Assessment of performance metrics for fusion network

Authors

  • Rohan Gupta Department of Electronics and Communication Engineering,SJPMLIET, Radaur, Haryana, India
  • Gurpreet Singh Department of Computer Science Engineering, PIT, Rajpura,MRSPTU, Bathinda, Punjab, India
  • Amanpreet Kaur Associate Professor, University Institute of Computing, Chandigarh University, Mohali

DOI:

https://doi.org/10.48129/kjs.v48i3.9751

Keywords:

ant colony optimization, mobile adhoc network, particle swarm optimization, qos, routing algorithm

Abstract

The arrangement which does not necessitate any infrastructure for doing discussion among nodes is called as mobile ad-hoc network. In this paper the direction-finding technique which is mixture of particle swarm optimization and ant colony optimization technique has been designed. To compute the usefulness of the intended technique the outcome of intended technique is evaluated with respect to several assessment metrics specifically routing overhead, packet delivery ratio and throughput. The designed technique is judged against several alternatives of particle swarm optimization technique and ant colony optimization technique i.e. EDNR+PSO, AntChain Protocol, Improvised Ant Colony Routing (IACR) and ANTALG. Open source simulator NS 2.3 is employed for carrying out the simulation. From the outcome it has been verified that the designed technique is finest in contrast to other alternatives of particle swarm optimization and ant colony optimization Routing overheads of the designed algorithm are reduced in contrast to other methods.

References

Batla, N., Kaur, A., Singh, G.(2014)Congestion Control Techniques in TCP: A Critique. Proceedings of 3rd National Conf. of Advances and Research in Technology (ART-2014), 45.1-45.5.

Batth, K.,and Singh, R.(2017)Performance Evaluation of Ant Colony Optimization Based Routing. Journal of Advanced Technology, 8:1-7.

Bhatia, D., Sharma, D.(2016) A Comparative Analysis of Proactive, Reactive and Hybrid Routing Protocols over open Source Network. Journal of Applied Engineering Research, 11: 3885-3896.

Cordon, O., viana, I., Herrera, F., Moreno, L. (2000)A new ACO model integrating evolution computation concepts. Best-worst ant System citeseer.

Dorigo, M., Caro, Di., Gambardella, M.(1999) Ant Algorithms for discrete optimization. Journal of Artificial Life, 5:137 – 172.

Dorigo, M., Maniezzo, V., Colorni, A. (1996) Ant System: Optimization by a colony of cooperating agents,” IEEE Transaction on Systems, Man, and Cybernetics—Part B, 26:29–41.

Duan, Q., Liao, T. W. (2010) Improved ant colony optimization algorithms for determining project critical paths. Journal of Automation in Construction, 19, 676-693.

F, C., T, V.(2010) Simple ant routing algorithm strategies for a (Multipurpose) MANET model. Journal of Ad-hoc Networks Elsevier, 8:810–823.

Gupta, A.K., Sadawarti, H., and Verma, A.K.(2014) Performance Enhancement of DYMO Routing Protocol with Ant Colony Optimization.Journal of Electrical and Electronics Engineering 2: 188-194.

Geetha, R., Srikanth G. Umarani. (2012)Ant Colony Optimization in Diverse Engineering Applications: an Overview. Journal of Computer Applications, 49:19-25.

Gupta, R., Singh, G., Kaur, A., Singh, A. (2018) Fitness function based particle swarm optimization algorithm for mobile ad-hoc networks. Journal of Engineering and Technology 7(3.1): 31-33.

Gupta, R., Singh, H., and Singh, G. (2017) Performance Evaluation of Routing Protocols for Mobile Ad-hoc Networks. Journal of Science and Technology, 10: 1-6.

G, S., K, Vignesh. (2015)Ant Colony Optimization Based Delay Aware Routing Protocol (ACO-DARP) For Wireless Sensor Network. Journal of Research in Applied Science & Engineering Technology, 3: 396-402.

Huang, P., Kang, Z., Liu, C., and Lin, F.(2016) ACO-Based Path Planning Scheme in RWSN Proceedings of the 10th IEEE Conference on Software, Knowledge, Information Management & Applications, 237-242.

Jha, R., Kharga, P. (2015) A Comparative Performance Analysis of Routing Protocols in MANET using NS3 Simulator. Journal of Computer Network and Information Security, 4: 62-68.

Kanani, C., Sinhal, A. (2013) Ant Colony Optimization based Modified AOMDV for Multipath Routing in MANET. Journal of Computer Applications. 82:14-19.

Kaur,A., Dhaka , V. S., Singh, G. (2016) Adjoining Ant’s Activities in Ad-hoc On-demand Multipath Distance Vector Routing. Indian Journal of Science and Technology, 9:1-6.

Kaur, A., Dhaka, V. S., Singh, G.(2016)Casting multipath behaviour into OANTALG to improve QoS. Proceedings of theconference on Computing for Sustainable Global Development, 2076-2081.

Kaur, A., Dhaka, V. S., Singh, G.(2016) ACO Agent Based Routing in AOMDV Environment. Proceedings of the Conference on Advances in Engineering & Technology-2016 (ICAET-2016) 57:1-8.

Kumar, P and Prasad V. V.(2015)Efficient Ant Colony Optimization (ACO) based Routing Algorithm for MANETs. Global Journal of Computer Science and Technology 15(3).

Li, B., Wang, L., and Song, W.(2008)Ant Colony Optimization for the Traveling Salesman Problem Based on Ants with Memory.Proceedings of thefourth Conference on Natural Computation, 496-501.

Li, K., Leu, J, Hosek, J.(2013) Ant-based on-demand clustering routing protocol for mobile ad-hoc networks. IEEE Conference Publications, 354–359.

Lu, Y., Comsa, I.S., Kuonen, P., and Hirsbrunner, B.(2015)Probabilistic Data Aggregation Protocol Based on ACO-GA Hybrid Approach in Wireless Sensor Networks, Proceedings of the 8th IEEE Conference Publications, 235-238.

Mahale, R., and Chavan, S. (2014) Throughput Aware ACO Based Routing Protocol for Wireless Sensor Network. Proceedings of the IEEE Conference Publications, 234-238.

M, Subha., and R, Anitha.(2011) ACORA – Ant Colony Optimization Routing Algorithm for MANETs Optimized Performance. Journal of Advanced Software Engineering 1: 35-45.

Nancharaiah, B., Chandra Mohan, B.(2014) The performance of a hybrid routing intelligent algorithm in a mobile ad hoc network. Journal of Computer and Electrical Engg.40:1255–1264.

Pan, W., Wang, L. (2009)An Ant Colony Optimization Algorithm Based on the Experience Model.Proceedings of the fifth International Conference on Natural Computation, 13-18.

Prasant, M., Li, J., and Gui, C. (2003) QoS in Mobile Ad-hoc Networks. IEEE Wireless Communications, 10:44-52.

Sharma, H., Kumar, A., and Gupta, M.A.(2017) Performance Enhancement of RoutingProtocol in MANET by implementing Ant Colony Optimization. Journal of Advanced Research Computer Engineering & Technology, 6: 1090-1098.

Simaremare, H., Abouaissa, A., Sari, R., Lorenz, P. (2014) Security and performance enhancement of AODV routing Protocol”, Journal of Communication System.

Sim,Y., Lee, S., Lee, S.(2017) Function-Oriented Networking and On-Demand Routing System in Network Using Ant Colony Optimization Algorithm. Symmetry, 9:1-25.

Singh, A., Dhaka, V. S., Singh, G.(2016) Comparative Analysis of Dynamic Path Maintenance Routing Protocols for Mobile Ad-Hoc Networks. Journal of Science and Technology, 9:1-6.

Singh, G., Kumar, N., and Verma, A.(2014) ANTALG: An Innovative ACO based Routing Algorithm for MANETs. Journal of Network and computer applications, 45: 151-167.

Singh, G., Kumar, N., and Verma, A.(2012)Ant colony algorithms in MANETs: A review. Journal ofNetwork and Computer Applications, 35: 1964-1972.

Socha, K., Dorigo, M.(2008)Ant colony optimization for continuous domains. European Journal of Operation Research - Elsevier, 185:1155–1173.

Wei, X.(2013)Improvement and Implementation of Best-worst Ant Colony Algorithm. Journal of Applied Science Engineering Technology,5: 4971- 4976.

Ya-li, WANG., Mei, SONG., Yi-fei, WEI., Ying-he, WANG., jun, WANG Xiao.(2014)Improved ant colony-based multi-constrained QoS energy-saving routing and throughput optimization in wireless Ad-hoc networks. Journal of China University Posts and Telecommunication 21:43-53.

Yu, K.,Lee, M., Chi, S.(2017) Dynamic Path Planning Based on Adaptable Ant Colony Optimization algorithm. Proceedings of theSixth International Conference on Future Generation Communication Technologies,1- 7.

Published

24-06-2021