Enhancement of Quality of Service in Mobile Ad-Hoc Networks using Hybrid Load Balanced Simulator: Annealing Simulated
Wireless topologies can change rapidly and unexpectedly. Hybrid networks are connected by gateways, which act as entry points for all traffic. Some gateways may be subject to high traffic loads and therefore may be overloaded. To compare the performance of the proposed work, various parameters inclu...
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Published in | International Conference on System Modeling & Advancement in Research Trends (Online) pp. 405 - 413 |
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Main Authors | , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
16.12.2022
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Subjects | |
Online Access | Get full text |
ISBN | 9781665487320 1665487321 |
ISSN | 2767-7362 |
DOI | 10.1109/SMART55829.2022.10046821 |
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Summary: | Wireless topologies can change rapidly and unexpectedly. Hybrid networks are connected by gateways, which act as entry points for all traffic. Some gateways may be subject to high traffic loads and therefore may be overloaded. To compare the performance of the proposed work, various parameters including end-to-end latency, power consumption, and throughput are considered. Load Balancing Hybrid Simulator (LBHS) is an algorithm used in this paper to distribute traffic load among multiple gateways to solve load balancing problems in MANET. It combines a Hybridge Annealing Simulation (HAS) network technology with Decentralized Random Search (DRS). A network that supports QoS in MANET. The Dominant Minimal Set (DMS) problem is solved using AS. The DSS heuristic algorithm provides an algorithm with a simple structure and a high degree of exploration. In addition to faster convergence than other algorithms, it also implements an axiomatic algorithm to ensure the diversity of agents and avoid falling into local optimum. The test results show that the proposed Hybridge Annealing Simulated Decentralized Random Search (HAS-DRS) procedure performs better than the dominated connection set (DCS). |
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ISBN: | 9781665487320 1665487321 |
ISSN: | 2767-7362 |
DOI: | 10.1109/SMART55829.2022.10046821 |