Cloud

Cloud computing can raise ethical issues. In many cases these will depend on particular applications and circumstances. The present paper sets out to identify ethical issues of cloud computing that arise from the fundamental nature of the technology rather than any specific circumstances. The paper describes how these general features were identified, how ethical issues arising from them were collected and it concludes by discussing means of addressing them.

The landscape of cloud computing has significantly changed over the last decade. Not only have more providers and service offerings crowded the space, but also cloud infrastructure that was traditionally limited to single provider data centers is now evolving. In this paper, we firstly discuss the changing cloud infrastructure and consider the use of infrastructure from multiple providers and the benefit of decentralising computing away from data centers. These trends have resulted in the need for a variety of new computing architectures that will be offered by future cloud infrastructure. These architectures are anticipated to impact areas, such as connecting people and devices, data-intensive computing, the service space and self-learning systems. Finally, we lay out a roadmap of challenges that will need to be addressed for realising the potential of next generation cloud systems.

Enterprises would do well to consider the flexibility and risk-management implications of adding SaaS to their portfolios of IT services. Integration and composition are critical components in your architecture strategies to incorporate SaaS successfully as a fully participating member of your service-centric IT infrastructure. Today, SaaS applications are expected to take advantage of the benefits of centralization through a single-instance, multi-tenant architecture, and to provide a feature-rich experience competitive with comparable on-premise applications. A typical SaaS application is offered either directly by the vendor or by an intermediary party called an aggregator, which bundles SaaS offerings from different vendors and offers them as part of a unified application platform.

Clouds provide a powerful computing platform that enables individuals and organizations to perform variety levels of tasks such as: use of online storage space, adoption of business applications, development of customized computer software, and creation of a "realistic" network environment. In previous years, the number of people using cloud services has dramatically increased and lots of data has been stored in cloud computing environments. In the meantime, data breaches to cloud services are also increasing every year due to hackers who are always trying to exploit the security vulnerabilities of the architecture of cloud. In this paper, three cloud service models were compared; cloud security risks and threats were investigated based on the nature of the cloud service models. Real world cloud attacks were included to demonstrate the techniques that hackers used against cloud computing systems. In addition, countermeasures to cloud security breaches are presented.

Abstract— Recent boom in the cloud computing industry has caused a shift in the information technology industry and has affected the way how information and data is stored and shared among the enterprise. The advent of social applications also demands the availability of resources that can be shared among the others. Cloud based architecture has made it possible for enterprises to utilize the computation power that was not available in the past. This paper takes a look and compares the top available service providers on the basis of the cost for each computing model as well takes a look at the performance by measuring the response time. It is observed that at all these service providers and elaborated the comparison of all based on their available architectures.

Keywords— Comparison of Cloud Operators, Cloud Computing, Azure, RackSpace, Amazon Web Services

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A new method called Fmask (Function of mask) for cloud and cloud shadow detection in Landsat imagery is provided. Landsat Top of Atmosphere (TOA) reflectance and Brightness Temperature (BT) are used as inputs. Fmask first uses rules based on cloud physical properties to separate Potential Cloud Pixels (PCPs) and clearsky pixels. Next, a normalized temperature probability, spectral variability probability, and brightness probability are combined to produce a probability mask for clouds over land and water separately. Then, the PCPs and the cloud probability mask are used together to derive the potential cloud layer. The darkening effect of the cloud shadows in the Near Infrared (NIR) Band is used to generate a potential shadow layer by applying the flood-fill transformation. Subsequently, 3D cloud objects are determined via segmentation of the potential cloud layer and assumption of a constant temperature lapse rate within each cloud object. The view angle of the satellite sensor and the illuminating angle are used to predict possible cloud shadow locations and select the one that has the maximum similarity with the potential cloud shadow mask. If the scene has snow, a snow mask is also produced. For a globally distributed set of reference data, the average Fmask overall cloud accuracy is as high as 96.4%. The goal is development of a cloud and cloud shadow detection algorithm suitable for routine usage with Landsat images.

This Tech Report consist of 4 documents: this one, and the companion booklets 1, 2 and 3.

Cloud computing has become an extremely attractive area of research and practice over the last few years. An increasing number of public and private sector organizations have either adopted cloud computing based solutions or are seriously considering a move to cloud computing. However, there are many concerns about adopting and using public cloud solutions. Hence, private cloud solutions are becoming an attractive alternative to a large number of companies. We initiated a project aimed at designing and setting up a private cloud infrastructure in an academic and scientific environment based on open source software. One of the key objectives of this project was to create relevant material for providing a reference guide on the use of open source software for designing and implementing a private cloud.

The primary focus on this document is to provide a brief background on different theoretical concepts of cloud computing and then elaborate on the practical aspects concerning the design, installation and implementation of a private cloud using open source solution. It is expected that organizations looking at the possibilities for implementing cloud solutions would benefit from getting the basics, and a view on the different aspects of cloud computing in this document. Defining the cloud computing; analysis of the economical, security, legality, privacy, confidentiality aspects. There is also a short discussion about the potential impact on the employee’s future roles, and the challenges of migrating to cloud.

The main part of this report is concentrating on the practical infrastructure related questions and issues, supplied with practical guidelines and how-to-dos. The main topic was the design of the server and network infrastructure, and the distribution of the roles over the servers belonging to a private cloud. The management of the instances and the related subjects are out of the scope of this document. This document is accompanied by three supplemental books that contain material from our experiences of scaling out in the virtual environment and cloud implementation in a physical environment using the available server and networking equipments.

Construction projects involve multidisciplinary and multi-actor collaborations that generate massive amounts of data over their lifecycle. Data are often sensitive, and embody rights, ownership and intellectual property of the creator. Managing project information raises concerns about security, inconsistency and loss of data. Conventional approach of dealing with the complexities of data management involves the adoption of BIM based solutions that lack suitable means for the governance of collaboration, and access and archival of managed data. To overcome the limitations of BIM, Cloud-based governance solutions have been suggested as a way forward. However, there is a lack of understanding of construction ICT (Information and Communication Technology) practices from the perspectives of data management and governance. This paper aims to fill this gap; first, by exploring barriers related to BIM adoption and collaboration practices, in particular, issues related to data management and governance that can potentially be ameliorated with Cloud technologies, and second, by identifying key requirements for Cloud-based BIM governance solutions. A structured questionnaire was conducted among informed construction practitioners in this study. The findings reveal several barriers to BIM adoption alongside ICT and collaboration issues with an urgent need to develop a BIM governance solution underpinned by cloud technology. Further, a number of important requirements for developing BIM governance solutions have been identified.

Cloud computing is commonly used to represent any work done on a computer, mobile or any device, where the data and possibly the application being used do not reside on the device but rather on an unspecified device elsewhere on the Internet. The basic premise of cloud computing is that consumers (individuals, industry, government, academia and so on) pay for IT services from cloud service providers (CSP). Services offered in cloud computing are generally based on three standard models (Infrastructure-as s service, Platform-as a service, and Software as a Service) defined by the National Institute of Standards and Technology (NIST). The reason for cloud existence is to resolve managing problems being faced for data that were excessively stored, either mandatory capacity was limited due to the infrastructure of the business, or large capacity that led to a wasted capital. Apart from those major factors such as the initial capital, capitals and the service-fix cost, the sophisticated effort for the patching, the managing and the upgrading of the internal infrastructure is a huge obstacle for firm‘s development and mobility. For many firms where client and cultural competency have not got the strength to manage large data center environments and infrastructure, it would be wise to upload their files or data backups to another machine via internet, in order to concentrate more on the organizations primary objectives.

— Big Data is currently a very burning topic in the fields of Computer Science and Business Intelligence, and with such a scenario at our doorstep, a humungous amount of information waits to be documented properly with emphasis on the market. By market, we mean the current technologies in use, the current prevalent tools, and the companies playing an imperative role in taming the data with such a colossal outreach.

Cloud computing has come up as one of the most promising &reliable technologies in the IT sector. However presently there exists a major issue of load balancing in the cloud computing environment. This paper consists of a solution for optimizing the load using genetic algorithm. Genetic algorithm which follows the evolutionary mechanism is able to develop a solution close to optimal solution. The proposed algorithm is developed by merging two existing algorithms by considering cost value as the fitness function. The workload is balanced by the considering the combination of both the load percentage and cost value of the resources. Allocation of resources is performed by taking the best fit value and reducing the response time and overall cost. Simulation results are shown using the cloud analyst simulator.

Considering the complexity of today"s service environment, Small-to-Medium sized Enterprises (SMEs) cannot afford to accept the status quo of service operations and therefore must have some clear business analytics objective to reach. Without clear metric objectives, organisations are almost destined for disaster since the allocation of resources may not have responded to the demand exerted from outside of the organisation. This is particularly true within a complex and rapidly changing cloud computing environment. The cloud dynamic ecosystem is moving towards a collection of services which interoperate across the Internet. This chapter offers a discussion on an approach to assessing cloud capabilities through Cloud Service Capability Assessment Framework (CSCAF). Service metrics plays a critical role in CSCAF and presents managers with a practical framework to carry out cloud capability assessments. The process may be simply described as publishing, retrieving, and managing cloud service descriptions, service publications which are matched with descriptions of consumer"s requirements and service matching.

"In developing countries, the lack of infrastructure like GPS (Global positioning system) and GIS (Geographic Information system) have hindered the growth of the police department. This
paper proposes a simple, useful and cost effective solution for crime mapping. Google cloud resources like satellite data, application and GIS software have been used to develop this application. The developer requires only a simple computer connected to the internet. The source of crime data is the RSS (Really Simple Syndication) feeds from various news websites."

Cloud gaming is an emerging technology that combines cloud computing with computer games. Compared to traditional gaming, its core advantages include ease of development/deployment for developers, and lower technology costs for users given the potential to play on thin client devices. In this chapter, we firstly describe the approach, and then focus on the impact of latency, known as lag, on Quality of Experience, for so-called First Person Shooter games. We outline our approach to lag compensation whereby we equalize within reason the up and downlink delays in real-time for all players. We describe the testbed in detail, the open source Gaming Anywhere platform, the use of NTP to synchronise time, the network emulator and the role of the centralized log server. We then present results that firstly validate the mechanism and also use small scale and preliminary subjective tests to assess and prove its performance. We conclude the chapter by outlining ongoing and future work.

Image processing algorithms related to remote sensing have been tested and utilized on the Hadoop MapReduce parallel platform by using an experimental 112-core high-performance cloud computing system that is situated in the Environmental Studies Center at the University of Qatar. Although there has been considerable research utilizing the Hadoop platform for image processing rather than for its original purpose of text processing, it had never been proved that Hadoop can be successfully utilized for high-volume image files. Hence, the successful utilization of Hadoop for image processing has been researched using eight different practical image processing algorithms. We extend the file approach in Hadoop to regard the whole TIFF image file as a unit by expanding the file format that Hadoop uses. Finally, we apply this to other image formats such as the JPEG, BMP, and GIF formats. Experiments have shown that the method is scalable and efficient in processing multiple large images used mostly for remote sensing applications, and the difference between the single PC runtime and the Hadoop runtime is clearly noticeable.

As the cloud computing is a new style of computing over internet. It has many advantages along with some crucial issues to be resolved in order to improve reliability of cloud environment. These issues are related with the load management, fault tolerance and different security issues in cloud environment. In this paper the main concern is load balancing in cloud computing. The load can be CPU load, memory capacity, delay or network load. Load balancing is the process of distributing the load among various nodes of a distributed system to improve both resource utilization and job response time while also avoiding a situation where some of the nodes are heavily loaded while other nodes are idle or doing very little work. Load balancing ensures that all the processor in the system or every node in the network does approximately the equal amount of work at any instant of time. Many methods to resolve this problem has been came into existence like Particle Swarm Optimization, hash method, genetic algorithms and several scheduling based algorithms are there. In this paper we are proposing a method based on Ant Colony optimization to resolve the problem of load balancing in cloud environment.

Education is highly important in today's society. It helps to motivate the minds and shape it into intellectuals. Many Academic Institutes are exploring new technologies for effective teaching and learning Methodology. One of the emerging technologies Cloud Computing can be very useful in teaching learning process. As Cloud provides a variety of services, an institute can offer quality education by providing latest infrastructure in terms of hardware and software. This paper focuses on basic introduction of cloud Computing and how cloud computing can be introduced in the education to improve teaching and learning methodology which can bring a revolution in the field of education.

Advancement in information and communication technology (ICT) has given rise to explosion of data in every field of operations. Working with the enormous volume of data (or Big Data, as it is popularly known as) for extraction of useful information to support decision making is one of the sources of competitive advantage for organizations today. Enterprises are leveraging the power of analytics in formulating business strategy in every facet of their operations to mitigate business risk. Volatile global market scenario has compelled the organizations to redefine their supply chain management (SCM). In this paper, we have delineated the relevance of Big Data and its importance in managing end to end supply chains for achieving business excellence. A Big Data-centric architecture for SCM has been proposed that exploits the current state of the art technology of data management, analytics and visualization. The security and privacy requirements of a Big Data system have also been highlighted and several mechanisms have been discussed to implement these features in a real world Big Data system deployment in the context of SCM. Some future scope of work has also been pointed out.

A Cloud Computing system is intended to improve and automate the controlling single point operations. By using a single point of control, this goal is accomplished through the elimination of duplicate entry and the contribution of data integrity, detailed drilldown, simple training, manageable support, minimal IT maintenance, easy upgrades and reduced costs. Overall, the advantages of cloud computing usage fulfill the original intentions of business as it allows process manufacturers to manage their business as simply and efficiently as possible. Enterprise Resource Planning (ERP) software is designed to improve and auto-mate business processes operations. However, there are many unnecessary administrative, procedural costs and delays often associated with this practice. Examples include duplicate data entry, data corruption, increased training, complicated supplier relations, greater IT support and software incompatibilities. Purpose of this system is Single Point of Control, Duplicate Entry Elimination, Data Integrity, Detail Drill Down, Basic Training, Manage Support, Security, Minimal IT Maintenance, Easy Upgrades, and Reduce Costs etc.

Contemporary mobilizations are largely enabled by and modeled after commercial social media platforms. The materiality of the communication infrastructure thus plays an important role in determining how people mobilize, organize and strategize. This chapter explores the tension between activist agency and the structure and political economy of platforms through the lenses of the cloud. The cloud is a) a metaphor for a particular way of connecting individuals in an instance of collective action, and b) the virtual imagined space hosting and shaping individual and collective interactions and meaning-making activities, constituting the repository of soft resources (e.g., identities, frames…) critical to collective action. Talking about the cloud allows us to move beyond the specifics of individual platforms such as Facebook and Twitter, addressing social media as a whole rather than separate services. Disentangling the materiality of the cloud will help us understand how infrastructures shape tactics, identities and networking strategies.

Weather and Climate forecasting is the application of science and technology to predict the state of the atmosphere for a given location. This provide occurrence or change in severity of plant diseases. At the field scale, these systems are used by growers to make economic decisions about disease treatments for control. Often the systems ask the grower a series of questions about the susceptibility of the host crop, and incorporate current and forecast weather conditions to make a recommendation. Forecasting system provide information about plants disease which happen due to Weather and Climate changes and it happen in such a fashion that disease can occur and cause economic losses.

The advent of Cloud Computing has altered the IT landscape. Hardware, software and the technical expertise required to provide and maintain IT services have been aggregated in the Data Centre. This has given rise to a new IT delivery system resulting in significant benefits in the way of efficiency and cost saving to name but a few. There are obvious positives, which give cloud-computing legitimacy as a solution such as: • Economy of Scale (virtualization has dramatically increased hardware utilization meaning IT workloads can be packed densely into a smaller space. This results in economy of scale as more IT can be serviced with less resource.) • A Reduction in capital expenditure on infrastructure and less software licensing costs. • Pay for IT services on demand therefore giving greater cost efficiency. Marry expenditure on IT services to company cash flow (based on operational activity.) • Workforce distribution. If employees can access the organizations data and IT resources over the Internet there is potential for savings by paying local (potentially cheaper) rates and lessening overhead costs associated with having to provide dedicated office space in expensive locations. • Outsource technical IT expertise to the datacenter. Lessen the need to hire IT staff to directly to manage specific IT needs that can be provided for by a cloud service provider. Those are just some of the benefits, which make cloudcomputing such an attractive model. However, there are also significant challenges that have emerged over time as cloud services have been adopted by a wide range of clients from personal users, to commercial organizations to government agencies. These are issues relating to data security, privacy, regulatory compliance, auditing and assessment, etc.… All of which are brought on by what is a lessening in an organizations control of its IT resource when a move to the Cloud occurs. This is because of the distributed nature of Cloud Services in which an organizations data now physically resides off-premises and perhaps in a system whose boundaries are significantly blurred in comparison to a deployment on the more traditional client-server based IT model and where the expertise to manage that resource has been outsourced to a third party. One such challenge is in the area of legislation. This document aims to outline some of the jurisdictional issues that accompany adoption of Cloud Services by an organization or entity. We will investigate the current status in regard to the legal state of cloud computing and identify what's being done to legislate for the changing face of IT as a result of the wide scale uptake of Cloud based services. In particular, how does a system of law, which is traditionally applied, based on jurisdiction, apply to a public cloud solution that is essentially ethereal in its nature?

Today teaching learning methodology has significantly changed. With the new innovations in the field of information technology, our classrooms are becoming virtual, knowledge is on the cloud. Though education field has adopted these new technologies, it is still faced with the problem of improving the quality standard of education and diminishing dropout rates. This paper will review the big data analytics techniques that can be used in the education sector and what are the challenges that affecting the improvement in quality of education.

Cloud computing is growing significantly day by day, and has created a shift in the IT industry. It brings several advantages to consumers by delivering computing as a service, such as self-service, on-demand, broad network access, rapid elasticity, resource pooling, and measured service. On the other hand, organizations have many fears when deciding to migrate to cloud computing, due to the many risks they are exposed to by the cloud environment. Risk management is an appropriate method to identify, assess, and manage risks. The traditional risk management frameworks do not fit cloud computing well due to its complex environment and the assumption by those frameworks that the assets are owned and fully managed by the organization itself. The aim of this paper is to propose a new security risk management framework for the cloud computing environment. The framework focuses on the two main issues that affect the effectiveness of risk management: loss of control and the multi-tenant architecture of cloud computing. The proposed framework has been evaluated on a hypothetical cloud computing provider to present the step by step progress of the proposed framework.

Cloud computing is envisioned as the next generation architecture for IT Enterprises, and has proliferated
itself due to the advantages it provides.Cloud computing provides solutions for carrying out efficient, scalable and low cost computing. The pay per usage concept of Cloud computing increases the resource utilisation of a vendor’s computing power and resources; at the same time,it results in reduced hardware costs forits users. It also provides access mobility, easier maintenance, scalabilityand operability in terms
of its management and usage. Because of the facilities and solutions it provides to the industry for the next generation computing, it is vulnerable to a variety of known and unknown attacks from attackers.Hence, securinga Cloud environment is a critical problem that needs urgent attention.This articlefocuses on a taxonomy of possible attacks on a Cloud environment and a taxonomy of the defence .The attack taxonomy describes existing threats on Cloud security, and the defence taxonomy gives a classification of the various counter measures that can be taken to protect the Cloud environment from such attacks. The aim of this article is to provideresearchers, academicians and industry with a better understanding of existing attacks and defence mechanisms on Cloud security.This is to provide a clearvision of the challenges that should be worked onto ensure next generation security forCloud computing

In the current digital era, education system has witness tremendous growth in data storage and efficient retrieval. Many Institutes have very huge databases which may be of terabytes of knowledge and information. The complexity of the data is an important issue as educational data consists of structural as well as non-structural type which includes various text editors like node pad, word, PDF files, images, video, etc. The problem lies in proper storage and correct retrieval of this information. Different types of learning platform like Moodle have implemented to integrate the requirement of educators, administrators and learner. Although this type of platforms are indeed a great support of educators, still mining of the large data is required to uncover various interesting patterns and facts for decision making process for the benefits of the students. In this research work, different data mining classification models are applied to analyse and predict students' feedback based on their Moodle usage data. The models described in this paper surely assist the educators, decision maker, mentors to early engage with the issues as address by students. In this research, real data from a semester has been experimented and evaluated. To achieve the better classification models, discretization and weight adjustment techniques have also been applied as part of the pre-processing steps. Finally, we conclude that for efficient decision making with the student's feedback the classifier model must be appropriate in terms of accuracy and other important evaluation measures. Our experiments also shows that by using weight adjustment techniques like information gain and support vector machines improves the performance of classification models.

Cloud computing present new economic and flexible business and technological models. The explosive uptake of cloud solutions has fuelled the growth of cloud service providers (CSP). However, recent development show that within the field of cloud computing there is often too much focus on technology solutions but little insight on cloud exploitation and service analytics from a business perspective. To support CSPs and cloud users, it is critical that sourcing decisions are informed to align cloud strategy and service capabilities. In this paper we present a contingency model which supports the assessment of cloud composite capabilities. While we develop an understanding of the research gaps which exists throughout academic and industry literature, the contribution of this paper is the introduction of our contingency model which forms the initial development of the Cloud Service Index (CSI). The CSI is a basis to assess cloud composite capabilities.

The Internet is an existing thing, always changing and growing. New applications and businesses are created endlessly. Besides to developing Internet, technology is changing the backdrop. Broadband connectivity is becoming cheap and omnipresent; devices are becoming more powerful and smaller with a variety of committed sensors. The abundance of more devices becoming connected is leading to a new prototype: the IoT. The IoTs is driven by an extension of the Internet through the addition of physical objects united with an ability to provide smarter services to the upbringing as more data becomes available. Various application domains like Smart Infrastructure, Healthcare, Security and Surveillance, Transportation, Retail, Industrial and Telecommunication etc., there are challenges associated with the IoTs, most explicitly in areas of trust and security, Privacy and Data Confidentiality. In this way, the things/objects are capable of recognizing events and changes in their surroundings and are acting and reacting autonomously.

The distributed computing is done on many systems to solve a large scale problem. The growing of high-speed broadband networks in developed and developing countries, the continual increase in computing power, and the rapid growth of the Internet have changed the way. In it the society manages information and information services. Historically, the state of computing has gone through a series of platform and environmental changes. Distributed computing holds great assurance for using computer systems effectively. As a result, supercomputer sites and datacenters have changed from providing high performance floating point computing capabilities to concurrently servicing huge number of requests from billions of users. The distributed computing system uses multiple computers to solve large-scale problems over the Internet. It becomes data-intensive and network-centric. The applications of distributed computing have become increasingly wide-spread.

Buying a car entails a cost, not counting the day to day high price tag of gasoline. People are looking for viable means of transportation that is cost-effective and can move its way through traffic faster. In the Philippines, motorcycle was the answer to most people transportation needs. With the increasing number of a motorcycle rider in the Philippines safety is the utmost concern. Today technology plays a huge role on how this safety can be assured. We now see advances in connected devices. Devices can sense its surrounding through sensor attach to it. With this in mind, this study focuses on the development of a wearable device named Smart Motorcycle Helmet or simply Smart Helmet, whose main objective is to help motorcycle rider in times of emergency. Utilizing sensors such as alcohol level detector, crash/impact sensor, Internet connection thru 3G, accelerometer, Short Message Service (SMS) and cloud computing infrastructure connected to a Raspberry Pi Zero-W and integrating a separate Arduino board for the anti-theft tracking module is used to develop the propose Internet-of Things (IoT) device. Using quantitative method and descriptive type research, the researchers validated the results from the inputs of the participant who tested the smart helmet during the alpha and beta testing process. Taking into account the ethical consideration of the volunteers, who will test the Smart Helmet. To ensure the reliability of the beta and alpha testing, ISO 25010 quality model was used for the assessment focusing on the device accuracy, efficiency and functionality. Based on the inputs and results gathered, the proposed Smart Helmet IoT device can be used as a tool in helping a motorcycle rider when an accident happens to inform the first-responder of the accident location and informing the family of the motorcycle rider.

This paper studies a fourth emerging service model of cloud computing, Business Process as a Service (BPaaS). BPaaS is generating hype but it is under researched with a lack of clarity regarding how BPaaS differentiates itself from other service models and what opportunities and challenges it presents for management and organisations attempting to implement it. In this paper we examine the theoretical underpinnings of BPaaS with a view to developing an understanding of the potential value of adopting the BPaaS model and its implications for the realisation of business value from cloud computing. We develop the SEIFS framework (Situation, Elemental, Integration, Flexibility, and Scalability) to provide guidance in the classification of cloud services as BPaaS or otherwise and attempt to validate this framework by using a series of case studies based in Irish cloud computing firms. Our paper aims to contribute to the literature by addressing confusion in the classification of cloud services, and specifically BPaaS. We also provide insights for prospective BPaaS providers to factor into their service design and discuss how BPaaS can provide a competitive advantage. Finally, we identify and discuss a number of areas for future research.

La ricerca - presentata nella “Giornata di Studio Interdisciplinare sul commercio elettronico”, tenutasi presso l’Università di Siena il 7 maggio 2015 - si incentra sul processo di standardizzazione delle clausole contrattuali in materia di cloud in atto in Europa e sulle Cloud Service Level Agreement Guidelines Standardisation pubblicate nel 2013 dalla Commissione Europea.
La standardizzazione delle clausole contrattuali non è un fenomeno nuovo per il diritto europeo. Già nelle direttive sulla tutela del consumatore sono rinvenibili, ad esempio, disposizioni che nel recare l’elenco delle clausole presuntivamente vessatorie di fatto si preoccupano di standardizzare le condizioni contrattuali, ancorché si tratti di quella da non applicare.

This article aims to look at one of the emerging trends in the practice of Law which is the fast-rising reality of
virtual, cloud-based law firms that is a remove from the conventional, brick-and-mortar law office model that has
been in existence since the inception of law practice in the country and since Time Immemorial all over the world.
This article aims to showcase the fact that, with the rise in the use of extremely sophisticated technology,
sophisticated clients are increasingly on the need for service providers that meet up with their own level of
sophistication and can be trusted to handle complex matters from anywhere and which results the client has access
to without having to spend the time rushing to the offices of his legal representative(s). Consequently, a lot of firms
that are still very brick-and-mortar focused are now becoming increasingly redundant and unpopular with clients
who want a more inclusive, cloud-based package that can service their needs from anywhere.

For Cloud based services to support enterprise class production workloads, Mainframe like predictable performance is essential. However, the scale, complexity, and inherent resource sharing across workloads make the Cloud management for predictable performance difficult. As a first step towards designing Cloud based systems that achieve such performance and realize the service level objectives, we develop a scalable stochastic analytic model for performance quantification of Infrastructure-as-a-Service (IaaS) Cloud. Specifically, we model a class of IaaS Clouds that offer tiered services by configuring physical machines into three pools with different provisioning delay and power consumption characteristics. Performance behaviors in such IaaS Clouds are affected by a large set of parameters, e.g., workload, system characteristics and management policies. Thus, traditional analytic models for such systems tend to be intractable. To overcome this difficulty, we propose a multi-level interacting stochastic sub-models approach where the overall model solution is obtained iteratively over individual sub-model solutions. By comparing with a single-level monolithic model, we show that our approach is scalable, tractable, and yet retains high fidelity. Since the dependencies among the sub-models are resolved via fixed-point iteration, we prove the existence of a solution. Results from our analysis show the impact of workload and system characteristics on two performance measures: mean response delay and job rejection probability.

The shading pattern of a Solar Panel if analyzed helps to improve the performance of a Solar panel. Shades on top of a Solar Panel are one of the major factors which causes disturbance on a solar panel. This paper helps analyze the shading on a solar panel which is caused by steady clouds. This may help to increase the efficiency of a solar panel. Various methods of Image processing technique is used to get the desired output. Those methods include techniques like median filtering and various morphological functions like usage of structuring element which gives the desired output. The problem of Boundary Estimation of a shading patter on a solar panel is addressed. Short-time shading and lightning is not at all useful for solar power plant. If the solar panel is shaded then proper measures have to be taken to keep the efficiency intact else there would be a serious loss in the amount of current generated with the help of a solar panel. Here the pixel values are measured and thus the exact numbers of dark and bright pixels are calculated and even the pixel values are reconfigurated to get the correct boundary estimation. The bypass diode is used to bypass the shaded area on the panel, which in turn helps to increase the efficiency of a solar panel by a significant amount. This method takes care of processing all kinds of shade on the solar panel from whatever source the shade is generated from.This concept can be taken further to analyse the various other parameters for effective operation.

The most common benchmarks for cloud computing are the Terasort benchmark and the YCSB benchmark. Although these benchmarks are quite useful, they were not designed for data warehouse systems and related OLAP technologies. In this paper, first, we present cloud computing and data warehouse systems. Then, we argue that TPC-H benchmark -the most prominent benchmark for decision support system, mismatches cloud rationale (scalability, elasticity, pay-per-use, fault-tolerance features) and Customer Relationship Management rationale (enduser satisfaction, Quality of Service features). Finally, we present new requirements for implementing a benchmark for data warehouse systems in the cloud. The proposed requirements should allow a fair comparison of different cloud systems providers' offerings.