Reducing the energy consumption of network nodes is one of the most important problems for routing in wireless sensor networks because of the battery limitation in each sensor. This paper presents a new ant colony optimization based routing algorithm that uses special parameters in its competency function for reducing energy consumption of network nodes. In this new proposed algorithm called life time aware routing algorithm for wireless sensor networks (LTAWSN), a new pheromone update operator was designed to integrate energy consumption and hops into routing choice. Finally, with the results of the multiple simulations we were able to show that LTAWSN, in comparison with the previous ant colony based routing algorithm, energy aware ant colony routing algorithms for the routing of wireless sensor networks, ant colony optimization-based location-aware routing algorithm for wireless sensor networks and traditional ant colony algorithm, increase the efficiency of the system, obtains more balanced transmission among the nodes and reduce the energy consumption of the routing and extends the network lifetime.
A wireless sensor network (WSN) typically consists of tens to hundreds or thousands of relatively small nodes, each equipped with a sensing device. Most sensor networks use wireless communication, and the nodes are often battery powered. Their limited resources, restricted communication capabilities, and constrained power consumption demand that efficiency be high on the list of design criteria . As a result of the advances in wireless communication and electronics technologies, wireless sensors are getting smaller, cheaper, and more powerful. Due to the fast development of the microprocessor, sensor and transceiver, there is great applications foreground about WSNs. Also since we often use these networks in rough and inaccessible environments such as battlefields, volcanoes, forests and so on, normally there is low possibility to change or recharge the defective or dead nodes. Hence, the main difference between WSNs and other classic wireless networks is that WSNs are hypersensitive and vulnerable to energy .
The limit energy is the key issue influencing WSNs performance. So, how to use the limit energy of WSNs to maximize the life of WSNs becomes the all-important problem of routing design . Most of the routing algorithms for sensor networks require location information for sensor nodes. In most cases location information is needed in order to calculate the distance between two particular nodes so that energy consumption can be estimated . Therefore, location information can be utilized in routing data in energy efficient way.
A family of ant colony optimization (ACO) algorithms has been successfully applied to solve some routing problems in WSN . Over the last two decades, ant colony optimization has emerged as a leading Meta heuristic method for the solution of combinatorial optimization problems .
In this paper, we proposed a routing algorithm for wireless sensor network based on ant colony optimization with special parameters. The main objective of the algorithm is to maximize the network lifetime by carefully defining link cost as a function of node remaining energy and the required transmission energy using that link. We call the proposed algorithm as life time aware routing algorithm for wireless sensor networks (LTAWSN) and compare it with energy aware ant colony routing algorithms for the routing of wireless sensor networks (EAACA) that presented in , ant colony optimizationbased location-aware routing algorithm for wireless sensor networks (ACLR) that presented in [5, 7], and traditional ant colony routing algorithm ACA, and see that proposed algorithm reduce consumption of energy in comparison of these routing algorithms, obtains more balanced transmission among the node, therefore extends the network lifetime.
The rest of this paper is organized as follows. In Sect. 2, some of the recent researches about ant colony routing algorithm in wireless sensor networks are presented. In Sect. 3, the proposed approach is described. Section 3 represents the simulation parameters. Section 4 discusses about the simulation results and finally Sect. 5 concludes the paper.
2 Related work
Some of the recent researches about ant colony routing algorithm in wireless sensor networks are presented as follows:
The authors in  proposed a routing algorithm for wireless sensor networks using ant colony optimization that present a comparison of two ant colony-based routing algorithms, taking into account current amounts of energy consumption under different scenarios and reporting the usual metrics for routing in wireless sensor networks.
In , the authors proposed an energy aware ant colony algorithm for the routing of wireless sensor networks that when the ant chooses the next node, not only the distance of sink node, but also the residual energy of next node and the path of the average energy are taken into account. This algorithm was compared with traditional ACA algorithm and gets more improvement in balance the energy consumption of nodes and extends the network life time.
In , the authors proposed a fair comparison of low energy adaptive clustering hierarchy (LEACH) and ant colony applied on LEACH on the basis of the death of first node in the wireless sensor networks and is shown that when the ant colony algorithm is applied on existing LEACH protocol, the network lifetime has improved.
In  first, a grade table is build and referred to generate several possible routing paths. Then the ACO explores these paths to reduce the power consumption of the nodes.
In  each node calculates the amount of its own energy level and then sums up the energy level of the remaining network. With the help of this comparison the node decides whether to become the cluster head or not for that round. The nodes with higher energy are more likely to become cluster heads. The drawback of this approach is that it requires extra communication of nodes with base station which in turn needs more energy.