Nandini Balusu1 ,
Suresh Pabboju2 and Narsimha G 3
1Assistant
Professor, Department of Computer Science, Telangana University, Nizamabad,
Telangana, India.
2Professor,
Chaitanya Bharathi Institute of Technology, Hyderabad, Telangana State, India.
3Professor,
Department of Computer Science, JNTUH College of Engineering, Hyderabad,
Telangana, India.
Nandini Balusu1 ,
Suresh Pabboju2 and Narsimha G 3
1Assistant
Professor, Department of Computer Science, Telangana University, Nizamabad,
Telangana, India.
2Professor,
Chaitanya Bharathi Institute of Technology, Hyderabad, Telangana State, India.
3Professor,
Department of Computer Science, JNTUH College of Engineering, Hyderabad,
Telangana, India.
Abstract
Wireless Mesh Networks offers cost-efficient and higher network efficiency by utilizing multiple channels
multiple radio(MCMR) nodes. Also addition, the amalgamation of multiple radio nodes and multiple hops
mesh framework tends to overcome the limitation of single radio networks like the ability to achieve the rising
accessible system bandwidth. In spite of these benefits, certain MCMR wireless mesh networks still suffer from
performance issues like network connectivity, network throughput degradation whenever network size
increases. Thus, an effective channel assignment (CA) approach could minimize the number of interference cochannels and enhance the throughput of the network. Thus, a hybridized form of gravitational search approach
and particle swarm optimization is presented in this paper to resolve the issue of CA. The velocity and position
updates of PSO are merged with the GSA operations to obtain the best channel with good connectivity. This
approach maximizes the capability of exploration and exploitation for global and local searches using PSO
and GSA operations. The goal of this methodology is the minimization of a number of interfering links and the
maximization of network connectivity and throughput. The experimental results for this approach are carried
out using NS2 and compared with previously suggested heuristic optimization algorithms such as Learning
Automated and Genetic Algorithm Approach, Improved Gravitational Search Approach and Dynamic particle
swarm optimization Approach. The simulation outcome showed a better performance of the suggested
methodology compared to existing methodologies.
Wireless Mesh Networks offers cost-efficient and higher network efficiency by utilizing multiple channels
multiple radio(MCMR) nodes. Also addition, the amalgamation of multiple radio nodes and multiple hops
mesh framework tends to overcome the limitation of single radio networks like the ability to achieve the rising
accessible system bandwidth. In spite of these benefits, certain MCMR wireless mesh networks still suffer from
performance issues like network connectivity, network throughput degradation whenever network size
increases. Thus, an effective channel assignment (CA) approach could minimize the number of interference cochannels and enhance the throughput of the network. Thus, a hybridized form of gravitational search approach
and particle swarm optimization is presented in this paper to resolve the issue of CA. The velocity and position
updates of PSO are merged with the GSA operations to obtain the best channel with good connectivity. This
approach maximizes the capability of exploration and exploitation for global and local searches using PSO
and GSA operations. The goal of this methodology is the minimization of a number of interfering links and the
maximization of network connectivity and throughput. The experimental results for this approach are carried
out using NS2 and compared with previously suggested heuristic optimization algorithms such as Learning
Automated and Genetic Algorithm Approach, Improved Gravitational Search Approach and Dynamic particle
swarm optimization Approach. The simulation outcome showed a better performance of the suggested
methodology compared to existing methodologies.
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