A Secure and Efficient Scheduling Mechanism for Emergency Data Transmission in IOT

admin February 24, 2019

Authors:

D.Subba Rao,Dr. N.S. Murti Sarma,

DOI NO:

https://doi.org/10.26782/jmcms.2019.02.00031

Keywords:

network of IOT,efficient scheduling algorithms, Elliptic curve cryptography,emergency nodes, transmissions in the network,

Abstract

Internet of things (IOT) enables electronic gadgets to communicate with the server and each other, enabling them to share crucial information. With the advancement in the technology, more and more devices are added to the network of IOT every day. In the era of smart cities, the amount of data being transmitted is immense. While transferring such a huge amount of data, the system has to prioritize the data being sent based on the importance, such as medical and fire safety information. Lack of efficient scheduling algorithms leads to inappropriate delivery of emergency packets, thus rupturing the functionality of the system. Also, the data sent over the network has to guardagainst attacks over the channel. To overcome these drawbacks, a scheduling algorithm named Efficient data emergency aware packet scheduling scheme (EARS), enhanced with data security using Elliptic curve cryptography is proposed in this paper. In EARS, each packet has a description of its priority and the deadline before which it has to reach the sink. This enables easy identification of the emergency nodes. Further, in order to reduce the total number of transmissions in the network, the normal data packets can be network-coded and sent to the destination. This will reduce the congestion in the network. The proposed method is compared with the existing state of the art techniques and the results produced outperformed the exciting methods.

Refference:

I.A. T Hashemet al., “The role of big data in smart city,” Int. J. Inf. Manage., vol. 36, no. 5, pp. 748–758, 2016.

II.F. Yang and I. Aug ́e-Blum, “Delivery ratio-maximized wakeup scheduling for ultra-low duty-cycled WSN under real-time constraints,” Comput.Netw., vol. 55, no. 3, pp. 497–513, 2011.

III.G. Lu and B. Krishnamachari, “Minimum latency joint scheduling and routing in wireless sensornetworks,” Ad Hoc Netw., vol. 5, no. 6, pp. 832–843, 2007.

IV.K.-H. Phung, B. Lemmens,M. Goossens, A. Nowe, L. Tran, and K. Steenhaut, “Schedule-based multi-channel communication in wireless sensor networks: A complete design and performance evaluation,” Ad Hoc Netw., vol. 26, pp. 88–102, 2015.

V.M. Nitti, R. Girau, and L. Atzori, “Trustworthiness management in the social internet of things,” IEEE Trans. Knowl. Data Eng., vol. 26, no. 5, pp. 1253–1266, May 2014.

VI.M. V. Moreno et al., “Applicability of big data techniques to smart cities deployments,” IEEE Trans. Ind. Informat., vol. 13, no. 2, pp. 800–809, Apr. 2017.

VII.P. Guo, T. Jiang, Q. Zhang, and K. Zhang, “Sleep scheduling for critical event monitoring in wireless sensor networks,” IEEE Trans. ParallelDistrib. Syst., vol. 23, no. 2, pp. 345–352, Feb. 2012.

VIII.R. Gomathi and N. Mahendran, “An efficient data packet scheduling schemes in wireless sensor networks,” in Proc. Int. Conf. Electron. Commun.Syst., Feb. 26–27, 2015, pp. 542–547.

IX.T.Qiu,K. Zheng, H. Song, M. Han, and B.Kantarci, “A local-optimization emergency scheduling scheme with self-recovery for smart grid,” IEEETrans. Ind. Inf, doi: 10.1109/TII.2017.2715844.

X.T. Qiu, R. Qiao, and D. Wu, “EABS: An event-aware backpressure scheduling scheme for emergency internet of things,” IEEE Trans. MobileComput., doi: 10.1109/TMC.2017.2702670.

XI.U. Jang, S. Lee, and S. Yoo, “Optimal wake-up scheduling of data gathering trees for wireless sensor networks,” J. Parallel Distrib. Comput., vol. 72, no. 4,pp. 536–546, 2012.

XII.V. Chang, “Towards a big data system disaster recovery in a private cloud,” Ad Hoc Netw., vol. 35, pp. 65–82, 2015.

XIII.X. Shen, C. Bo, J. Zhang, S. Tang, X. Mao, and G. Dai, “EFCon: Energy flow control for sustainable wireless sensor networks,” Ad Hoc Netw., vol. 11, no. 4, pp. 1421–1431, 2013.

XIV.Xue, B. Ramamurthy, and M. C. Vuran, “SDRCS: A servicedifferentiated real-time communication scheme for event sensing in wireless sensor networks,” Comput. Netw., vol. 55, no. 15, pp. 3287–3302, 2011.

XV.X. Xu, X. Li, andM. Song, “Distributed scheduling for real-time data collection in wireless sensor networks,” in Proc. IEEE Global Telecommun.Conf., Dec. 9–13, 2013, pp. 426–431.

 

D. Subba Rao, Dr. N.S. Murti Sarma View Download