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A scalable server architecture for mobile presence services

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Sree Chinni

In this we propose an efficient and scalable server architecture, called Presence Cloud, which enables mobile presence services to support large-scale social network applications. When a mobile user joins a network, Presence Cloud searches for the presence of his/her friends and notifies them arrival.

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Abstract Existing System Proposed System HARDWARE System Configuration SOFTWARE Configuration UML Diagrams Modules Data Tables Conclusion & Reference
Social network services are growing and many people are communicating with the world using them. It is essential because it maintains each mobile users presence information, such as the current status (online/offline), GPS location and network address. If presence updates occur frequently, the enormous number of message distributed by presence servers may lead to scalability problem.
To address this problem , we propose an efficient and scalable server architecture which is called PresenceCloud PresenceCloud organizes presence servers into server - to server architecture. The performance can be analysed in terms of search cost and search satisfaction level.
3 popular commercial IM systems are : AIM , Microsoft MSN , Yahoo! Messenger. They leverage some form of centralized clusters. Centralized clusters are used to provide presence services. Storing the presence is one of the most messaging traffic in these instant messaging system.
Peer to peer SIP has been proposed to remove centralized server. P2PSIP reduces the maintenance costs and failures in server based deployment These clients are organized in DHT Thus presence cloud can support large scale social network system service among thousand of servers.
Pentium-3 processor 1.1 GHz Speed 256 MB RAM 20 GB Hard Disk 1.44 MB Floppy Drive Standard Windows Key Board Two or Three Button Mouse SVGA Monitor
Operating System: Windows 95/98/2000/XP Application Server: Tomcat 5.0/6.X Front End: HTML , JAVA , JSP Scripts: Java Script Server side scripts: Java Server Pages Database: MySQL Database Connectivity: JDBC
A scalable server architecture for mobile presence services
A scalable server architecture for mobile presence services
A scalable server architecture for mobile presence services
A scalable server architecture for mobile presence services
A scalable server architecture for mobile presence services
Presence Cloud server overlay. One-hop caching strategy. Directed buddy search.
The Presence Cloud server overlay construction algorithm organizes the PS nodes into a server-to-server overlay, which provides a good low-diameter overlay property. The low-diameter property ensures that a PS node only needs two hops to reach any other PS nodes.
To improve the efficiency of the search operation, Presence Cloud requires a caching strategy to replicate presence information of users. In order to adapt to changes in the presence of users, the caching strategy should be asynchronous and not require expensive mechanisms for distributed agreement.
We contend that minimizing searching response time is important to mobile presence services. Thus, the buddy list searching algorithm of Presence Cloud coupled with the two-hop overlay and one-hop caching strategy ensures that Presence Cloud can typically provide swift responses for a large number of mobile users.
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Presence Server
In this paper, we have presented Presence Cloud, a scalable server architecture that supports mobile presence services in large-scale social network services. We have shown that Presence Cloud achieves low search latency and enhances the performance of mobile presence services. In addition, we discussed the scalability problem in server architecture designs, and introduced the buddy-list search problem, which is a scalability problem in the distributed server architecture of mobile presence services.
Through a simple mathematical model, we show that the total number of buddy search messages increases substantially with the user arrival rate and the number of presence servers. The results of simulations demonstrate that Presence Cloud achieves major performance gains in terms of the search cost and search satisfaction. Overall, Presence Cloud is shown to be a scalable mobile presence service in large-scale social network services.
Facebook, http://www.facebook.com. Twitter, http://twitter.com. Foursquare http://www.foursquare.com. Google latitude, http://www.google.com/intl/enus/latitude/intro.html. Buddycloud, http://buddycloud.com. R. B. Jennings, E. M. Nahum, D. P. Olshefski, D. Saha, Z.-Y. Shae, and C. Waters, A study of internet instant messaging and chat protocols, IEEE Network, 2006. Gobalindex, http://www.skype.com/intl/en-us/support/user- guides/p2pexplained/. Z. Xiao, L. Guo, and J. Tracey, Understanding instant messaging traffic characteristics, Proc. of IEEE ICDCS, 2007. C. Chi, R. Hao, D. Wang, and Z.-Z. Cao, Ims presence server: Traffic analysis and performance modelling, Proc. of IEEE ICNP, 2008.
http://java.sun.com http://www.sourcefordgde.com http://www.networkcomputing.com/ http://www.roseindia.com/ http://www.java2s.com/

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A scalable server architecture for mobile presence services

  • 2. Abstract Existing System Proposed System HARDWARE System Configuration SOFTWARE Configuration UML Diagrams Modules Data Tables Conclusion & Reference
  • 3. Social network services are growing and many people are communicating with the world using them. It is essential because it maintains each mobile users presence information, such as the current status (online/offline), GPS location and network address. If presence updates occur frequently, the enormous number of message distributed by presence servers may lead to scalability problem.
  • 4. To address this problem , we propose an efficient and scalable server architecture which is called PresenceCloud PresenceCloud organizes presence servers into server - to server architecture. The performance can be analysed in terms of search cost and search satisfaction level.
  • 5. 3 popular commercial IM systems are : AIM , Microsoft MSN , Yahoo! Messenger. They leverage some form of centralized clusters. Centralized clusters are used to provide presence services. Storing the presence is one of the most messaging traffic in these instant messaging system.
  • 6. Peer to peer SIP has been proposed to remove centralized server. P2PSIP reduces the maintenance costs and failures in server based deployment These clients are organized in DHT Thus presence cloud can support large scale social network system service among thousand of servers.
  • 7. Pentium-3 processor 1.1 GHz Speed 256 MB RAM 20 GB Hard Disk 1.44 MB Floppy Drive Standard Windows Key Board Two or Three Button Mouse SVGA Monitor
  • 8. Operating System: Windows 95/98/2000/XP Application Server: Tomcat 5.0/6.X Front End: HTML , JAVA , JSP Scripts: Java Script Server side scripts: Java Server Pages Database: MySQL Database Connectivity: JDBC
  • 14. Presence Cloud server overlay. One-hop caching strategy. Directed buddy search.
  • 15. The Presence Cloud server overlay construction algorithm organizes the PS nodes into a server-to-server overlay, which provides a good low-diameter overlay property. The low-diameter property ensures that a PS node only needs two hops to reach any other PS nodes.
  • 16. To improve the efficiency of the search operation, Presence Cloud requires a caching strategy to replicate presence information of users. In order to adapt to changes in the presence of users, the caching strategy should be asynchronous and not require expensive mechanisms for distributed agreement.
  • 17. We contend that minimizing searching response time is important to mobile presence services. Thus, the buddy list searching algorithm of Presence Cloud coupled with the two-hop overlay and one-hop caching strategy ensures that Presence Cloud can typically provide swift responses for a large number of mobile users.
  • 21. In this paper, we have presented Presence Cloud, a scalable server architecture that supports mobile presence services in large-scale social network services. We have shown that Presence Cloud achieves low search latency and enhances the performance of mobile presence services. In addition, we discussed the scalability problem in server architecture designs, and introduced the buddy-list search problem, which is a scalability problem in the distributed server architecture of mobile presence services.
  • 22. Through a simple mathematical model, we show that the total number of buddy search messages increases substantially with the user arrival rate and the number of presence servers. The results of simulations demonstrate that Presence Cloud achieves major performance gains in terms of the search cost and search satisfaction. Overall, Presence Cloud is shown to be a scalable mobile presence service in large-scale social network services.
  • 23. Facebook, http://www.facebook.com. Twitter, http://twitter.com. Foursquare http://www.foursquare.com. Google latitude, http://www.google.com/intl/enus/latitude/intro.html. Buddycloud, http://buddycloud.com. R. B. Jennings, E. M. Nahum, D. P. Olshefski, D. Saha, Z.-Y. Shae, and C. Waters, A study of internet instant messaging and chat protocols, IEEE Network, 2006. Gobalindex, http://www.skype.com/intl/en-us/support/user- guides/p2pexplained/. Z. Xiao, L. Guo, and J. Tracey, Understanding instant messaging traffic characteristics, Proc. of IEEE ICDCS, 2007. C. Chi, R. Hao, D. Wang, and Z.-Z. Cao, Ims presence server: Traffic analysis and performance modelling, Proc. of IEEE ICNP, 2008.
  • 24. http://java.sun.com http://www.sourcefordgde.com http://www.networkcomputing.com/ http://www.roseindia.com/ http://www.java2s.com/