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Simulation Result's for Collabrative Caching Zonal Routing Protocol (CCZRP) for Mobile Adhoc Network: A Research Paper

by Vivek M Gulhane, D. N. Chaudhari
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 112 - Number 3
Year of Publication: 2015
Authors: Vivek M Gulhane, D. N. Chaudhari
10.5120/19644-1231

Vivek M Gulhane, D. N. Chaudhari . Simulation Result's for Collabrative Caching Zonal Routing Protocol (CCZRP) for Mobile Adhoc Network: A Research Paper. International Journal of Computer Applications. 112, 3 ( February 2015), 8-15. DOI=10.5120/19644-1231

@article{ 10.5120/19644-1231,
author = { Vivek M Gulhane, D. N. Chaudhari },
title = { Simulation Result's for Collabrative Caching Zonal Routing Protocol (CCZRP) for Mobile Adhoc Network: A Research Paper },
journal = { International Journal of Computer Applications },
issue_date = { February 2015 },
volume = { 112 },
number = { 3 },
month = { February },
year = { 2015 },
issn = { 0975-8887 },
pages = { 8-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume112/number3/19644-1231/ },
doi = { 10.5120/19644-1231 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:48:26.595016+05:30
%A Vivek M Gulhane
%A D. N. Chaudhari
%T Simulation Result's for Collabrative Caching Zonal Routing Protocol (CCZRP) for Mobile Adhoc Network: A Research Paper
%J International Journal of Computer Applications
%@ 0975-8887
%V 112
%N 3
%P 8-15
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In understanding of how individual quality patterns form and impact the social network is proscribed, however it is important for a deeper understanding of network dynamics and evolution. This question is basically unknown, partly, as a result of the issue in getting large-scale society-wide information that at the same time capture the high-powered info on individual movements and social interactions. Human quality patterns are complicated and distinct from one person to another. Nonetheless, actuated by tremendous potential advantages of modeling such patterns in sanctioning new mobile services and technologies, researchers have tried to capture salient characteristics of human quality. during this implementation paper discuss various routing protocols used for human quality model i. e. DSR, AODV, CHAMP and try to project a protocol for human quality model i. e. CCZRP (Collaborative Caching with Zonal Routing Protocol). Within the projected protocol use human quality model on CCZRP, CHAMP and DSR simulated on NS2 software system and compare them using different parameters.

References
  1. D. Easley and J. Kleinberg. Networks, crowds, and markets: Reasoning about a highly connected world. Cambridge University Press, 2010.
  2. G. Caldarelli. Scale-free networks: complex webs in nature and technology. Oxford University Press, 2007.
  3. M. Rivera, S. Soderstrom, and B. Uzzi. Dynamics of Dyads in Social Networks: Assortative, Relational, and Proximity Mechanisms. Annual Review of Sociology, 36:91{115, 2010.
  4. P. Juang, H. Oki, Y. Wang, M. Martonosi, L. S. Peh, and D. Rubenstein, Energy-efficient computing for wildlife tracking: design tradeoffs and early experiences with zebranet, Proc. ACM ASPLOS, 2002.
  5. J. Ott and D. Kutscher, A disconnection-tolerant transport for drive-thru internet environments, in Proceedings of IEEE INFO- COM, 2005.
  6. D. Brockmann, L. Hufnagel, and T. Geisel. The scaling laws of human travel. Nature, 439(7075):462{465, 2006.
  7. M. Gonzfialez, C. Hidalgo, and A. -L. Barabffasi. Understanding individual human mobility patterns. Nature, 453(7196):779{782, 2008.
  8. C. Song, T. Koren, P. Wang, and A. -L. Barabffasi. Modelling the scaling properties of human mobility. Nature Physics, 2010.
  9. N. Eagle and A. Pentland. Eigenbehaviors: Identifying structure in routine. Behavioral Ecology and Sociobiology, 63(7):1057{1066, 2009.
  10. C. Song, Z. Qu, N. Blumm, and A. -L. Barabasi. Limits of predictability in human mobility. Science, 327(5968):1018, 2010.
  11. M. Morzy. Prediction of moving object location based on frequent trajectories. In ISCIS, pages 583{592, 2006.
  12. M. Morzy. Mining frequent trajectories of moving objects for location prediction. In MLDM, pages 667{680, 2007.
  13. H. Jeung, Q. Liu, H. T. Shen, and X. Zhou. A hybrid prediction model for moving objects. In ICDE, pages 70,79, 2008
  14. G. Yavas, D. Katsaros, O. Ulusoy, and Y. Manolopoulos. A data mining approach for location prediction in mobile environments. Data Knowl. Eng. , 54(2):121{146, 2005.
  15. F. Giannotti, M. Nanni, and D. Pedreschi. Efficient mining of temporally annotated sequences. In SDM, 2006.
  16. A. Monreale, F. Pinelli, R. Trasarti, and F. Giannotti. Wherenext: a location predictor on trajectory pattern mining. In KDD, pages 637{646, 2009.
  17. D. Liben-Nowell and J. M. Kleinberg. The link prediction problem for social networks. In CIKM, pages 556{559, 2003.
  18. M. Al Hasan, V. Chaoji, S. Salem, and M. Zaki. Link prediction using supervised learning. In SDM: Workshop on Link Analysis, Counter-terrorism and Security, 2006.
  19. C. Wang, V. Satuluri, and S. Parthasarathy. Local probabilistic models for link prediction. In ICDM, pages 322{331, 2007.
  20. R. Lichtenwalter, J. T. Lussier, and N. V. Chawla. New perspectives and methods in link prediction. In KDD, pages 243{252, 2010.
  21. R. Lambiotte, V. Blondel, C. De Kerchove, E. Huens, C. Prieur, Z. Smoreda, and P. Van Dooren. Geographical dispersal of mobile communication networks. Physica A: Statistical Mechanics and its Applications, 387(21):5317{5325, 2008.
  22. L. Backstrom, E. Sun, and C. Marlow. Find me if you can: improving geographical prediction with social and spatial proximity. In WWW, pages 61{70, 2010.
  23. N. Eagle, A. Pentland, and D. Lazer. Inferring friendship network structure by using mobile phone data. Proceedings of the National Academy of Sciences, 106(36):15274, 2009.
  24. J. Cranshaw, E. Toch, J. Hong, A. Kittur, and N. Sadeh. Bridging the gap between physical location and online social networks. In Ubicomp, pages 119{128, New York, NY, USA, 2010. ACM.
  25. Rongxing Lu "Pi: A Practical Incentive Protocol for Delay Tolerant Networks", Ieee Transactions On Wireless Communications, Vol. 9, No. 4, April 2010
  26. Perkins, C. and Royer, E. and Das, S. , "Ad hoc On demand Distance Vector (AODV) routing," RFC 3561, Jul. 2003.
  27. M. Marina and S. Das, "On-demand multipath distance vector routing in ad hoc networks," in Proc. IEEE ICNP '01, 2001, pp. 14–23.
  28. C. Song, T. Koren, P. Wang, and A. -L. Barabasi. Modeling the scaling properties of human mobility. Nature Physics, 2010.
  29. ADD HOME. Mobility management and housing project. 2009.
  30. Rahul C. Basole. The value and impact of mobile information and communication technologies. Proceedings of the IFAC Symposium, Atlanta, GA. , 2004.
  31. P. Nain, D. Towsley, B. Liu, and Z. Liu, "Properties of Random Direction Models," INRIA technical report RR-5284,July 2004.
  32. Vasanthi. V and Hemalatha. M, 2012. A Proportional Analysis of Dissimilar Mobility Models in Ad-Hoc Sensor Network over DSR Protocol. Int. J. Computer Applications 42 (15); PPno. 26-32.
  33. M. Sanchez and P. Manzoni, A Java-Based Ad Hoc Networks Simulator, in Proceedings of the SCS Western Multiconference Web-based Simulation Track, Jan. 1999.
  34. K. Zhou, L. Meng, Z. Xu, G. Li and J. Hua, "A Dynamic Clustering-Based Routing Algorithm for Wireless Senor Networks," Information Technology Journal, Vol. 7, No. 4, 2008, pp. 694-697.
  35. A. D. Amis, R. Prakash, T. H. P. Vuong and D. T. Huynh, "Max-Min D-Cluster Formation in Wireless Ad-Hoc Networks," Proceedings of the IEEE 9th Annual Joint Conference of the IEEE Computer and Communications Societies, Tel Aviv, 26-30 March 2000, pp. 32-41.
  36. Y. He, W. S. Yoon and J. H. Kim, "Multi-level Cluster-ing Architecture for Wireless Sensor Networks," Infor-mation Technology Journal, Vol. 5, No. 1, 2006, pp. 188-191.
  37. W. Liu and J. Yu, "Energy Efficient Clustering and Rout-ing Scheme for Wireless Sensor Networks," Proceeding of the IEEE International Conference on Intelligent Com-puting and Intelligent Systems, Shanghai, 20-22 Novem-ber 2009, pp. 612-616.
  38. Perkins, C. and Royer, E. and Das, S. , "Ad hoc On demand Distance Vector (AODV) routing," RFC 3561, Jul. 2003.
Index Terms

Computer Science
Information Sciences

Keywords

Human mobility Link Prediction Routing Parameters of Human Mobility Social Network CCZRP Routing Protocol

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