## 2 Related Work
### Ant Routing  
As an effective distributed approach, the ACO algorithms have been introduced to the design of routing protocol and have received many achievements [17-25].  
The ACO algorithm was first used in traditional networks [17]. ARA [18] was the first algorithm used in mobile ad hoc networks (MANETs), which exploits the pheromone laying behavior of ants to search for routing. The above two algorithms are however not suitable for WSNs. In [19], [PERSON] _et al._ used an improved ACO algorithm (PACO) to search for multipaths between source nodes and the sink node in MANETs. Although the PACO improves the efficiency of data transmission, the number of ants required to search for routing is great, resulting in great energy consumption at the start-up stage. Moreover, the PACO only uses the length of path as metric without considering the current energy of nodes: these discovered paths may contain the low energy nodes, which will shorten the working time of the paths.  
Recently, routing protocols based on ACO for WSNs have been the focus of many studies [20-25]. In [20], [PERSON] _et al._ studied three distinct Ant-based algorithms for WSNs. However, the algorithms only focus on the building of an initial pheromone distribution, and thus, the algorithms are only good at system start-up phase. In [21], [PERSON] _et al._ presented a new WSNs routing algorithm based on ACO, which can minimize communication load and save energy. Nevertheless, the algorithm does not consider the feature of data correlation, the energy consumption of communication is huge when a lot of sources exist in the network. In [22], [PERSON] _et al._ introduced a routing strategy on the basis of ant algorithm for WSNs, using deflection angle, energy and distance as routing factors to help the ant to search for routing. The convergence rate of the algorithm is good. However, the algorithm did not utilize the redundancy of data, and thus the algorithm has the same disadvantage as [21]. A reinforcement learning scheme is proposed in [23], which reduces the energy consumption and shortens the time delay. The algorithm, however, only uses the distance as metric, so it cannot protect the minimum energy node, and therefore, it may shorten the network lifetime. In [24], [PERSON] _et al._ constructed a chain by means of an ant colony algorithm that connects all the nodes in the networks. Although the algorithm can find suboptimal routing for mobile agents, the time delay of the algorithm is long, and the cost of reconstructing routing is also high. In [25], [PERSON] _et al._ proposed a multipath routing based on ant colony system, which extends the network lifetime. Although the algorithm balances the energy consumption among nodes by multipath, it does not take into consideration the influence of the minimum energy node on multiple paths. In [26], [PERSON] _et al._ presented an ACO-based multipath routing, which provides good energy efficiency. However, the algorithm belongs to a kind of flat routing, therefore, its scalability is not good.  
Although these algorithms presented above have some advantages, there still exist some shortcomings that prevent their application in large scale WSNs. To overcome the disadvantages of conventional ant-based routing algorithms, we propose an improved protocol by integrating the advantages of hierarchical routing, multipath routing and ACO.