An Efficient QOS Improvement Established on Unreasonable Investment, with a Half and Half Node Participation Clustering Approach in Mobile Ad Hoc Network


  • T Ramani
  • P Sengottuvelan





Unreasonable investment, half and half node participation, cluster, collaboration weightage, Manet.


Mobile ad hoc network (MANET) is characterized as a self-arranging foundationless system utilized for correspondence by wireless connections with the help of nodes. A MANET is suggested as the wireless system with autonomous nodes moving naturally concerning each other. Because of the different free moves of nodes, a lot of packet misfortune happens in transmitting the packet from source to goal. The danger of lousy node conduct is extraordinarily high. The unsecured unplanned system condition is started because of the progressive idea of systems and node portability. Likewise, the assignment of central administration is more confused in an improvised order. Because of the concept of free moving attributes, MANET faces disgraceful node collaboration. In this proposed work manages node collaboration to security issues like Unreasonable Investment, with a Half and Half Node Participation based Clustering approach (UIH2NPC) in MANET. The node collaboration among the nodes in MANET is enhanced by estimating the weightage of helpfulness of every node in the system. The assessment of node collaboration weightage identifies the external nodes contribution in the order. Execution assessments are done.




[1] Sandeep J & Satheesh Kumar J, ‘Efficient Packet Transmission and Energy Optimization in Military Operation Scenarios of MANETâ€, Elsevier, Procedia Computer Science, Vol.47, (2015), pp.400-407.

[2] Wen W, Dong Z, Chen G, Zhao S & Chang CY, “Energy Efficient Data Collection Scheme in Mobile Wireless Sensor Networksâ€, 31st International Conference on Advanced Information Networking and Applications Workshops (WAINA), (2017), pp.226-230.

[3] Wang J, Zuo L, Zhang Z, Xia F & Kim JU, “Mobility Based Data Collection Algorithm for Wireless Sensor Networksâ€, IEEE Ninth International Conference on Mobile Ad-hoc and Sensor Networks (MSN), (2013), pp.342-347.

[4] Xie S & Wang Y, “Construction of tree network with limited delivery latency inhomogeneous wireless sensor networksâ€, Wireless Personal Communications, Vol.78, No.1, (2014), pp.231-246.

[5] Zhao M, Ma M & Yang Y, “Efficient data gathering with mobile collectors and space-division multiple access techniques in wireless sensor networksâ€, IEEE Trans. Comput., Vol.60, No.3, (2011), pp.400-417.

[6] Kinalis A, Nikoletseas S, Patroumpa D & Rolim J, “Biased sink mobility with adaptive stop times for low latency data collection in sensor networksâ€, Inf. Fusion, (2014).

[7] Nazir B & Hasbullah H, “Mobile sink based routing protocol(MSRP) for prolonging network lifetime in winsâ€, Computer Applications and Industrial Electronics, (2010), pp.624-629.

[8] Du J, Liu H, Shangguan L, Mai L, Wang K & Li S, “Rendezvous data collection using a mobile element in heterogeneous sensor networksâ€, International Journal of Distributed Sensor Networks, (2012), pp.1-12.

[9] Salarian H, Chin KW & Naghdy F, “An energy-efficient mobile-sink path selection strategy for wireless sensor networksâ€, IEEE Trans. Veh. Technol., Vol.63, No.5, (2014), pp.2407-2419.

[10] Liu F, Wang Y, Lin M, Liu K & Wu D, “A Distributed Routing Algorithm for Data Collection in Low-Duty-Cycle Wireless Sensor Networksâ€, IEEE Internet of Things Journal, Vol.4, No.5,(2017), pp.1420-1433.

[11] G Mussabekova, S Chakanova, A Boranbayeva, A Utebayeva, K Kazybaeva, K Alshynbaev (2018). Structural conceptual model of forming readiness for innovative activity of future teachers in general education school. Opción, Año 33. 217-240

[12] Abdulla AEAA, Nishiyama H & Kato N, “Extending the lifetime of wireless sensor networks: A hybrid routing algorithmâ€, Comput. Commun. J., Vol.35, No.9, (2012), pp.1056-1063.

[13] Ramos A, Lazar M, Holanda Filho R & Rodrigues JJ, “A security metric for the evaluation of collaborative intrusion detection systems in wireless sensor networksâ€, IEEE International Conference on Communications (ICC), (2017), pp.1-6.

[14] Corona I, Giacinto G & Roli F, “Adversarial attacks against intrusion detection systems: Taxonomy, solutions and open issuesâ€, Information Sciences, Elsevier, Vol.239, (2013), pp.201-225.

[15] Amine D, Nasr-Eddine B & Abdelhamid L, “A distributed and safe weighted clustering algorithm for mobile wireless sensor networksâ€, Procedia Computer Science, Vol.52, (2015), pp.641-646.

[16] Guntupalli L, Martinez-Bauset J, Li FY & Weitnauer MA, “Aggregated packet transmission in duty-cycled WSNs: Modeling and performance evaluationâ€, IEEE Trans. Veh. Technol., Vol.66, No.1, (2017), pp.563-579.

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