24-06-2014, 11:55 AM
Cloud Computing
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. INTRODUCTION
Applications such as auctions, personal portfolio valuations for financial decisions, sensors-based monitoring, route planning based on traffic information, etc., make Extensive use of dynamic data. For such applications, data from one or more independent data sources may be aggregated to determine if some action is warranted. Given the increasing number of such applications that make use of highly dynamic data, there is significant interest in systems that can efficiently deliver the relevant updates automatically. As an example, consider a user who wants to track a portfolio of stocks in different (brokerage) accounts. Stock data values from possibly different sources are required to be aggregated to satisfy user’s requirement. These aggregation queries are long running queries as data are continuously changing and the user is interested in notifications when certain conditions hold. Thus, responses to these queries are refreshed continuously.
A truly web-centric enterprise (WCE) combines current, lean technology with intelligent and agile management methods. It embraces flexibility and less stringent organisational policy. With it comes an amorphous and extremely dynamic classification of users and their information needs. It involves getting information to the right people at the right time and in the right context—all of which may change in days or weeks, not years. It requires a more progressive approach to control.
The impact of moving to a web-centric environment can be significant, enabling businesses to accelerate the pace of business and meet the increased need for constant innovation in order to outpace the competition. Moreover, it can help organisations reach new customers and obtain new levels of efficiency. In the early and mid-1990s, IT found itself at a crossroads. CIOs spent years and millions of dollars purchasing, implementing, customizing, and maintaining enterprise resource planning (ERP) and customer relationship management (CRM) applications. Challenges related to e-mail, the Internet, laptops, and security kept many IT departments extremely busy.
Although exceptions certainly exist, the challenges that a typical IT department faces today are significantly different than those of a decade ago. As a result, IT has changed significantly within that time frame. Large enterprises have had to navigate increasingly challenging waters amidst changes of unprecedented scope and speed. These tectonic shifts included
• The continued globalization of business.
• The acceleration of “network orchestrator” models—intermediaries who leverage information platforms to establish themselves as value brokers at the heart of business ecosystems.
• The explosion of mobile, open-source, and device-independent information access and use.
• Exponentially larger amounts of data from various sources, including social media, videos, audio, reviews, and more.
• The decreased price of storage and the availability of virtual storage to consumers and enterprises alike.
• The consumerisation of IT and the introduction of tools and apps into the enterprise workplace and workflow
Cloud Computing
Cloud computing helps organisations meet the need for mobility, while also helping to control costs associated with hardware, ease the introduction of products as services, and more. As the foundation of a web-centric environment, cloud computing brings organisations more than simply the ability to shift their focus from managing servers to managing the enterprise—with it, comes the ability to reduce capital expenses and maintenance costs, and deploy projects faster. These are all key factors for success as business continues to move faster. Interestingly, while cloud computing is a hot topic today, the concept behind cloud computing has been around for decades.
Broadband exploded as storage costs declined. And the real impetus for the rise of cloud computing has been increased mobility. Billions of mobile phones have been sold, many of which are “smart”—that is, they allow for web browsing, productivity, and other “non-phone” functions. In many parts of the world, a Smartphone is the most common way to access online resources and information. Today, many former products are becoming services. Terms like infrastructure as a service (IaaS) and platform as a service (PaaS) have entered the business zeitgeist. Also, it’s projected that many more business tools will be offered as a service in the coming years. “Everything as a service” will become the norm as businesses grapple with finding ways to reduce their innovation timelines.
Collaboration
While intelligent organisations have been able to work for years with partners, clients, vendors, and employees across the globe, the web-centric enterprise moves well beyond e-mail as the primary form of collaboration. By providing applications that enable tele presence meetings or face-to-face interactions via tablets, web-centric IT organisations can introduce the use of visual communication tools to help speed decision making and enhance productivity. The rise of high-bandwidth networks like Verizon 4G LTE is expanding the reach of corporate networks, helping to make video more and more commonplace.
Free or near-free tools such as Yammer allow organisations to communicate in real time, creating wikis, streams of news, and video-based discussions. While mostly a consumer tool, Google+ shows good promise with its ten-way video chat, among other features. Skype, arguably the de facto standard for online video chatting, continues to be a major player in both the business and consumer video chat experience
In this mix of change is a generational shift. Millennials in the workforce have a firm expectation of being able to use social tools to do their daily work. They don’t want to rely upon stand-alone tools. To them, collaboration is a conversation independent of the tools and platforms. The new generation is as comfortable interacting in a virtual crowd as the old generation was in physical meetings. Simply put, collaborative tools are going to define how people get work one, wherever they are. These collaborative tools support the ability for employees to engage with one another, with other businesses, and with their customers in non-traditional ways and are a necessary element of an agile business going forward.
Data dissemination
In this section, we present the model to estimate the number of refreshes required to disseminate a data item while maintaining a certain incoherency bound. There are two primary factors affecting the number of messages that are needed to maintain the coherency requirement.
Incoherency Bound Model
Consider a data item which needs to be disseminated at an incoherency bound Cite. new value of the data item will be pushed if the value deviates by more than C from the last pushed value. Thus, the number of dissemination messages will be proportional to the probability of value out greater than C for data value (t) at the source aggregator at the client, at times. A data item can be modelled as a discrete time random process [10] where each step is correlated with its previous step. In a push-based dissemination, a data source can follow one of the following schemes:
. RELATED WORK
A Web-centric application is one of the possible configurations that organize components of an enterprise middleware. This kind of application is widely spread because it results adequate when the use of more complex solutions represent an unnecessary overhead in runtime and development. Typically these applications are divided in three-tiers that groups presentation, logic, and data persistence. They are built around a Web server that controls the user interaction and performs the transactional logic.
3.1 Web centric application tier
We describe the implementation of a framework for the development of Web-centric applications for the Java 2 Enterprise Edition (J2EE). This work wants to cover three objectives: first, the definition of an architectural reference, with concrete components and base classes, for developing applications; second, the definition of a set of models to adequately support the application design having finite state machines as basic representation for the application logic; and third, the creation of a tool that allows development of those models, aimed to automatically generate some of the application code. As result of the integration of these three objectives we obtained an innovative approach and tool for applications development.
Client tier
In this tier the means for user/application interaction are given. Standard browsers can support this interaction by using plain HTML pages, dynamic HTML pages generated by Java Server Pages (JSP) technology, or Java Applets, with communicate with Web-standard protocols (HTTP, HTML XML). Clients can also interact through a Web-services interface, or even, stand-alone Java client applications, communicating through an HTTP or RMI-IIOP protocols. Exploiting Web-protocols, it is also possible to implement clients in other programming languages
Business classes
These are classes which belong to the Business logic layer. Business classes correspond to entities which have a semantic value in the application context, and therefore, they are present in the domain model of the system. They are traditional classes in the sense of object-oriented programming. Examples of Business classes, which can be found in common applications, are: “invoices”, “contracts”, “customers”, “items”, etc.
Business classes are characterized by their attributes that own a persistent state. Persistence is achieved indirectly by the support of Data objects, which belong to the data services layer. Instances of Business classes also have links to other instances, so that they can represent the associations, creations or relations of use, that exist in the real system. Methods of Business classes are grouped in two sets. Methods used to access and update the state, and to perform object services within the context of the application domain (e.g. methods set and get attributes). Methods used to create and manage instances and their access to the database. Finally, another characteristic of Business classes is the possibility of having shared accesses to their instances from different user sessions
. GENERALISATION PROPERTIES OF COMPETING
MARKETPLACES
The review carried out in Chapter 4 reveals a gap in the literature. there is no clear methodology for assessing the generalisation properties of competing market mechanisms. While economic mechanism design provides tools for dealing with this generalisation issue, through the design of incentive compatible mechanisms that generalise across all environments, these theoretical approaches only allow mechanisms to be designed for very restrictive settings, and competition between market mechanisms has not been considered. the first research objective of this chapter is to develop a methodology for analysing the generalisation abilities of competing market mechanisms. Such a methodology is important for designing and analysing many types of competitive market mechanism in simulated environments, where the generalisability of results is very important [21]. In that vein, a methodology of this type will be particularly useful to support other experimental simulation work later on in the thesis.
As discussed in Chapter 4, launched in 2007, the TAC Market Design Tournament [22] (CAT Tournament) has been used as a tool to encourage research into double auction mechanism rules. Entrants to CAT tournaments provide market mechanism agents called specialists, who must abstract as many traders as possible to their market. Each CAT game consists of potentially hundreds of different trading agents (provided by the organisers), and multiple
Competing specialist agents (provided by the entrants). the rich environment created by, not only many traders competing with each other, but also many market mechanisms competing to abstract traders, creates a potentially excellent test-bed for evaluating the effects of different double auction market mechanism rules, as used by the specialists. However, within such a complex environment, it may be the case that specialist performance is dependent on, or correlated with, some environmental factors. Given this, specialists may therefore be considered brittle if their performance greatly depends on environmental factors. the second research goal within this chapter is to better understand the characteristics of the mechanisms used by the specialists,
Discussions
In addition to fuzzy decision trees, many fuzzy techniques, including linguistic summaries a context- association rules and a fuzzy classification approach have been applied to data mining. However, these techniques assume that the data characteristics and the underlying associations hidden in the data are stable over time and they perform data mining in the whole database.
To deal with the data collected in different time periods, the maintenance of discovered association rules active data mining, and the measurement of difference between two datasets have been proposed in data mining literature. Incremental updating techniques can be used to update the discovered association rules if there are additions, deletions, or modifications of any tuples in a database after the discovery of a set of association rules. Active data mining is concerned with representing and querying the shape of the history of parameters for the discovered association rules. In a framework has been proposed to measure the difference between two datasets by building two models and measuring the amount of work required to transform one model to the other. Although these techniques can be used to track the variations in supports and confidences of association rules, none of them is developed for mining rule sets to discover and predict rule changes.
Although the mining of rule changes over time is an important problem, it has received little attention. To our best knowledge, in addition to our previous work, this problem has only been studied in concerned with finding whether a decision tree built in a time period is applicable in other time periods. Given two datasets collected at two different time periods, this approach builds a decision tree based on one of the datasets and then builds another based on the other dataset such that the latter tree uses the same attribute and chooses the same cut point for the attribute as the former at each step of partitioning. The approach, according to can be used to identify three categories of changes in the context of decision tree building: partition change, error rate change, and coverage change. Compared to instead of building a decision tree in the next time instance to ensure that it resembles the first, our approach is to mine for changes in association rules discovered at different time periods.
CONCLUSION
As per the mal result, it has become evident that the approach is a valuable approach from the broker's view it is very easy to keep track of the current situation of the stocks in the market irrespective of the time period. From the client's point of view it is very to decide whether to hold, buy or sell any particular stock based on its price movement information provided by the broker in the market. On subsequent evaluation we find that hybrid based approach is proved as a promising one for extracting some association rules of predictive nature from Indian stock market which could be used for prediction or recommendations in stock trading platforms. We have presented the result implementation of apriori mining algorithm. The approach is a valuable approach as it provides immediate information about the status of the stock, or multiple stocks together, for irrespective number of days.