Heterogeneous Cloud Radio Access Network
|P. Singh1 , N. Singh2 , S. Rani3|
1 Dept. of CSE, Giani Zail Singh Campus Collage of Eng. and Technology (PTU,) Bathinda, India.
2 Dept. of CSE, Giani Zail Singh Campus Collage of Eng. and Technology (PTU,) Bathinda, India.
3 Dept. of CSE, Giani Zail Singh Campus Collage of Eng. and Technology (PTU,) Bathinda, India.
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Section:Research Paper, Product Type: Journal Paper
Volume-5 , Issue-9 , Page no. 46-51, Sep-2017
Online published on Sep 30, 2017
Copyright © P. Singh, N. Singh, S. Rani . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: P. Singh, N. Singh, S. Rani, “Heterogeneous Cloud Radio Access Network”, International Journal of Computer Sciences and Engineering, Vol.5, Issue.9, pp.46-51, 2017.
MLA Style Citation: P. Singh, N. Singh, S. Rani "Heterogeneous Cloud Radio Access Network." International Journal of Computer Sciences and Engineering 5.9 (2017): 46-51.
APA Style Citation: P. Singh, N. Singh, S. Rani, (2017). Heterogeneous Cloud Radio Access Network. International Journal of Computer Sciences and Engineering, 5(9), 46-51.
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|To reduce the several in between base station processing in heterogeneous network we connect all the heterogeneous Network with the main more powerful central server on cloud and in this way in this Network name is HCRAN, for reducing the cost and load in this paper we properly study existing system and then some problems that present in the previous Network reduce or eliminate in this Network ,like overloading ,Energy consumption, reduced in this Network but Throughput increased and dead nodes decreases in this Network .In this thesis paper we increases the overall performance of the HCRAN by using the base station shifting technique and changes the method of devices connected with the base-station in the previous HCRAN the devices connect with the base station according to the distance but in this paper the distance and energy factor considered for connection for improving the performance of system ,in this way by implementing this techniques in the HCRAN the energy consumption and overloading, main problems in the previous HCRAN resolves in this system. The overall work divided in three scenario in the first scenario the base stations shifting technique that is new technique shows in simulations results and in the second scenario the connection process between the base- stations and devices in system shows according to distance and energy factor and in the third scenario the overall work combined and shows the wake up situations after sleep and connection with the nearest base- station shows in this thesis paper.|
|Key-Words / Index Term :|
|Energy consumption, Throughput, No of calls drop, No of dead nodes|
 P.S.Negi, “A survey of data storage and retrieval in cloud computing”, In IJCSE, Vol.8, Issue 16, pp.202-205, 2016.
 Park, J.H.Kim, “Swarm intelligence-based sensor network deployment strategy”, In IEEE , Vol. 4, Issue 10, pp. 1-6,2010.
 Li. G and Li. J., “ Global weighted fairness guaranteed congestion avoidance protocol for wireless sensor networks”, In IEEE, Vol. 5, Issue 11, pp. 601-605, 2011.
 M. Cheng, X. Gong, and L. Cain, “ Joint routing and link rate allocation under bandwidth and energy constraints in sensor networks”, In IEEE , Vol. 8, Issue 9, pp. 3770-3779, 2009].
 Tseng, Cheng, C.S, “ Adaptive coverage-preserving routing protocol for wireless sensor network”, In Sensing Technology (ICST), 2013 Seventh International Conference”, China, pp. 730-734,2013.
 P. Minet, and S. Mahfoudh, “An energy efficient routing based on OLSR in wireless ad hoc and sensor networks”, “In Advanced Information Networking and Applications-Workshops, 2008. AINAW 2008. 22nd International Conference on IEEE”, America, pp. 1253-1259, 2008.
 Lee, S.Youngish, “Connectivity restoration in a partitioned wireless sensor network with assured fault tolerance”, In Ad Hoc Networks, Vol. 4, Issue 15, pp. 1-19, 2015.
 Yan, J. Jiao, H, “A self-adaptive clustering algorithm for wireless sensor network”, In 2009 5th International Conference on Wireless Communications, Networking and Mobile Computing”, China, pp. 1-4, 2009.
 M. Khan, Mangos, “A survey of computation offloading strategies for performance improvement of applications running on mobile devices, “Journal of Network and Computer Applications”, Vol. 7, Issue 13, pp. 28-40, 2013.