An optimum strategy for dynamic and stochastic packet routing problems by chaotic neurodynamics

An improved routing algorithm using chaotic neurodynamics for packet routing problems

“…We first describe the method to implement the conventional chaotic method [5][6][7][8][9]. Moreover, we explain how the conventional chaotic method fails to decentralize the packets if packet flow increases.…”

“…In the chaotic routing model [5][6][7][8][9], the ith node has a chaotic neural network with N i chaotic neurons, and the ijth neuron represents connections between the ith and the jth nodes. Furthermore, if the ijth neuron fires, a packet is transmitted from the ith to the jth adjacent nodes.…”

“…Typical examples of static combinatorial optimization problems are the traveling salesman problem [1,2], the quadratic assignment problem [3] and the vehicle routing problem [4], whereas examples of dynamic combinatorial optimization problems are the packet routing problem [5][6][7][8][9][10][11][12][13][14][15][16][17] and the traffic flow control problem [18]. In static combinatorial optimization problems, the search space of the solution does not change.…”

“…To remove the congestion in the networks, the routing method that autonomously distributes packet transmissions using chaotic neurodynamics has been proposed [5][6][7][8][9]. By using a refractory effect that successfully memorizes packet routing history, the routing method [5][6][7][8][9] is more successful at avoiding the loss of packets better than the sp-hop method.…”

“…By using a refractory effect that successfully memorizes packet routing history, the routing method [5][6][7][8][9] is more successful at avoiding the loss of packets better than the sp-hop method. However, we have noted that the chaotic method [5][6][7][8][9] fails to remove congestion at hub nodes if the number of packets continues to increase in the network.…”