to break down project require- ments into small and achievable segments. This approach guarantees user feedback on every task of the project. Segments can be planned, developed, and tested individually to maintain high-quality standards without any major bottlenecks. The development stage of every component thus becomes a single “iteration” process. Moreover, lean agile software methods place huge emphasis on developing a collaborative relationship between application developers and end users. The entire development process is transparent to the end user and feedback is sought at all stages of development, and the needy changes are made accordingly then and there. Using lean agile development in conjunction with the cloud paradigm provides a highly interactive and collaborative environment. The moment developers fi nalize a feature, they can push it as a cloud service; users can review it instantly and provide valuable feedback. Thus, a lengthy feedback cycle can be eliminated thereby reducing the probability of misstated or misunderstood requirements. This considerably curtails the time and efforts for the software development organization while increasing end-user satisfaction. Following the lean agile approach of demand- driven production, end users ’ needs are integrated in a more cohesive and effi cient manner with software delivery as cloud services. This approach stimulates and sustains a good amount of innovation, requirement discovery, and validation in cloud computing.
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