Background:
In recent era of technology, the traditional Ant Colony Algorithm (ACO) is insufficient in
solving the problem of network congestion and load balance, and network utilization.
Methods:
This paper proposes an improved ant colony algorithm, which considers the price factor based on the theory of
elasticity of demand. The price factor is denominated in the impact on the network load which means indirect control of
network load, congestion or auxiliary solution to calculate the idle resources caused by the low network utilization and
reduced profits.
Results:
Experimental results show that the improved algorithm can balance the overall network load, extend the life of
path by nearly 3 hours, greatly reduce the risk of network paralysis, and increase the profit of the manufacturer by 300
million Yuan.
Conclusion:
Furthermore, results shows that the improved method has a great application value in improving the network
efficiency, balancing network load, prolonging network life and increasing network operating profit.
Influence of network load on the performance of opportunistic scanning
