Networks today are continuously changing and network routing is a major challenge. This is due th... more Networks today are continuously changing and network routing is a major challenge. This is due the fact that the networks complexity is increasing and predominant in today’s internet. To cope up with this problem we use the advanced concepts of artificial intelligence and give a cognitive approach to the issues faced in networking. In our paper we give the detailed description of the implementation of the two algorithms namely Bacteria Foraging Algorithm (BFA) and Artificial Bee Colony (ABC). These algorithms were chosen to analyze how foraging algorithm and evolutionary algorithm run on network routing setup. We notice that when we use the BFA in our network setup we obtain an optimal path and then on the same setup if we run ABC algorithm we get an optimal path with better credentials. The focus here was to find the optimal path based on the bandwidth. We studied the setup for convergence rate, hop count and optimal cost found by the algorithms. We found that ABC was better than B...
Networks today are continuously changing
and network routing is a major challenge. This is due
... more Networks today are continuously changing
and network routing is a major challenge. This is due
the fact that the networks complexity is increasing
and predominant in today’s internet. To cope up with
this problem we use the advanced concepts of
artificial intelligence and give a cognitive approach to
the issues faced in networking. In our paper we give
the detailed description of the implementation of the
two algorithms namely Bacteria Foraging Algorithm
(BFA) and Artificial Bee Colony (ABC). These
algorithms were chosen to analyze how foraging
algorithm and evolutionary algorithm run on network
routing setup. We notice that when we use the BFA
in our network setup we obtain an optimal path and
then on the same setup if we run ABC algorithm we
get an optimal path with better credentials. The focus
here was to find the optimal path based on the
bandwidth. We studied the setup for convergence
rate, hop count and optimal cost found by the
algorithms. We found that ABC was better than BFA
in terms of the three factors considered above in the
simulation results.
Networks today are continuously changing and network routing is a major challenge. This is due th... more Networks today are continuously changing and network routing is a major challenge. This is due the fact that the networks complexity is increasing and predominant in today’s internet. To cope up with this problem we use the advanced concepts of artificial intelligence and give a cognitive approach to the issues faced in networking. In our paper we give the detailed description of the implementation of the two algorithms namely Bacteria Foraging Algorithm (BFA) and Artificial Bee Colony (ABC). These algorithms were chosen to analyze how foraging algorithm and evolutionary algorithm run on network routing setup. We notice that when we use the BFA in our network setup we obtain an optimal path and then on the same setup if we run ABC algorithm we get an optimal path with better credentials. The focus here was to find the optimal path based on the bandwidth. We studied the setup for convergence rate, hop count and optimal cost found by the algorithms. We found that ABC was better than B...
Networks today are continuously changing
and network routing is a major challenge. This is due
... more Networks today are continuously changing
and network routing is a major challenge. This is due
the fact that the networks complexity is increasing
and predominant in today’s internet. To cope up with
this problem we use the advanced concepts of
artificial intelligence and give a cognitive approach to
the issues faced in networking. In our paper we give
the detailed description of the implementation of the
two algorithms namely Bacteria Foraging Algorithm
(BFA) and Artificial Bee Colony (ABC). These
algorithms were chosen to analyze how foraging
algorithm and evolutionary algorithm run on network
routing setup. We notice that when we use the BFA
in our network setup we obtain an optimal path and
then on the same setup if we run ABC algorithm we
get an optimal path with better credentials. The focus
here was to find the optimal path based on the
bandwidth. We studied the setup for convergence
rate, hop count and optimal cost found by the
algorithms. We found that ABC was better than BFA
in terms of the three factors considered above in the
simulation results.
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Papers by Bharath Alva
and network routing is a major challenge. This is due
the fact that the networks complexity is increasing
and predominant in today’s internet. To cope up with
this problem we use the advanced concepts of
artificial intelligence and give a cognitive approach to
the issues faced in networking. In our paper we give
the detailed description of the implementation of the
two algorithms namely Bacteria Foraging Algorithm
(BFA) and Artificial Bee Colony (ABC). These
algorithms were chosen to analyze how foraging
algorithm and evolutionary algorithm run on network
routing setup. We notice that when we use the BFA
in our network setup we obtain an optimal path and
then on the same setup if we run ABC algorithm we
get an optimal path with better credentials. The focus
here was to find the optimal path based on the
bandwidth. We studied the setup for convergence
rate, hop count and optimal cost found by the
algorithms. We found that ABC was better than BFA
in terms of the three factors considered above in the
simulation results.
and network routing is a major challenge. This is due
the fact that the networks complexity is increasing
and predominant in today’s internet. To cope up with
this problem we use the advanced concepts of
artificial intelligence and give a cognitive approach to
the issues faced in networking. In our paper we give
the detailed description of the implementation of the
two algorithms namely Bacteria Foraging Algorithm
(BFA) and Artificial Bee Colony (ABC). These
algorithms were chosen to analyze how foraging
algorithm and evolutionary algorithm run on network
routing setup. We notice that when we use the BFA
in our network setup we obtain an optimal path and
then on the same setup if we run ABC algorithm we
get an optimal path with better credentials. The focus
here was to find the optimal path based on the
bandwidth. We studied the setup for convergence
rate, hop count and optimal cost found by the
algorithms. We found that ABC was better than BFA
in terms of the three factors considered above in the
simulation results.