IJSTR

International Journal of Scientific & Technology Research

Home About Us Scope Editorial Board Blog/Latest News Contact Us
0.2
2019CiteScore
 
10th percentile
Powered by  Scopus
Scopus coverage:
Nov 2018 to May 2020

CALL FOR PAPERS
AUTHORS
DOWNLOADS
CONTACT

IJSTR >> Volume 8 - Issue 11, November 2019 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Chain Based Routing Algorithm Using Hybrid Optimisation For Wireless Sensor Network

[Full Text]

 

AUTHOR(S)

Rohini, Dr. Kanika Sharma

 

KEYWORDS

Wireless Sensor Network, Routing Protocol, Ant Lion Optimization and Genetic Optimization Algorithm in WSN.

 

ABSTRACT

WSNs are spatially distributed, self-regulating sensors to track the physiological objects or observe the ecological information and gather the information to the main controller. WSN contains radio trans-receiver, micro-controller and sensor devices. A sensor device contains various applications that can be utilised in various fields. Different sensor devices are categorised on the basis of the inclines for the deployment of the fields that focused in term of economical, engineering, price and scalability. In wireless sensor network the system is controlled by the main controller and utilised to acquire information from various fields. Some of the applications of WSN is agriculture, monitoring of environment, Healthcare and transport services, authentication and surveillance, industrial uses. Wireless sensor network has the key restraint on power of sensor hops that is single hops contains a definite amount of energy. Hence, WSN may contain a robust energy reduced technique as key issue on the basis of energy. In present research, routing protocol utilise Power efficient gathering in sensor information systems (PEGASIS) is routing convention that depends on chain based and greedy approach. The sensors hops are arranged in form of the chain. In case any hop fails in between then the chain is rebuilt to bypass the failed hop. CH is allocated and transfers the information to the controller or sink hop. Performance metrices was analysed with packet delivery ratio to achieve the value up to 80%.In proposed research, a routing method for WSN is developed to improve the network lifetime, packet delivery ratio and energy consumption with help of number of rounds. The novel method has designed hybridization with GA+ALOA algorithm to resolve the issues in the network. GALO (Genetic-Ant Lion Optimization) is developed to improve the performance of the network. Simulation analysis is done using MATLAB. It is analysed that packet delivery ratio is improved up to 85%. Hence, the packet loss value is 9 bits and reduce energy is 0.9 joules.

 

REFERENCES

[1] Lazarescu, M. T. (2013), “Design of a WSN platform for long-term environmental monitoring for IoT applications” , IEEE Journal on emerging and selected topics in circuits and systems, vol.3(1), pp. 45-54.
[2] Đurišić, M. P., Tafa, Z., Dimić, G. and Milutinović, V. (2012), “ A survey of military applications of wireless sensor networks” , In 2012 Mediterranean conference on embedded computing (MECO) ,pp. 196-199. IEEE.
[3] Murillo, A. F., Peña, M. and Martínez, D. (2012), Applications of WSN in health and agriculture” , In 2012 IEEE Colombian Communications Conference (COLCOM) , pp. 1-6, IEEE.
[4] Bera, S., Misra, S., Roy, S. K and Obaidat, M. S. (2016), “ Soft-WSN: Software-defined WSN management system for IoT applications” , IEEE Systems Journal, vol. 12(3), pp.2074-2081.
[5] Alcaraz, C., Lopez, J., Roman, R. and Chen, H. H. (2012), “ Selecting key management schemes for WSN applications” , Computers & Security, vol. 31(8),pp. 956-966.
[6] Yick, J., Mukherjee, B., and Ghosal, D. (2008), “ Wireless sensor network survey” , Computer networks, vol. 52(12),pp . 2292-2330.
[7] Ye, W., Heidemann, J. and Estrin, D. (2002), “ An energy-efficient MAC protocol for wireless sensor networks” , In Proceedings. Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies , vol. 3, pp. 1567-1576, IEEE.
[8] Sohrabi, K., Gao, J., Ailawadhi, V., and Pottie, G. J. (2000), “ Protocols for self-organization of a wireless sensor network” , IEEE personal communications, 7(5), 16-27.
[9] Doherty, L.and El Ghaoui, L. (2001), “ Convex position estimation in wireless sensor networks” , In Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No. 01CH37213) ,Vol. 3, pp. 1655-1663, IEEE.
[10] Chang, J. H. and Tassiulas, L. (2004), “ Maximum lifetime routing in wireless sensor networks” , IEEE/ACM Transactions on networking, vol.12(4), pp.609-619.
[11] Huang, C. F and Tseng, Y. C. (2005), “The coverage problem in a wireless sensor network” ,Mobile networks and Applications, vol. 10(4), pp.519-528.
[12] Herbert, J., O'Donoghue, J., Ling, G., Fei, K and Fok, C. L. (2006), “ Mobile agent architecture integration for a wireless sensor medical application” , In 2006 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Workshops, vol 2(1) ,pp. 235-238, IEEE.
[13] Omeni, O., Wong, A. C. W., Burdett, A. J. and Toumazou, C. (2008), “ Energy efficient medium access protocol for wireless medical body area sensor networks”, IEEE Transactions on biomedical circuits and systems, vol.2(4), pp.251-259.
[14] Alkhatib, A. A. A. and Baicher, G. S. (2012), “Wireless sensor network architecture”, In 2012 International Conference on Computer Networks and Communication Systems (CNCS 2012).
[15] Ruiz, L. B., Nogueira, J. M and Loureiro, A. A. (2003), “ Manna: A management architecture for wireless sensor networks” , IEEE communications Magazine, vol. 41(2), pp.116-125.