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Role of Fuzzy Logic in Information Routing-A Review


Affiliations
1 Punjab Technical University, Jalandhar, Punjab, India
2 Department of CSE, National Institute of Technology, Jalandhar, Punjab, India
3 Dept of Electronics and Communication Engineering, Doaba College of Engineering and Technology, Kharar, Punjab, India
     

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The routing is restricted by a multiple constraints such as node buffer capacities, residual link capacities, and the number ofhops on the path that often makes the routing problem intractable. These multiple constraints have very diverse effects on delay, delay jitter, loss ratio, bandwidth, and so on especially in distributed applications such as Internet phone and distributed games. Secondly, any future integrated services network is likely to carry both QoS and best effort traffic, which makes the issue of performance optimization complicated. Thirdly, the network state changes dynamically due to transient load fluctuation, connections in and out, link up and down and thus, the growing network size makes it increasingly difficult to gather up-to-date state information in such dynamic environments. The mathematical forms including these factors together becom extremely complex to derive and difficult to work with. This is one area where Adaptive fuzzy mechanism is beneficial.


Keywords

Fuzzy Logic Control, Fuzzy Algorithms, Routing Algorithms.
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  • Role of Fuzzy Logic in Information Routing-A Review

Abstract Views: 211  |  PDF Views: 2

Authors

Paramjit Singh
Punjab Technical University, Jalandhar, Punjab, India
Ajay K. Sharma
Department of CSE, National Institute of Technology, Jalandhar, Punjab, India
T. S. Kamal
Dept of Electronics and Communication Engineering, Doaba College of Engineering and Technology, Kharar, Punjab, India

Abstract


The routing is restricted by a multiple constraints such as node buffer capacities, residual link capacities, and the number ofhops on the path that often makes the routing problem intractable. These multiple constraints have very diverse effects on delay, delay jitter, loss ratio, bandwidth, and so on especially in distributed applications such as Internet phone and distributed games. Secondly, any future integrated services network is likely to carry both QoS and best effort traffic, which makes the issue of performance optimization complicated. Thirdly, the network state changes dynamically due to transient load fluctuation, connections in and out, link up and down and thus, the growing network size makes it increasingly difficult to gather up-to-date state information in such dynamic environments. The mathematical forms including these factors together becom extremely complex to derive and difficult to work with. This is one area where Adaptive fuzzy mechanism is beneficial.


Keywords


Fuzzy Logic Control, Fuzzy Algorithms, Routing Algorithms.