Cloud computing delivers virtualized resources. In previous chapter, it has been discussed how virtualization technology has revolutionized the computing environment. It is important to note that in reality the virtualized resources are effective representations of actual physical resources. Cloud data centers maintain a large pool of physical computing resources which is presented in virtual mode as infrastructure service. This chapter focuses on how those resource pools are organized in cloud data centers.

Resource sharing is another important feature of cloud computing. Any resource component from the pool of resources is not dedicatedly used to serve one particular user or application; rather they are shared among multiple users or applications. Through this increment in resource utilization rate, a comparatively smaller number of resources can serve a large number of users.

Resource pooling, virtualization and sharing of resources ultimately converge to produce the dynamic behaviour of cloud systems. Cloud supplies the resources dynamically to users. This dynamic resource provisioning eliminates the need of permanent procurement of computing resources. This turns out to be a very effective technique as application demands or loads during computation do not remain same over a period of time.

RESOURCE POOLING

The utility service model of cloud computing requires to maintain huge amount of all types of computing resources to provide different services to consumers. For this purpose, cloud service providers create pool of computing resources. Effective pooling or grouping of resources requires appropriate system designing and architectural planning.

Resource pooling in cloud needs setting up of strategies by provider for categorizing and managing resources. Before resource pooling concept appeared, earlier people used to maintain discrete and independent set of resources known as silos.

In traditional computing model, the silos are made with very little or no inter-connections. On the other hand in cloud computing, the consumers use well-connected pool of computing resources. They gain almost no knowledge or control over the locations from where physical resources are allotted to them. In its out-of-best scenario, the providers sometimes ask for choice of geographic location (country or continent) from where a consumer wants to get resources. But this choice is only possible in case of large service providers who have data centers at multiple geographic locations around the world.

The first three chapters of this book provide an overview of introductory cloud computing issues. Beginning with the discussion about limitations of traditional computing approach, it focused on the primary benefits of cloud computing adoption. The second chapter also explained how starting from the days of mainframe computers, cloud computing has matured over the years with continuous developments and reformations in the field of computing.

With this basic understanding of the primary concepts and knowledge regarding the technological drivers behind cloud computing, it is now time to delve further. Now, it will be appropriate to understand the architectural model of cloud computing.

In this chapter, the standard definitions and globally accepted NIST (National Institute of Standards and Technology) model of cloud computing have been explored in order to establish a baseline. NIST has identified five characteristics which have collectively revolutionized this computing model. Apart from these, different types of cloud deployments have also been discussed. Understanding the cloud deployment models is important as it is critical for making informed decisions so that appropriate cloud solution can be picked to satisfy personal or business needs.

STANDARD CLOUD MODEL

Cloud computing is a reality now and is being delivered commercially. Decades of research and several innovations have paved the way for its success. Though the concept surfaced several years back, the implementation of the concept has been possible through different phases of remodeling and renovation over the years.

During its early days, the idea was defined in many ways by different sections of people as they presented it from their respective view points. Academicians, computer engineers, system architects, software developers, and consumers had their own ideas and suggestions about the models for this new approach of computing. All these proposals had several limitations as there were many aspects which had to be considered. Formation of a complete definition which could address all of these aspects was thus felt necessary. A standard model was also required as it becomes substantive for the advancement of any technology.

In cloud computing everything moves around the globe through a huge network called Internet. All requested services and data from any public cloud are delivered to consumers via Internet. The delivery of the content from the source to the consumer may involve delays as the two may be far apart geographically from one another. This delay in content delivery in cloud computing could increase the response time barrier in acceptance of the technology. This delay may further increase due to heavy traffic over the network. And, studies have shown that delay in response time can cause huge business loss.

Cloud computing is made not only for network-centric computing but also for network-centric content management. To serve the purpose of instant delivery of content via network to the consumers, technologists have introduced the concept of a dedicated network for faster content delivery. Content generators like cloud service providers can make use of these networks for efficiently delivering their content to millions of consumers across the globe.

CONTENT DELIVERY IN THE CLOUD

Content is any kind of data ranging from text to audio, image, video and so on. Delivering this content to any location at any time is a critical issue for the success of cloud services. Smooth delivery of content and a positive user experience have always been the prime concern of content makers and content providers in world-wide networked environment like cloud computing. The primary objective is to minimize the page (that is the content in a page) load time as studies have shown that even a delay of a second in page loading time can negatively affect customers’ experience significantly.

Forecasting any failure in network delivery and overcoming it has always been a challenge for content suppliers and the scenario has turned more critical with the adoption of network-centric cloud computing environment. The network requirements for delivering content have changed extensively during the last decade when large volumes of multimedia content started pouring in and consumers’ expectation regarding content availability over Internet shot up.

Computing performance over cloud-based services is very important to encourage cloud service adoption as consumers are accustomed to working on their personal work-stations in traditional way of computing.

According to the first postulate of quantum mechanics, the state of an isolated system is described by a vector in the Hilbert space. However, more often than not, we encounter systems interacting with other systems. In this chapter we address the question of describing the state of a system interacting with other systems without any reference to the details of the other system or that of the interaction between them. This leads to the concept of the density operator. The concept of density operator will be seen to arise also while characterizing the state of a mixture of particles in different states.

State of a Subsystem

Consider a system composed of the subsystems A and B lying in the Hilbert space of dimensions nA and nB, respectively. We use the formalism developed in Section 5.6 for describing a composite system. Let the state of the composite system be. Recall (5.71) which expresses the composite state of A and B in terms of the superposition of the tensor product of their basis states:

where and are the sets of the orthonormal basis states of A and B. Let it be that we are interested in the properties of only one of the subsystems, say, the subsystem A. Those properties are determined by the expectation values of the operators which act on the states of the subsystem A alone.

The physical quantum harmonic oscillator (h.o.) in one dimension is a linear combination of the operators and. Its properties are described by the wave function representing its state jxi in the position representation spanned by the eigenvectors. The energy eigenvalue problem of the h.o. in the position representation amounts to solving the second-order Schrödinger equation for x(x). The solution of that equation has been derived in Section 11.2 as a special case of the general solution of exactly solvable potentials.

Very often one encounters Hamiltonians which are linear combinations of operators and where and obey the same commutation relation as and but those operators do not act on fjxig. We call them h.o. like Hamiltonians. In such cases, one cannot define (x) and consequently the eigenvalue problem of such Hamiltonians cannot be reduced to the one of solving Schrödinger's differential equation.

The eigenvalue problem of h.o. like Hamiltonians therefore requires different approaches for its solution. This chapter discusses the method of solving that problem using only the commutation relation between, without reference to any representation. That approach proves useful even for the physical h.o. as it reduces its eigenvalue problem to the one of solving a simple first-order differential equation, a task arguably simpler than solving the second-order differential equation. The eigenvalue spectrum found by the two methods turns out to be the same.

In general, the method of solving the eigenvalue problem by using only the commutation relations between the operators constituting the Hamiltonian is indispensable while dealing with Hamiltonians, such as the ones involving spin, which have no classical counterpart.

The introduction of cloud computing creates numerous benefits for consumers of computing services but it also has security concerns associated with it. In addition to most security risks present in the traditional computing environment, cloud computing brings a new set of security issues with it. These issues emerge basically due to the massive sharing of infrastructure and resources which is an inherent feature of the utility service model.

A proper understanding of cloud architecture and appropriate selection of cloud deployment may reduce the security risks to a great extent. It is also important to understand that security maintenance is a combined effort for both the provider and the consumer of cloud. This chapter tries to focus on the security aspects of cloud from different service levels, apart from discussing the cloud security design principles and frameworks.

Cloud-based security systems need to address all the basic needs of an information system like confidentiality, integrity, availability of information, identity management, authentication and authorization. These security requirements are not new, but cloud computing specific standpoint on these issues are essential to analyze as well as implement security in a cloud-based system.

CLOUD SECURITY

For an enterprise, sharing infrastructure in cloud computing environment is like a person going to some public place with valuable belongings. Others with wrong intent may anytime target those valuable belongings. Similarly, moving sensitive files or data out of an enterprise's own network security boundary, in cloud computing, also causes security concerns. Hence, implementation of strong identity management and access control mechanism are important in cloud environment.

Security is developing resistance to damage or protecting a system from any harm. Security is a major concern for any computing system and also for the cloud computing system too. Computing system security means protection of the system itself and also of the data that it stores.

When an IT service consumer, be it an individual or an organization, migrates to cloud computing, especially in public cloud services; much of the computing infrastructure moves into the control of third-party cloud services providers.

Introduction: the Nature of Empire

This chapter and the next will consider empire and trade which, like power and profit, were closely linked. Traditionally ‘empire’ was understood in terms of control over territory, and the resources that it contained, predominantly but not exclusively within Europe: the Roman Empire was the greatest example. In the Middle Ages and beyond the main ‘empire’ within Europe was the Holy Roman Empire, in which the Habsburg emperors ruled a variety of territories, including Austria and Hungary, and exercised a looser authority over very many more, mostly in what became Germany. Further west the Normans and Angevins ruled an Anglo-French empire: kings of England ruled a considerable part of France until the 1450s.

From the late fifteenth century a new meaning of ‘empire’ developed. It was used mainly of lands outside Europe and focused on the acquisition of highly profitable commodities of three types.

First, precious metals. The Spanish conquests in South America opened Europeans’ eyes to the enormous profits that could be made from plunder and mining in a continent rich in gold and silver. Many of the early English colonists in North America hoped to make their fortune in this way but were doomed to disappointment.

Second, staple crops, particularly sugar and tobacco, for which a strong demand quickly developed in Europe. There was a strong incentive to grow these on a large scale, on plantations, in order to maximise production and profits. Production on such a scale developed first in the Portuguese sugar plantations in Brazil, but the Spaniards followed their example where conditions were suitable, notably in the Caribbean; so, later, did the English.

We humans are surrounded by technology. We have machines for almost everything and computers allow us to achieve things that were long deemed impossible. We live in a day and age where dreams can become reality overnight due to technical innovation, and the amount of information that we have access to via a tiny machine in our pockets is simply astounding. There is talk right now about flying people to Mars and growing tomatoes there. Yes, we humans are a smart bunch.

Despite all this, there are some things we are still unable to do, and some machines we simply cannot build. And some of these failures have to do with language. A machine that can translate one language into another language perfectly? No, we don't have it (and please don't insult us by referring to Google Translate). Okay, how about something more modest, like a machine that can for any combinations of words in a single language (say, English) say whether it is a good sentence or not? It is perhaps hard to believe but even that is still out of our reach. Language, as it turns out, is an evasive and slippery creature.

At the same time, it is clear that such a machine, capable of stating for every English sentence whether it is grammatical or not, does exist. In fact, we have about 360 million of those machines on our planet. They are called native speakers of English. These speakers have at their disposal the knowledge of their mother tongue, English, and this knowledge can generate zillions of distinct combinations of English words and evaluate each of them, whether old or new, as being either a good sentence or not. Probably you have never heard someone say Syntax is one of the most fascinating topics in linguistic theory, but if you are a native speaker of English you know immediately that the sentence is grammatically correct (and hopefully after reading this book you will also find it to be correct content-wise). So these native speaker brains can do something that we cannot imitate with any man-made machine. The fact that we cannot mimic such everyday human language behaviour shows us that there is something worthwhile studying.

Introduction

The approach of this second chapter considering Britain and Ireland around 1450 is bottom-up rather than top-down. It has three main themes. First, it discusses the economy – agriculture, trade and manufactures – and the extent to which the balance of economic power was transformed by the Black Death. Second, it looks at the communities in which people lived and the way in which they were governed. It shows that, although the better-off wielded more power than the poor, there was a significant growth in participation and self-government, as seen in the treatment of the poor. The third theme is religion – the Church's organisation and teachings, and popular belief and spirituality. It argues that, while many popular beliefs and practices did not fully reflect the Church's teachings, a substantial proportion of the people were deeply attached to the Church and its liturgy.

Making a Living: Agriculture

The great majority of the people of Britain and Ireland made their living wholly or partly from agriculture. Some rented farms from landowners, on which they were able to produce enough (more or less) to support their families. Others held little or no land and depended on selling their labour, either in agriculture or rural industry; they might also be able to gather firewood and foodstuffs from woodland. Many rural families lived close to the margins of subsistence, at the mercy of crop failure and disease. Their diet was limited and monotonous, with a heavy dependence on grain, or, in pastoral areas, dairy produce. There was as yet no staple crop (like the potato) to enable people to feed a family from a small plot of land. Those living near the sea might be able to catch fish, but meat was a rarity: those who reared cattle often did so to sell, not for their own consumption. The right to catch wild animals and river fish was jealously guarded by the landowners.