
NIT6130 Peer To Peer Sharing And Cloud Storage
Data Collection
It is significant to design so many experiment procedures and make an analysis of the results when the experiment is completed. Since It is important to start with the areas when the collection of data is useful for the experiments. In the first set, multiple sources of data are found.
Data Sources
When the project begins, it is possible to make research about the problems, experiments of design and chose sources for the data collection. Hence mostly it is possible to choose three different categories of people. Hence It maintains all group people like every age group people, young students and professional’s. Therefore three different locations of work are:
- Community Places
- College or campus
- Corporations
A collection of Data
Therefore a table is maintained to record the data sources and organization record so that data is collected on that location. Since it is possible to collect the type of data, its format and charge fee and maintain appropriate research.
Data Storage
When the table is developed properly then the next step is to collect the data and put all the resources in the table. Hence the coming tables describe the raw data or whatever the processing is maintained by the people. There is a number of data stored in the system. It is possible not to forget the knowledge and multiple factors in the system. (“Data Collection (Integration) from Distributed Sources”, 2013)
Design and Implementation
Hence the next approach is to maintain the designing and steps for the implementation.Since It is possible to process the selection features and phases of dimensions for both design and implementation. The different task in the system is helpful in maintaining the design aspects of the system. Hence It is sufficient to fill the resources in the network and satisfy several aspects of the network. Different network criteria are maintained in the system and make data capable in achieving the system benefits. It is effective in the implementation of the resources according to the online gaming application and adds all the aspects in the design work.
Data Pre-processing
Data pre-processing is a beneficial part when all the people do not participate in the survey. Since It is supported to participate and don’t describe the answers mentioned in the system. When the data is evaluated then analysis the raw data in the system. Therefore keep filtering of data duplicity and check data samples and keep maintaining data records in the file. Hence the pre-processing of the network resources is analyzing each step in the network and demonstrates the features to support system capabilities. Since it forms the reduction in the information and makes accessibility in the network. It is easy to work in some conditions where the use of data is easy to demonstrate.
Feature Selection or dimension reduction
When the pre-processing of data is completed then the next work is to obtain the structures from the consequences and reduce the chances of selecting the random data resources. (Jamakovic, Bohnert & Karagiannis, 2013)
Experiment Designing
- Detailed Design Steps
Hence the current experiments of the project are based on a scenario which is helpful to purpose the scenarios. Since It is possible to select the services of Peer to Peer sharing of resources and maintain cloud storage which performs qualitative and quantitative approach. Since it is possible to collect the data and analyze the search for cloud applications and maintain services from amazon s3 and make a comparison to evaluate the approaches. Therefore the online gaming platform is helpful in achieving the services from the cloud and makes the use of essential features. It is capable of maintaining the peer to peer network connection with the resources and demonstrates its use in the system. Hence all these early demonstrations for the user is capable of the maintenance in the system.
Since it is possible to set some designed features which are helpful in categorizing the background details like age, gender, and education. Hence by this, an idea is generated about the people and their performance. It is adaptable to add the dimensions and selection criteria of the system.
Hence It is possible to use the statistics and the results. Therefore all the details are stored in the cloud and accessed with the help of the peer to peer internet connection. It is assigned to make use of services and achieve all the data in maintaining the features of the system.
Implementation
- Software and Tools
The next phase after the design and survey is implementation.Since it is possible to keep the survey on the main aspects of the system.
Result Analysis
Result Estimation
Therefore as per the network, it is possible to use the services of the cloud to store a large amount of data on it. Since it is useful to aware of the services of the cloud and makes a connection in the whole internet network. Therefore It is possible to share a large amount of data in the network with the need of an intermediate server. Hence there are multiple sources which support the cloud-based services for storing and accessing the information. Hence this estimation of the resources helps in enabling a large amount of data on the server. Since it is possible to perform multiple activities in the server. Hence in relevancy with the people and easy to share the data resources some services maintain satisfaction in holding a large amount of data. Hence It is possible to diagnose the entire relevancy in the system.
Result Summary
According to the current survey, the total of 100 in which 28% people have cloud services, 24% have used online gaming and approx. Therefore about one-third of the people maintain satisfaction in the work. . It is possible to make updations in the current applications and demonstrate the usage of system resources.
As per the results, it is possible to design the application with new features. Since it is possible to give preference to the people in the design and improve the online gaming application to maintain satisfaction with the users.
References
- Data Collection (Integration) from Distributed Sources. (2013). Encyclopedia Of Systems Biology, 519-519. doi: 10.1007/978-1-4419-9863-7_100313
- Fiat, A. (2003). Some Issues Regarding Search, Censorship, and Anonymity in Peer to Peer Networks. Automata, Languages And Programming, 33-33. doi: 10.1007/3-540-45061-0_3
- Fox, G. (2001). Peer‐to‐peer networks. Computing in Science & Engineering, 3(3), 75-77.
- Griffiths, M. D., Davies, M. N., & Chappell, D. (2004). Online computer gaming: a comparison of adolescent and adult gamers. Journal of adolescence, 27(1), 87-96.
- Hwang, K., & Li, D. (2010). Trusted cloud computing with secure resources and data coloring. IEEE Internet Computing, 14(5), 14-22.
- Jamakovic, A., Bohnert, T., & Karagiannis, G. (2013). Mobile Cloud Networking: Mobile Network, Compute, and Storage as One Service On-Demand. The Future Internet, 356-358. doi: 10.1007/978-3-642-38082-2_33
- Lv, Q., Cao, P., Cohen, E., Li, K., & Shenker, S. (2002, June). Search and replication in unstructured peer-to-peer networks. In Proceedings of the 16th international conference on Supercomputing(pp. 84-95). ACM.
- Wang, C., Wang, Q., Ren, K., & Lou, W. (2009, July). Ensuring data storage security in cloud computing. In Quality of Service, 2009. IWQoS. 17th International Workshop on(pp. 1-9). Ieee.
- Wang, F., Ghanea-Hercock, R. A., & Sun, Y. (2010). S. Patent No. 7,852,786. Washington, DC: U.S. Patent and Trademark Office.
- Waschke, M. (2012). Cloud Storage and Cloud Network. Cloud Standards, 115-144. doi: 10.1007/978-1-4302-4111-9_6
- Wilkinson, S., Boshevski, T., Brandoff, J., & Buterin, V. (2014). Storj a peer-to-peer cloud storage network.
- Wilkinson, S., Boshevski, T., Brandoff, J., & Buterin, V. (2014). Storj a peer-to-peer cloud storage network.