Abstract
Optimization models related with routing, bandwidth utilization and power consumption are developed in the wireless mesh computing environment using the operations research techniques such as maximal flow model, transshipment model and minimax optimizing algorithm. The Path creation algorithm is used to find the multiple paths from source to destination.A multi-stage optimization model is developed by combining the multi-path optimization model, optimization model in capacity utilization and energy optimization model and minimax optimizing algorithm. The input to the multi-stage optimization model is a network with many source and destination. The optimal solution obtained from this model is a minimum energy consuming path from source to destination along with the maximum data rate over each link. The performance is evaluated by comparing the data rate values of superimposed algorithm and minimax optimizing algorithm. The main advantage of this model is the reduction of traffic congestion in the network. Keywords-optimization; breakthrough; transportation; aximization; superimposed; transshipment.
Highlights
If b>0 the optimal flow from j to i is b. we develop an optimization model which utilizes the capacity of the link effectively
A maximization type transportation problem can be converted into usual minimization type transportation problem by subtracting each of the costs from the highest cost given in the problem to obtain only the optimal solution
Routers and bridges).Since we consider a network with one source and one destination and rest of the nodes to forward packets, we apply transshipment model to develop an optimization model in power consumption
Summary
Let s be the source node and N be a set of neighbor nodes of source. Let xij be the rate of transmission of packets over the link (i,j) and cij be the capacity of the link (i,j). (Total incoming flow = Total outgoing flow) xij cij (capacity constraint) xij 0 (non-negativity restrictions). Even though this LPP can be solved using simplex method, we are using a simple and efficient algorithm called maximal flow algorithm [20] to find the maximal flow. 1) Maximal Flow Algorithm Step 1: For all links set the residual capacity equal to the initial capacity and label source node 1 with [ , -]. If the sink node has been labeled (i.e., k = n) and a breakthrough path is found, go to step 5. If b>0 the optimal flow from j to i is b. we develop an optimization model which utilizes the capacity of the link effectively The advantage of this model is the elimination of congestion problem in the network
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