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Correlation Distance Based Greedy Perimeter Stateless Routing Algorithm for Wireless Sensor Networks


Affiliations
1 Department of Computer Science, Saranathan college of Engineering, Trichy-12, India
 

Wireless sensor networks (WSNs) are a popular study topic because of the extensive range of potential applications they have. A WSN is made up of a few hundred to tens of thousands of sensor nodes from anywhere, all of which interconnect via radio signals. Restrictions on computing power, storage, battery life, and transmission bandwidth are all factors to consider while designing a WSN. Clustering and routing procedures have been proposed to deal with these problems. Wi-Fi sensor network routing is a critical but tough task. A Greedy Perimeter Stateless Routing (GPSR) algorithm, an effectual and receptive routing system is developed. Packet forwarding decisions are based on node placements. When transferring messages, the GPSR always takes the shortest route possible between the source and destination nodes. Using distance measurements including Euclidean, city block, cosine, and correlation, the complete weighted directed graph is constructed in this study. Rigorous simulation has been executed using NS-2. Also, the GPSR performance with different distance measures is compared and validated. The results show that the proposed GPSR with correlation distance provides better performance in terms of packet delivery ratio, throughput, routing overhead and average stability time of cluster head, when compared to other distance measures.

Keywords

Complete Weighted Directed Graph, Clustering, Greedy Perimeter Stateless Routing, Packet Delivery Ratio, Wireless Sensor Network.
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  • Chandel, A., Chouhan, V.S. and Vyas, D.. A Survey on Architecture and Protocols for Wireless Sensor Networks. In Advances in Information Communication Technology and Computing, 2021 127-141. Springer, Singapore.

  • Shankar K and Elhoseny M, Trust-based cluster head election of secure message transmission in MANET using a multi-secure protocol with TDES, Journal of Univeresal Computer Science, 25. 1221-1239.

  • 3217/jucs-025-10-1221.

  • Dutta AK, Elhoseny M, Dahiya V, et al. An efficient hierarchical clustering protocol for multihop Internet of vehicles communication, Transactions on Emerging Telecommunications Technologies. 31. 10.1002/ett.3690.

  • Elhoseny M and Shankar K., Reliable data transmission model for mobile Ad Hoc network using signcryption technique, IEEE Transactions on Reliability. 69, 2020 1077-1086. 10.1109/TR.2019.2915800.

  • Uma Maheswari P, Manickam P, Sathesh Kumar K, et al. Bat optimization algorithm with fuzzy based PITsharing (BF-PIT) algorithm for Named Data Networking (NDN). Journal of Intelligent & Fuzzy Systems. 37. 2019,1-8. 10.3233/JIFS-179086.

  • Arjunan S, Pothula S and Ponnurangam D. F5Nbasedunequal clustering protocol (F5NUCP) for wirelesssensor networks. Int J CommunSyst2018; 31(17):e3811.

  • Gupta, D., Khanna, A., SK, L., Shankar, K., Furtado, V. and Rodrigues, J.J., 2019. Efficient artificial fish swarm based clustering approach on mobility aware energy‐efficient for MANET. Transactions on Emerging Telecommunications Technologies, 30(9), p.e3524.

  • Elhoseny M and Shankar K. Energy efficient optimal routing for communication in VANETs via clustering model., Emerging technologies for connected internet of vehicles and intelligent transportation system networks (Studies in systems, decision and control, vol. 242). Cham: Springer,2019, pp.1214.

  • Shahraki, A., Taherkordi, A., Haugen, Ø. and Eliassen, F., Clustering objectives in wireless sensor networks: A survey and research direction analysis. Computer Networks, 180, 2020 p.107376.

  • Arjunan S and Pothula S. A survey on unequal clustering protocols in wireless sensor networks. Journal of King Saud University - Computer and Information Sciences. 31. 2019, 10.1016/j.jksuci.2017.03.006..

  • Arjunan S and Sujatha P., Lifetime maximization of wireless sensor network using fuzzy based unequal clustering and ACO based routing hybrid protocol. Applied Intelligence. 48. 2018, 1-18. 10.1007/s10489-017-1077-y. 2018; 48(8): 2229– 2246.

  • Fanian, F. and Rafsanjani, M.K.,. Cluster-based routing protocols in wireless sensor networks: A survey based on methodology, Journal of Network and Computer Applications, 142, 2019, pp.111-142.

  • Diwakaran, S., Perumal, B. and Devi, K.V., An intelligent data aware and energy censoring scheme for wireless sensor networks. Cluster Computing, 22(2), 2019, pp.4213-4220.

  • A. Zahedi, M. Arghavani, F. Parandin, and A. Arghavani, Energy efficient reservation-based cluster head selection in WSNs,, Wireless Personal. Communication, vol. 100, no. 3, 2018,. 667–679.

  • D. Sharma, A. Goap, A. Shukla, and A. P. Bhondekar, Traffic heterogeneity analysis in an energy heterogeneous WSN routing algorithm, in Proceedings. 2nd International Conference on. Communication Computer. Networks., 2019, 335– 343.

  • D. Sharma and A. P. Bhondekar, ‘‘Traffic and energy aware routing for heterogeneous wireless sensor networks,’’ IEEE Communication Letters, vol. 22, no. 8, Aug. 2018, , pp. 1608–1611,.

  • R. M. Al-Kiyumi, C. H. Foh, S. Vural, P. Chatzimisios, and R. Tafazolli, Fuzzy logic-based routing algorithm for lifetime enhancement in heterogeneous wireless sensor networks, IEEE Transactions on. Green Communication. Networks., vol. 2, no. 2, Jun. 2018,. 517–532,

  • Cho, E.S.; Yim, Y.; Kim, S.H. Transfer-Efficient Face Routing Using the Planar Graphs of Neighbors in High Density WSNs.Sensors2017, 17, 2402.

  • Cho, H.; Kim, S.; Kim, C.; Oh, S.; Kim, S.H. Energy-efficient look ahead face routing using coverage range in wireless networks. In Proceedings of the 2017 14th IEEE Annual Consumer Communications & Networking Conference (CCNC), Las Vegas, NV, USA, 8–11 January 2017; . 767– 771.

  • Masoud, M.Z., Jaradat, Y., Jannoud, I. and Al Sibahee, M.A,. A hybrid clustering routing protocol based on machine learning and graph theory for energy conservation and hole detection in wireless sensor network. International Journal of Distributed Sensor Networks, 15(6)., 2019 .1550147719858231.

  • Parvin, S.; Sarram, M.A.; Mirjalily, G.; Adibnia, F, A survey on void handling techniques for geographic

  • routing in VANET network. International. Journal of Grid Distributed. Computing., 8, 2015,101–114.

  • Huang, H., Yin, H., Min, G., Zhang, J., Wu, Y., & Zhang, X.,Energy-aware dual-path geographic routing to bypass routing holes in wireless sensor networks,. IEEE Transactions on Mobile Computing, 17(6), 2018,1339–1352.

  • Greedy Perimeter Stateless Routing, Available: https://www.icir.org/bkarp/gpsr/.

  • Routing Dynamic Source Routing , by Margaret Rouse Available:https://searchnetworking.techtarget.com/Dynamic-Source-Routing

  • Hamid, A. and Hong, C.S,. Defence against lap-top class attacker in wireless sensor network, 8th International Conference Advanced Communication Technology Vol. 1, 2006, February . 5-pp. IEEE.


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  • Correlation Distance Based Greedy Perimeter Stateless Routing Algorithm for Wireless Sensor Networks

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Authors

S. Venkatasubramanian
Department of Computer Science, Saranathan college of Engineering, Trichy-12, India

Abstract


Wireless sensor networks (WSNs) are a popular study topic because of the extensive range of potential applications they have. A WSN is made up of a few hundred to tens of thousands of sensor nodes from anywhere, all of which interconnect via radio signals. Restrictions on computing power, storage, battery life, and transmission bandwidth are all factors to consider while designing a WSN. Clustering and routing procedures have been proposed to deal with these problems. Wi-Fi sensor network routing is a critical but tough task. A Greedy Perimeter Stateless Routing (GPSR) algorithm, an effectual and receptive routing system is developed. Packet forwarding decisions are based on node placements. When transferring messages, the GPSR always takes the shortest route possible between the source and destination nodes. Using distance measurements including Euclidean, city block, cosine, and correlation, the complete weighted directed graph is constructed in this study. Rigorous simulation has been executed using NS-2. Also, the GPSR performance with different distance measures is compared and validated. The results show that the proposed GPSR with correlation distance provides better performance in terms of packet delivery ratio, throughput, routing overhead and average stability time of cluster head, when compared to other distance measures.

Keywords


Complete Weighted Directed Graph, Clustering, Greedy Perimeter Stateless Routing, Packet Delivery Ratio, Wireless Sensor Network.

References