P2P Applications in 4G/5G Networks Using D2D Communications Based on Social Attributes of Users

Authors

  • B. Eleena Assistant Professor,ECE Department Bhoj Reddy Engineering College for Women Author
  • Veldanda Anusha B. Tech Students, Department Of Ece, Bhoj Reddy Engineering College For Women, India. Author
  • Baddam Archana B. Tech Students, Department Of Ece, Bhoj Reddy Engineering College For Women, India. Author
  • Kandula Divya B. Tech Students, Department Of Ece, Bhoj Reddy Engineering College For Women, India. Author

Abstract

P2P (peer-to-peer) systems have gained popularity 
in wireless communication due to increase in 
Internet usage and preservation of autonomy of 
the participating nodes. These systems are become 
useful in sharing contents. P2P systems have some 
unique characteristics like autonomy, scalability 
and cost efficiency, etc. which separate these 
systems from other distributed systems.P2P 
applications can be incorporated in D2D (Device
to-Device) communication which has been 
considered as potential technology in 4G (4th 
Generation) and 5G (5th Generation) cellular 
networks. In D2D communications, two users’ 
equipments directly communicate with each other 
without involvement of the eNB (Evolved Node B). 
5G network is going to support huge number of 
devices with heterogeneous characteristics. 
The traditional centralized network support can’t 
accommodate huge users demand. P2P 
applications with help of D2D communication can 
reduce the burden of eNB and offload the 
workload. The social attributes of users can also 
play crucial role in building P2P system among 
users. So, the social attributes-based networks can 
integrate the social attributes like mobility pattern, 
social relationship, professional relationship etc. 
of users in P2P application based on D2D 
communication. We propose network assisted and 
social attributes based content sharing application 
(P2P system) using D2D communication for 
4G/5G cellular networks.

Downloads

Download data is not yet available.

References

1. Abdun Naser Mahmood, Christopher Leckie

and Parampalli Udaya. IEEE Transactions on

Knowledge and Data Engineering,Vol. 20, No. 6,

pp. 752-767, June 2008.

2. Agarwal, P., Alam, M.A. and Biswas, R.

Computer Engineering and Applications, pp. 365-

368, March 2010.

3. Aggarwal, C.C. and Yu, IEEE Transactions on

Knowledge and Data Engineering, Vol. 14, No. 2,

pp. 210-225, March/April 2002.

4. Ana L.N. Fred and Anil K. Jain. ombining

Multiple Clusterings Analysis and Machine

Intelligence, Vol. 27, No. 6, pp.835-850, June 2005.

5. Atev, S., Miller, G. and Papanikolopoulos,

N.P.

IEEE Transactions on Intelligent

Transportation Systems, Vol. 11, Issue 3, pp. 647

657, September 2010.

6. Bandyopadhyay, S., Giannella, C., Maulik,

U., Kargupta, H., Liu, K. and Datta, S. -to-Peer

Information Sciences, Vol. 176, Issue 14, pp. 1952

1985, July 2006.

7. Bagnall, A.J. and Janacek, Clustering Time

Series from ARMA Tenth ACM SIGKDD

International Conference on Knowledge Discovery

and Data Mining, pp. 49-58, 2004.

8. Beliakov, G., James, S. and Gang Li. Learning

Choquet-Integral Fuzzy Systems, Vol. 19, Issue 3,

pp. 562-574, June 2011.

9. Bi-Ru Dai, Jen-Wei Huang, Mi-Yen Yeh and

Ming-Syan Chen. Transactions on Knowledge and

Data Engineering, Vol. 18, No. 9, pp. 1166-1180,

September 2006.

10. Brickey, J., Walczak, S. and Burgess, T.

Comparing

Semi

Automated

Clustering

Transactions on Software Engineering, Issue 99,

pp. 1-1, June 2011.

11. Dai, B.-R., Huang, J.-W., Yeh, M.-Y. and

Chen, M.-S. IEEE Transactions on Knowledge and

Data Engineering, Vol. 18, No. 9, pp. 1166-1180,

September 2006.

12. Damaris

Pascual,

Filiberto -Pattern

Recognition Letters, pp. 454-461, July 2009.

13. Datta, S., Bhaduri, K., Giannella, C., Wolff, R.

and Kargupta, H. -to Transactions on Internet

Computing, Vol. 10, No. 4, pp. 18-26, July/ August

2006.

14. Eric Hsueh-Chan Lu, Vincent S. Tseng and

Philip

S.

Cluster-Based Temporal Mobile

Sequential Patterns in Location-Based Engineering,

Vol. 23, No. 6, pp. 914-927, June 2011.

15. Fuyuan Cao, Jiye Liang, Liang Bai,

Xingwang Zhao and Chuangyin - IEEE

Transactions on Fuzzy System, Vol. 18, Issue 5, pp.

872-882, October 2010.

16. Gancarski, P. and Blansche, A. Darwinian,

Lamarckian, and Baldwinian (Co) Evolutionary

Approaches for Feature Weighting in K -means-

IEEE Transactions on Evolutionary Computation,

Vol. 12, Issue 5, pp. 617-629, October 2008.

17. Haiying Shen and Kai Hwang. cality

Preserving Clustering and Discovery of Resources

in Wide-Area Distributed Computational IEEE

Transactions on Networking, Vol. 61, No. 4,pp.

458-473, April 2012.

18. He, Q., Yan, J., Yang, Y., Kowalczyk, R. and

Jin, H. A Decentralized Service Discovery

Approach on Peer-to Transactions on Services

Computing, Issue 99, pp.1-1, June 2011.

19. Hefeeda, M., Cheng-Hsin Hsu and

Mokhtarian, K. Evaluation of a Proxy Cache for

Peer- to Transactions on Computers, Vol. 60, Issue

7, pp. 964-977, July 2011.

20. Huang, J.Z., Ng, M.K., Rong, H. and Li,

Weighting in K Analysis and Machine Intelligence,

Vol. 27, No. 5, pp. 657-668, May 2

Downloads

Published

2025-06-18

Issue

Section

Articles

How to Cite

P2P Applications in 4G/5G Networks Using D2D Communications Based on Social Attributes of Users . (2025). International Journal of Multidisciplinary Engineering In Current Research, 10(6), 250-256. https://ijmec.com/index.php/multidisciplinary/article/view/805