Efficient QoS Routing in Manet using Quantum Behaved PSO
Nibedita Jagadev1, Binod Kumar Pattanayak2
1Herry Sulendro Mangiri, Post Graduate Program, Universitas Negeri Yogyakarta , Yogyakarta, Indonesia.
2Herminarto Sofyan, Faculty of Engineering, Universitas Negeri Yogyakarta, Yogyakarta, Indonesia.
Manuscript received on November 12, 2019. | Revised Manuscript received on November 25, 2019. | Manuscript published on 30 November, 2019. | PP: 5803-5807 | Volume-8 Issue-4, November 2019. | Retrieval Number: D8600118419/2019©BEIESP | DOI: 10.35940/ijrte.D8600.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In mobile ad hoc networks, there is always a requirement of transferring real time multimedia information between a source-destination pair through a communication network. To support these communications and emergence of real-time applications, the basic requirement is to determine a feasible path which can join the source node and the destination node with a minimal cost .The paths are subjected to some constraints such as bandwidth, end-to-end delay, jitter and hop count. So, in order to assure an efficient performance, these QoS routing constraints must be properly handled. Therefore, complication of the problem is considered and accessible solution is provided using meta-heuristic algorithm rather than any other methods. To resolve the multi-constrained QoS routing problem in Mobile Ad-hoc Networks (MANETs), an intelligent algorithm has been proposed here to find the feasible path. This paper proposes a QPSO algorithm for solving multimedia routing which is capable of finding the low-cost route with bandwidth, delay and hop count as the constraints. In the proposed algorithm, the feasible path from the source node to the destination node is selected for communication which satisfies the minimum required bandwidth, less end-to-end delay and minimum hop count. The simulation results illustrate that the proposed QPSO algorithm with a novel node selection technique is able to find a better optimal path with multiple QoS constrains such as Bandwidth, hop count and network delay (end-to-end delay). It can meet the real-time requirements in multimedia communication networks.
Keywords: QoS, Mobile Ad-hoc Network, Quantum Particle Swarm Optimization.
Scope of the Article: Waveform Optimization for Wireless Power Transfer.