Ant colony algorithm is a classical routing algorithm. And it are used in a variety of application because it is economic and self-organized. However, the routing algorithm will expend huge amounts of energy at the beginning. In the paper, based on the idea of Dijkstra algorithm, the improved ant colony algorithm was proposed to balance the energy consumption of networks. Through simulation and comparison with basic ant colony algorithms, it is obvious that improved algorithm can effectively balance energy consumption and extend the lifetime of WSNs.

Ant colony algorithms that emerged by M. Dorigo et al. [

In the paper, we propose improved ant colony algorithm to acquire the optimal path by routing optimization. We try to save the energy consumption and prolong network life under the condition that the path meets the needs.

Dijkstra algorithm is proposed by Dutch computer scientist Edsger Wybe Dijkstra to solve problem about the shortest path from an original point to other points in the directed graph.

Every point updates the shortest path information from the original point. It is usually defined as follows.

Suppose

At the initial moment,

In the ant colony algorithm model, wireless sensor network could be described as an undirected graph. At the beginning, the lack of initial pheromone leads to low solving speed and high consumption, which has affected the overall performance of ant colony algorithm [

Node number

If

Through the operation, the node gets the information about routes from the node to the end point. The routes have no back haul.

Simulated with the search food process of ant colony, the model for basic ant colony algorithm is as follows.

Suppose

In order to balance the energy consumption of nodes, improved ant colony algorithm entered the energy factor based on the basic ant colony routing algorithm to find shorter and high energy path. Then, the improved probability from node

Subset

Computation on simulation examples and comparison with basic ant colony routing algorithm show that improved ant colony routing algorithm is effective. As shown in Figure

Node distribution.

Comparing the life cycle of two algorithms, we suppose energy consumed is 0.1 J by receiving and sending information. As is shown in Figure

Comparison of the duration of the energy consumption in two algorithms.

Comparison of life cycle in two algorithms.

On the other hand, Table

Average routing distance comparison.

Algorithm | Improved ant colony routing algorithm | Basic ant colony routing algorithm |
---|---|---|

1 | 114.354 | 304.503 |

2 | 114.518 | 269.581 |

3 | 114.700 | 267.072 |

4 | 114.261 | 319.672 |

5 | 114.559 | 339.222 |

6 | 113.953 | 266.705 |

7 | 113.710 | 301.923 |

The wireless sensor network has distinguishing characteristics such as weak node calculation ability and energy limited node, so we should make it efficiency and save sources in the design of wireless sensor network routing algorithm. Ant colony algorithm is a new heuristic searching algorithm, which has many advantages in route optimization but wastes some time and energy due to pheromone deficiency. Therefore, this paper puts forward improved ant colony routing algorithm, which is inspired by the Dijkstra algorithm changing the wireless sensor network undirected graph to directed graph and energy equilibrium consumption ideas to improve the ant colony algorithm.

Compared with basic ant colony routing algorithm, improved ant colony routing algorithm is an algorithm with low energy and has high performance.

The authors declare that there is no conflict of interests regarding the publication of this paper.

This work is supported by Beijing Education Science and Technology Development Program (KM201110016015).