Increasing the Amount of Data and Reducing the Cost of Using Network Coding in Wireless Sensor Networks

This paper presents an optimization model to increase the amount of data collected and balance the bandwidth consumption of the edges and uses network coding. To solve this model, the dual method is used and to calculate a lower bound and find the optimal answer and point in the optimization model, the Karush-KunTucker condition is used, which requires calculating the derivative of the Lagrangian function with respect to its variables. Solving this problem and equations in polynomial time is very difficult, time consuming and almost impractical due to the involvement of different parameters and limited resources of wireless sensor networks with a large number of nodes, so to solve this problem, a distributed and iterative algorithm is proposed. It uses the sub gradient method and the network flow separation method. The effectiveness of the proposed model and algorithm has been investigated by simulation in terms of number of source sensor nodes, Lagrangian coefficient and step size. Up to 23% of bandwidth consumed, average network life and energy consumed.