TOPQoS : TENSOR Based Optimum Path Selection in Internet of Things to Enhance Quality of Service

Authors(2) :-A. Dalvin Vinoth Kumar, L. Arockiam

The electronic devices or gadgets that are connected to the internet play a prominent role among human beings in this new era. The things connected together bring smartness to the network. The smart Network of the things or objects is termed as Internet of Things (IoT). IoT acts as a bridge between the Internet world and the real world. It changes the ordinary devices into smart devices by adding intelligence to the system which is connected to the Internet. The routing protocol for IoT needs to satisfy the applications needed for lossy sensor nodes. In this paper, the Light weight On-demand Ad-hoc Distance Vector routing protocol - Next Generation (LOADng) is enhanced to achieve QoS by optimum path selection. The proposed Tensor Based Optimum Path (TOP) identification technique dynamically identifies optimum path Using TENSOR model. The proposed work is implemented using cooja IoT simulator.

Authors and Affiliations

A. Dalvin Vinoth Kumar
Research Scholar, Department of Computer Science, St. Joseph's College (Autonomous), Thiruchirapalli, Tamil Nadu, India
L. Arockiam
Associate Professor, Department of Computer Science, St. Joseph's College (Autonomous), Thiruchirapalli, Tamil Nadu, India

Internet of Things, Quality of Service,Smart home, PDR, Packet Loss,Timeliness Contiki.

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Publication Details

Published in : Volume 2 | Issue 6 | November-December 2017
Date of Publication : 2017-12-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 852-859
Manuscript Number : CSEIT1726200
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

A. Dalvin Vinoth Kumar, L. Arockiam, "TOPQoS : TENSOR Based Optimum Path Selection in Internet of Things to Enhance Quality of Service", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 6, pp.852-859, November-December-2017.
Journal URL : http://ijsrcseit.com/CSEIT1726200

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