Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Dynamic Channel Allocation in Mobile Network by Fuzzy Logic


Affiliations
1 Department of Engineering, Dr.C.V. Raman University, Bilaspur, India
     

   Subscribe/Renew Journal


The fuzzy means of allocating WDM (wavelength division multiplexing) channels in a hierarchical all-optical network (AON) for the modified token medium access protocol is addressed. The goal is to minimize the average delay of local subnet and global bound traffic, and to maximize the number of nodes that can be supported by the network. This is achieved by allotting a minimum number of spatially-reuse channels to the subnets, which can accommodate a certain maximum number of nodes. Actually the minimum number of nodes that are sought for each subnet in terms of cost. By working out the maximum number of nodes for each subnet and the total subnets that can be supported, the optimum number of global channels and the overall total number of nodes for the entire network, can hence be determined. The packet generation rate and average delay in slot time are used to gauge the performance of the fuzzy channel allocation model. Recent demand for mobile telephone service has been growing rapidly while the electromagnetic spectrum of frequencies allocated for this purpose remains limited. Channel allocation schemes provide a flexible and efficient access to bandwidth in wireless and mobile communication system. In this paper, distributed dynamic channel allocation algorithm is the spatial distribution of channel demand changes with time, the spatial distribution of allocated channels adjusts accordingly. The algorithm guarantees relaxed mutual exclusion and provide necessary condition for information structure. The algorithm is deadlock free, starvation free and prevents co-channel interference.


Keywords

Fuzzy Solution, Fuzzy Optimization, Dynamic Channel Allocation, Grid Cellular System, Fuzzy Set, Node, Subnet, Global Channel, Global Delay, Local Delay, Local Channel.
User
Subscription Login to verify subscription
Notifications
Font Size

Abstract Views: 149

PDF Views: 1




  • Dynamic Channel Allocation in Mobile Network by Fuzzy Logic

Abstract Views: 149  |  PDF Views: 1

Authors

Tarun Dhar Diwan
Department of Engineering, Dr.C.V. Raman University, Bilaspur, India

Abstract


The fuzzy means of allocating WDM (wavelength division multiplexing) channels in a hierarchical all-optical network (AON) for the modified token medium access protocol is addressed. The goal is to minimize the average delay of local subnet and global bound traffic, and to maximize the number of nodes that can be supported by the network. This is achieved by allotting a minimum number of spatially-reuse channels to the subnets, which can accommodate a certain maximum number of nodes. Actually the minimum number of nodes that are sought for each subnet in terms of cost. By working out the maximum number of nodes for each subnet and the total subnets that can be supported, the optimum number of global channels and the overall total number of nodes for the entire network, can hence be determined. The packet generation rate and average delay in slot time are used to gauge the performance of the fuzzy channel allocation model. Recent demand for mobile telephone service has been growing rapidly while the electromagnetic spectrum of frequencies allocated for this purpose remains limited. Channel allocation schemes provide a flexible and efficient access to bandwidth in wireless and mobile communication system. In this paper, distributed dynamic channel allocation algorithm is the spatial distribution of channel demand changes with time, the spatial distribution of allocated channels adjusts accordingly. The algorithm guarantees relaxed mutual exclusion and provide necessary condition for information structure. The algorithm is deadlock free, starvation free and prevents co-channel interference.


Keywords


Fuzzy Solution, Fuzzy Optimization, Dynamic Channel Allocation, Grid Cellular System, Fuzzy Set, Node, Subnet, Global Channel, Global Delay, Local Delay, Local Channel.