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GLOBALSOFT TECHNOLOGIES 
IEEE PROJECTS & SOFTWARE DEVELOPMENTS 
IEEE FINAL YEAR PROJECTS|IEEE ENGINEERING PROJECTS|IEEE STUDENTS PROJECTS|IEEE 
BULK PROJECTS|BE/BTECH/ME/MTECH/MS/MCA PROJECTS|CSE/IT/ECE/EEE PROJECTS 
CELL: +91 98495 39085, +91 99662 35788, +91 98495 57908, +91 97014 40401 
Visit: www.finalyearprojects.org Mail to:ieeefinalsemprojects@gmail.com 
On Social Delay-Tolerant Networking Aggregation, Tie 
Detection, and Routing 
Abstract 
Social-based routing protocols have shown their promising capability to improve the message delivery 
efficiency in Delay Tolerant Networks (DTNs). The efficiency greatly relies on the quality of the 
aggregated social graph that is determined by the metrics used to measure the strength of social 
connections. In this paper, we propose an improved metrics that leads to high-quality social graph by 
taking both frequency and duration of contacts into consideration. Furthermore, to improve the 
performance of social-based message transmission, we systematically study the community evolution 
problem that has been little investigated in the literation. Distributed algorithms based on the obtained 
social graph are developed such that the overlapping communities and bridge nodes (i.e., connecting 
nodes between communities) can be dynamically detected in an evolutionary social network. Finally, we 
take all the results above into our social-based routing design. Extensive trace-driven simulation results 
show that our routing algorithm outperforms existing social-based forwarding strategies significantly. 
Existing system 
Social-based routing protocols have shown their promising capability to improve the message delivery 
efficiency in Delay Tolerant Networks (DTNs). The efficiency greatly relies on the quality of the
aggregated social graph that is determined by the metrics used to measure the strength of social 
connections. 
Proposed system 
In this paper, we propose an improved metrics that leads to high-quality social graph by taking both 
frequency and duration of contacts into consideration. Furthermore, to improve the performance of 
social-based message transmission, we systematically study the community evolution problem that has 
been little investigated in the literation. Distributed algorithms based on the obtained social graph are 
developed such that the overlapping communities and bridge nodes (i.e., connecting nodes between 
communities) can be dynamically detected in an evolutionary social network. Finally, we take all the 
results above into our social-based routing design. Extensive trace-driven simulation results show that 
our routing algorithm outperforms existing social-based forwarding strategies significantly. 
SYSTEM CONFIGURATION:- 
HARDWARE CONFIGURATION:- 
 Processor - Pentium –IV 
 Speed - 1.1 Ghz 
 RAM - 256 MB(min) 
 Hard Disk - 20 GB 
 Key Board - Standard Windows Keyboard 
 Mouse - Two or Three Button Mouse 
 Monitor - SVGA 
SOFTWARE CONFIGURATION:- 
 Operating System : Windows XP 
 Programming Language : JAVA
 Java Version : JDK 1.6 & above.

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IEEE 2014 DOTNET PARALLEL DISTRIBUTED PROJECTS On social delay tolerant networking aggregation, tie detection, and routing

  • 1. GLOBALSOFT TECHNOLOGIES IEEE PROJECTS & SOFTWARE DEVELOPMENTS IEEE FINAL YEAR PROJECTS|IEEE ENGINEERING PROJECTS|IEEE STUDENTS PROJECTS|IEEE BULK PROJECTS|BE/BTECH/ME/MTECH/MS/MCA PROJECTS|CSE/IT/ECE/EEE PROJECTS CELL: +91 98495 39085, +91 99662 35788, +91 98495 57908, +91 97014 40401 Visit: www.finalyearprojects.org Mail to:ieeefinalsemprojects@gmail.com On Social Delay-Tolerant Networking Aggregation, Tie Detection, and Routing Abstract Social-based routing protocols have shown their promising capability to improve the message delivery efficiency in Delay Tolerant Networks (DTNs). The efficiency greatly relies on the quality of the aggregated social graph that is determined by the metrics used to measure the strength of social connections. In this paper, we propose an improved metrics that leads to high-quality social graph by taking both frequency and duration of contacts into consideration. Furthermore, to improve the performance of social-based message transmission, we systematically study the community evolution problem that has been little investigated in the literation. Distributed algorithms based on the obtained social graph are developed such that the overlapping communities and bridge nodes (i.e., connecting nodes between communities) can be dynamically detected in an evolutionary social network. Finally, we take all the results above into our social-based routing design. Extensive trace-driven simulation results show that our routing algorithm outperforms existing social-based forwarding strategies significantly. Existing system Social-based routing protocols have shown their promising capability to improve the message delivery efficiency in Delay Tolerant Networks (DTNs). The efficiency greatly relies on the quality of the
  • 2. aggregated social graph that is determined by the metrics used to measure the strength of social connections. Proposed system In this paper, we propose an improved metrics that leads to high-quality social graph by taking both frequency and duration of contacts into consideration. Furthermore, to improve the performance of social-based message transmission, we systematically study the community evolution problem that has been little investigated in the literation. Distributed algorithms based on the obtained social graph are developed such that the overlapping communities and bridge nodes (i.e., connecting nodes between communities) can be dynamically detected in an evolutionary social network. Finally, we take all the results above into our social-based routing design. Extensive trace-driven simulation results show that our routing algorithm outperforms existing social-based forwarding strategies significantly. SYSTEM CONFIGURATION:- HARDWARE CONFIGURATION:-  Processor - Pentium –IV  Speed - 1.1 Ghz  RAM - 256 MB(min)  Hard Disk - 20 GB  Key Board - Standard Windows Keyboard  Mouse - Two or Three Button Mouse  Monitor - SVGA SOFTWARE CONFIGURATION:-  Operating System : Windows XP  Programming Language : JAVA
  • 3.  Java Version : JDK 1.6 & above.