Abstract View

Author(s): Manisha Chandrakar, V. K. Patle

Email(s): manishachandrkar00@gmail.com , patlevinod@gmail.com

Address: School of Studies in Computer Science and IT, Pt. Ravishankar Shukla University Raipur, Chhattisgarh, India.
School of Studies in Computer Science and IT, Pt. Ravishankar Shukla University Raipur, Chhattisgarh, India.
*Corresponding Author: manishachandrkar00@gmail.com

Published In:   Volume - 36,      Issue - 2,     Year - 2023

DOI: 10.52228/JRUB.2023-36-2-2  

ABSTRACT:
Various sensor nodes whose deployment is done in a random way are included in Wireless sensor networks (WSN) within a region for gathering the information out of the respective atmospheres as well as forwards it towards the Base Station (BS). Constrained sources of energy are allotted to the WSN nodes. The consumption of energy of nodes must be reduced for obtaining the enhanced lifetime of the network. Clustering is referred as a technique that reduced the consumption of energy in WSNs. By transmitting the gathered data to the sink through the Cluster Head (CH) nodes located within the clustered networks, the energy of the node can be saved. In WSNs, fault tolerance is a significant issue to consider. The entire data communication system can be rendered inoperable by the failure of just one cluster head. Within the scope of this research, a cluster-based routing method with fault tolerance is provided. The purpose of this study is to present an innovative technique for increasing tolerance of failure and data accumulation in clustered WSN by making use of backup CHs and improving the relay node selection mechanism by modifying ACO. The selection of the backup cluster head is what allows for fault tolerance in this case (BKCH). The method can be broken down into two distinct stages. In the first step, the network is categorized into clusters; in the second step, CHs and BCHs are chosen from the pool of candidates. Communication within the cluster takes place between the member nodes and the CH nodes. Aggregator nodes (AG) are utilised for the purpose of inter-cluster communication, and the modified ACO is utilised to determine which node serves as the most effective relay between CH and AG. When compared with other energy-conserving protocols, this technique uses less energy while increasing fault resilience and PDR.

Cite this article:
Manisha Chandrakar; V. K. Patle (2023). Enhanced ACO in clustering algorithm for QoS in WSN enabled IoT. Journal of Ravishankar University (Part-B: Science), 36(2), pp. 19-34.DOI: https://doi.org/10.52228/JRUB.2023-36-2-2


References:

[1] C.-Y. Chong, S.P. Kumar, Sensor networks: evolution, opportunities, and challenges, Proc. IEEE 91 (2003) 1,247–1,256.

[2] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “Wireless sensor networks: A survey,” Comput. Netw., vol. 38, no. 4, pp. 393–422, 2002.

[3] K. Lin, C. F. Lai, X. Liu, and X. Guan, “Energy efficient routing with node compromised resistance in wireless sensor networks,” Mobile Netw. Appl., vol. 17, pp. 75–89, 2012.

[4] K. A. Darabkh, N. J. Al-Maaitah, I. F. Jafar, and K. Ala’F, “EA-CRP: A novel energy-aware clustering and routing protocol in wireless sensor networks,” Comput. Elect. Eng., vol. 72, pp. 702–718, 2017.

[5] J. Chang and L. Tassiulas, “Maximum lifetime routing in wireless sensor networks,” IEEE/ACM Trans. Netw., vol. 12, no. 4, pp. 609–619, Aug. 2004.

[6] A. A. Ahmed and Y. Mohammed, “A survey on clustering algorithms for wireless sensor networks, Elsevier,” Comput. Commun., vol. 30, pp. 2826–2841, 2007.

[7] T. He, J. A. Stankovic, C. Lu, and T. Abdelzaher, “SPEED: A stateless protocol for real-time communication in sensor networks,” in Proc. 23rd Int. Conf. Distrib. Comput. Syst.,, 2003, pp. 46–55.

[8] E. Felemban, C. G. Lee, and E. Ekici, “MMSPEED: Multipath multispeed protocol for QoS guarantee of reliability and timelines in wireless sensor networks,” IEEE Trans. Mobile Comput., vol. 5, no. 6, pp. 738–754, Jun. 2006.

[9] X. Huang and Y. Fang, “Multiconstrained QoS multipath routing in wireless sensor networks,” J. Wireless Netw., vol. 14, no. 4, pp. 465–478, 2008.

[10] X. Song, C. Wang, and J. Pei, “ASenNet: A multiple QoS metrics hierarchical routing protocol based on swarm intelligence optimization for WSN,” in Proc. IEEE Int. Conf. Inf. Sci. Technol., Hubei, China, Mar. 23–25, 2012, pp. 531–534.

[11] W. Cai, X. Jin, Y. Zhang, K. Chen, and R.Wang, “ACO based QoS routing algorithm for wireless sensor networks,” in Proc. 3rd Int. Conf.Ubiquitous Intell. Comput., LNCS, 2006, pp. 419–428.

[12] M. A. Adnan, M. A. Razzaque, I. Ahmed, and I. F. Isnin, “Bio-mimic optimization strategies in wireless sensor networks: A survey,” Sensors, vol. 14, pp. 299–345, 2014.

[13] S. Hadim and N. Mohamed, “Middleware: Middleware challenges and approaches for wireless sensor networks,” IEEE Distrib. Syst. Online, vol. 7, no. 3, Mar., pp. 1–23, 2006.

[14] S. Yi, P. Naldurg, and R. Kravets, “Security-aware protocol for wireless ad-hoc networks,” in Proc. 2nd ACM Int. Symp. Mobile Ad Hoc Netw. Comput., Long Beach, CA, USA, 2001, pp. 299–302.

[15] F. Khan, “Secure communication and routing architecture in wireless sensor networks,” in Proc. IEEE 3rd Global Conf. Consum. Electron., 2014, pp. 647–650.

[16] P. Zhang, G. Xiao, and H.-P. Tan, “Clustering algorithms for maximizing the lifetime of wireless sensor networks with energy-harvesting sensors,” Computer Networks, vol. 57, no. 14, pp. 2689–2704, 2013.

[17] M. S. Bahbahani, M. W. Baidas, and E. Alsusa, “A distributed political coalition formation framework for multi-relay selection in cooperative wireless networks,” IEEE Transactions on Wireless Communications, vol. 14, no. 12, pp. 6869–6882, 2015.

[18] A. Engel and A. Koch, “Heterogeneous wireless sensor nodes that target the Internet of Things,” IEEE Micro, vol. 36, no. 6, pp. 8–15, 2016.

[19] A. Chakraborty, R. R. Rout, A. Chakrabarti, and S. K. Ghosh, “On network lifetime expectancy with realistic sensing and traffic generation model in wireless sensor networks,” IEEE Sensors Journal, vol. 13, no. 7, pp. 2771–2779, 2013.

[20] J.-S. Lee and T.-Y. Kao, “An improved three-layer low-energy adaptive clustering hierarchy for wireless sensor networks,” IEEE Internet of Things Journal, vol. 3, no. 6, pp. 951–958, 2016.

[21] S. Bandyopadhyay and E. J. Coyle, “Minimizing communication costs in hierarchically-clustered networks of wireless sensors,” Computer Networks, vol. 44, no. 1, pp. 1–16, 2004.

[22] B. H. Calhoun, D. C. Daly, N. Verma et al., “Design considerations for ultra-low energy wireless micro-sensor nodes,” IEEE Transactions on Computers, vol. 54, no. 6, pp. 727–740, 2005.

[23] H. Harb and A. Makhoul, “Energy-efficient sensor data collection approach for industrial process monitoring,” IEEE Transactions on Industrial Informatics, vol. 14, no. 2, pp. 661–672, 2018.

[24] R. C. Shah and H. M. Rabaey, “Energy aware routing for low energy ad hoc sensor networks,” in Proc. IEEE Wireless Commun. Netw. Conf. Rec., Orlando, FL, USA, Mar. 2002, pp. 350–355.

[25] F. Bouabdallah, N. Bouabdallah, and R. Boutaba, “Towards reliable and efficient reporting in wireless sensor networks,” IEEE Trans. Mobile Comput., vol. 7, no. 8, pp. 978–994, Aug. 2008.

[26] J. Li and P. Mohapatra, “Analytical model and mitigation techniques for the energy hole problems in sensor networks,” Pervasive Mobile Comput., vol. 3, no. 8, pp. 233–254, 2007.

[27] D. Kumar, T. C. Aseri, and R. B. Patel, “EEHC: energy efficient heterogeneous clustered scheme for wireless sensor networks,” Computer Communications, vol. 32, no. 4, pp. 662–667, 2009.

[28] D. Sharma and A. P. Bhondekar, “Traffic and energy aware routing for heterogeneous wireless sensor networks,” IEEE Communications Letters, vol. 22, no. 8, pp. 1608–1611, 2018.

[29] S. Dutt, S. Agrawal, and R. Vig, “Cluster-head restricted energy efficient protocol (CREEP) for routing in heterogeneous wireless sensor networks,” Wireless Personal Communications, vol. 100, no. 4, pp. 1477–1497, 2018.

[30] S. Tanwar, S. Tyagi, N. Kumar, and M. S. Obaidat, “LA-MHR: learning automata based multilevel heterogeneous routing for opportunistic shared spectrum access to enhance lifetime of WSN,” IEEE Systems Journal, vol. 13, no. 1, pp. 313–323, 2019.

[31] Z. Hong, L. Yu, and G.-J. Zhang, “Efficient and Dynamic Clustering Scheme for Heterogeneous Multi-level Wireless Sensor Networks,” Acta Automatica Sinica, vol. 39, no. 4, pp. 454–460, 2013.

[32] Z. Hong, R. Wang, and X. Li, “A clustering-tree topology control based on the energy forecast for heterogeneous wireless sensor networks,” IEEE/CAA Journal of Automatica Sinica, vol. 3, no. 1, pp. 68–77, 2016.

[33] S. Kavi Priya, T. Revathi, and K. Muneeswaran, “Multi-constraint multi-objective QoS aware routing heuristics for query driven sensor networks using fuzzy soft sets,” Applied Soft Computing, vol. 52, pp. 532–548, 2017.

[34] D.-R. Chen, “An energy-efficient QoS routing for wireless sensor networks using self- stabilizing algorithm,” Ad Hoc Networks, vol. 37, pp. 240–255, 2016.

[35] M. Faheem and V. C. Gungor, “Energy efficient and QoS aware routing protocol for wireless sensor network- based smart grid applications in the context of industry 4.0,” Applied Soft Computing, vol. 68, no. 7, pp. 910–922, 2018.

[36] A. K. Mishra, R. U. Rahman, R. Bharadwaj, and R. Sharma, “An enhancement of PEGASIS protocol with improved network lifetime for wireless sensor networks,” in 2015 IEEE Power, Communication and Information Technology Conference (PCITC),, pp. 142–147, Bhubaneswar, India, October 2015.

[37] R. Singh and A. K. Verma, “Energy efficient cross layer based adaptive threshold routing protocol for WSN,” AEU – International Journal of Electronics and Communications, vol. 72, pp. 166–173, 2017.

[38] Parvinder Singh, Rajeshwar Singh, "Energy-Efficient QoS-Aware Intelligent Hybrid Clustered Routing Protocol for Wireless Sensor Networks", Journal of Sensors, vol. 2019, Article ID 8691878, 12 pages, 2019. https://doi.org/10.1155/2019/8691878.

Related Images:



Recent Images



Herbal Alternatives for Oral Health:  Mechanistic Exploration with their Market Potential
Time of the Day Variability in Pit-Building Behavior of Antlion Larvae
A Comprehensive Review of a particular Skin Injury: Pathogenesis, triggers, and current Treatment Options
Enhanced antioxidant activity in Curcuma caesia Roxb. microrhizomes treated with silver nanoparticles
Studies on the Interaction of Imidazolium Ionic Liquids with Human Serum Albumin
Basic and Advanced Logical Concept Derived from Surface Enhanced Infrared Spectroscopy (SEIRS) as Sensing Probe for Analysis of Chemical Species: A Brief Review
Soil Erosion Risk Estimation by using Semi Empirical RUSLE model: A case study of Maniyari Basin, Chhattisgarh
An Estimator of Population Variance Using Multi-Auxiliary Information
Microemulsion as Novel Drug Delivery for Fungal Eye Infection
Potential of Bioactive Compounds for Atopic Dermatitis

Tags


Recomonded Articles:

Author(s): Naman Shukla; K. Anil Kumar; Madhu Allalla; Sanjay Tiwari

DOI: 10.52228/JRUB.2022-35-1-2         Access: Open Access Read More

Author(s): Srishti Verma; Visheshta Valvi; Kamlesh Kumar Shukla

DOI: 10.52228/JRUB.2022-35-1-6         Access: Open Access Read More

Author(s): Pratap Toppo; PK Joshi; AK Geda

DOI:         Access: Open Access Read More

Author(s): Dinesh Kumar Sharma; Bhabani S Nayak

DOI:         Access: Open Access Read More

Author(s): B S Ajitkumar; Prashant S Hande; Vikas Jha; Pratiksha Alagh; Shailendra Rane

DOI:         Access: Open Access Read More

Author(s): Mukesh Sharma; Ajazuddin; Amit Alexander; DK Tripathi

DOI:         Access: Open Access Read More

Author(s): Princy Dugga; Shamsh Pervez; Rakesh Kumar Sahu; Madhuri Verma; Shahina Bano; Manas Kanti Deb

DOI: 10.52228/JRUB.2017-30-1-5         Access: Open Access Read More

Author(s): D. P .Kuity; T. Lakshminarayan

DOI:         Access: Open Access Read More

Author(s): Akanksha Jain; Pradeep Kumar Naik; Sunil Kumar Senapati

DOI:         Access: Open Access Read More

Author(s): P.V.N. Rao; A.T. Rao

DOI:         Access: Open Access Read More

Author(s): B K Senapati; P K Panigrahi

DOI:         Access: Open Access Read More

Author(s): Bhumika Yadu; S Keshavkant

DOI:         Access: Open Access Read More

Author(s): D.P. Kuity

DOI:         Access: Open Access Read More

Author(s): P Sharma; R Shrivastava; MG Roymon

DOI:         Access: Open Access Read More

Author(s): M.G. Roymon; Rashmi Zankyani; Mabel Varghese

DOI:         Access: Open Access Read More