Author : J. Jayabharathi 1
Date of Publication :30th March 2018
Abstract: Researches in field of QoS and energy supportive approaches in IoT networks nodes primarily focus on node inter connectivity and packet transmission, packet collision during transmission and optimize network lifetime. Majority of QoS and energy supportive algorithms in IoT networks focus on providing route management and effective data transmissions, supportive energy dissipation on the transmission route. EAMRO, the proposed algorithm lead to maximal node utilization, as well as decrease on node energy used during transmission on selected route. Consistent demand on QoS and controlled energy consumption is always felt by researching community. This paper proposes an energy controlled QoS support routing scheme EAMRO for IoT node location systems where demand for services are high. EAMRO suggests an optimal energy identification approach for selection of a data transmission route, along with route identification based on ratio of energy identified and its corresponding distance to destination node as location aware to solve the problem. Providing optimal QoS is controlled by assigning a least transmission power to the nodes where each node is aware of location information and hence able to adjust their transmission power accordingly. EAMRO is simulated using cup carbon simulator whose performance shows minimal energy consumption of sensor nodes compared to RPL.
Reference :
-
- A. Aijaz and A. Aghvami, “Cognitive machine-tomachine communications for internet-of-things: A protocol stack perspective”, IEEE Internet of Things Journal, vol. 2, no. 2, pp. 103-112, April 2015.
- A. Al-Fuqaha, M. Guizani, M. Mohammadi, M. Aledhari, and M. Ayyash, “Internet of things: A survey on enabling technologies, protocols and applications”, IEEE Communications Surveys Tutorials, pp. 99, 2015.
- Ahcène Bounceur, “CupCarbon: A New Platform for Designing and Simulating Smart-City and IoT Wireless Sensor Networks (SCI-WSN)”, International Conference on Internet of Things and Cloud Computing, Cambridge, United Kingdom, 2016
- Arunkumar Sangiah, Arunkumar Thangavelu, Venkatesan Meenakshi Sundram, “Cognitive Computing for Big Data systems over IOT - Frameworks, Tools and Applications”, Springer publications, 2017.
- Dujovne, T. Watteyne, X. Vilajosana, and P. Thubert, “6TiSCH: Deterministic IP-enabled industrial internet (of things)”, IEEE Communications Magazine, vol. 52, no. 12, pp. 36-41, December 2014.
- IEEE 1905.1-2013, “IEEE Standard for a Convergent Digital Home Network for Heterogeneous Technologies”, pp. 93, April 12, 2013.
- V. Karagiannis, P. Chatzimisios, F. VazQuez –Gallego, and J. AlonsoZarate, “A survey on application layer protocols for the internet of things”, Transaction on IoT and Cloud Computing, vol. 3, no. 1, pp. 11-17, 2015.
- Krishnamachari B, Estrin D, Wicker S, “Modeling DataCentric Routing in Wireless Sensor Networks”, USC Computer Engineering Technical Report, CENG 02–14, 2002.
- C. Lin, “On demand QoS routing in Multihop mobile networks”, In Proceedings of Twentieth Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM), Vol3, pp. 1735–1744, April 2001.