29-08-2013, 04:51 PM
Storing and Indexing Spatial Data in P2P Systems
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Abstract
The peer-to-peer (P2P) paradigm has become very popular for storing and sharing required information in a totally decentralized manner. In existing, research focused on P2P systems that host 1D data. At present, the need for P2P applications with multidimensional data has emerged, motivating research on P2P systems that manage such information. Our focus is on structured P2P systems that share spatial information. We present SPATIALP2P, a totally decentralized indexing and searching framework that is suitable for spatial data. SPATIALP2P supports P2P applications in which spatial information of various sizes can be dynamically inserted or deleted, and peers can join or leave.
SCOPE:
The peer-to-peer (P2P) paradigm has become very popular for storing and sharing required information in a totally decentralized manner. In existing, research focused on P2P systems that host 1D data. At present, the need for P2P applications with multidimensional data has emerged, motivating research on P2P systems that manage such information. Our focus is on structured P2P systems that share spatial information.
Introduction:
THE peer-to-peer (P2P) paradigm has become very popular for storing and sharing information in a totally
Decentralized manner. Typically, a P2P system is a distributed environment formed by autonomous peers that
Operate in an independent manner. Each peer stores a part of the available information and maintains links (indexes) to other peers. P2P systems. Provide a method to distribute the available information to peers guarantee the retrieval of any information that exists in the system achieve a reasonable index size for all peers,
Achieve a reasonable search path for any search performed in the system. Maintain a low cost for updating peer indexes when peers join or leave, and Achieve data and search load balancing, i.e., there are no peers overloaded with stored data and there are no traffic bottleneck in the network. Until recently, research has focused mostly on P2P systems that handle 1D data such as strings and numbers. However, the need for P2P applications that manage multidimensional data has emerged. These systems pose additional requirements that stem from the particularities of such data.
ECONOMICAL Feasibility
This study is carried out to check the economic impact that the system will have on the organization. The amount of fund that the company can pour into the research and development of the system is limited. The expenditures must be justified. Thus the developed system as well within the budget and this was achieved because most of the technologies used are freely available. Only the customized products had to be purchased.
TECHNICAL FEASIBILITY
This study is carried out to check the technical feasibility, that is, the technical requirements of the system. Any system developed must not have a high demand on the available technical resources. This will lead to high demands on the available technical resources. This will lead to high demands being placed on the client. The developed system must have a modest requirement, as only minimal or null changes are required for implementing this system.
Existing System
SPATIALP2P distributes the spatial information to peers and guarantees the retrieval of any spatial area that exists in the system with low space and time complexity. These Systems can handle only 1D data such as strings and numbers. Storing and sharing the spatial information in a centralized manner.
Proposed System
The Proposed System uses two techniques in the first category are based on the idea that 1D index can be reused in order to manage multidimensional data, if the dimensionality is reduced to one. This idea was the first to be explored. Techniques in the second category are based on the idea that centralized hierarchical indexes can be reused to manage dispersed multidimensional data, if they are properly distributed.
THE .NET FRAMEWORK
The .NET Framework is a new computing platform that simplifies application development in the highly distributed environment of the Internet.
For example, ASP.NET hosts the runtime to provide a scalable, server-side environment for managed code. ASP.NET works directly with the runtime to enable Web Forms applications and XML Web services, both of which are discussed later in this topic.
The following illustration shows the relationship of the common language runtime and the class library to your applications and to the overall system. The illustration also shows how managed code operates within a larger architecture.
NET Framework Class Library:
The .NET Framework class library is a collection of reusable types that tightly integrate with the common language runtime. The class library is object oriented, providing types from which your own managed code can derive functionality. This not only makes the .NET Framework types easy to use, but also reduces the time associated with learning new features of the .NET Framework. In addition, third-party components can integrate seamlessly with classes in the .NET Framework.
For example, the .NET Framework collection classes implement a set of interfaces that you can use to develop your own collection classes. Your collection classes will blend seamlessly with the classes in the .NET Framework.
As you would expect from an object-oriented class library, the .NET Framework types enable you to accomplish a range of common programming tasks, including tasks such as string management, data collection, database connectivity, and file access. In addition to these common tasks, the class library includes types that support a variety of specialized development scenarios.
Conclusion
Research in P2P systems has recently expanded in the domain of multidimensional data. The techniques that have been proposed until now belong to two broad categories. Techniques in the first category are based on the idea that 1D indexes can be reused in order to manage multidimensional data, if the dimensionality is reduced to one. This idea was the first to be explored. Techniques in the second category are based on the idea that centralized hierarchical indexes can be reused to manage dispersed multidimensional data, if they are properly distributed. More elaborated solutions