Sunil Kumar

Work place: I. K. Gujral Punjab Technical University, Kapurthala (Punjab), India

E-mail: sunilymca2k5@gmail.com

Website:

Research Interests: Computational Science and Engineering, Computer systems and computational processes, Computer Networks, Network Architecture, Network Security, Data Structures and Algorithms

Biography

Sunil Kumar received the B.Tech. degree in Computer Science & Engineering from Bundelkhand University, Jhansi, India, in 2001 and the M.Tech. degree in Computer Engineering from the Maharshi Dayanand University, Rohtak, India, in 2007. His research interests lie in the area of Computer Networks, Wireless Networks and Cryptography & Network Security. He is currently pursuing Ph.D in Computer Science & Engineering from I. K. Gujral Punjab Technical University, Kapurthala (Punjab), India.

Author Articles
Error Prone Transmission System to Resist Data Loss in a Wireless Sensor Network

By Sunil Kumar C. Rama Krishna A. K. Solanki

DOI: https://doi.org/10.5815/ijcnis.2017.11.02, Pub. Date: 8 Nov. 2017

Data losses in wireless sensor network (WSN) commonly occur due to diverse transmission errors such as hardware or software limitations, channel congestion, network coverage constraint and transmission delay. Another important cause for data loss is distinct security attacks caused by illegal interferences of illicit third parties. Apart from that data loss may occur due to some unforeseen causes too. A number of efforts have been made in WSN to control such types of data loss during the transmission process individually or along with various combinations. However, none of them are capable of addressing each of the mentioned cause of data loss in WSN environment. Henceforth, we have proposed an error resistant technique for WSN to address all of the mentioned causes for data loss. The proposed technique also offers a backup system for the accidental data losses. The experimental results shows that the proposed technique offers minimum data loss during the communication process by offering higher Signal to Noise Ratio (SNR) and low Information Loss compared to the other existing error control techniques. The time efficiency can also be justified by its high Throughput and complexity can be verified by measuring Cyclomatic Complexity.

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