## 2 Related Works
Energy heterogeneity means that the heterogeneous nodes are line powered, or their battery is replaceable. Among the above three types of resource heterogeneity, the most important heterogeneity is the energy heterogeneity, because both computational heterogeneity and link heterogeneity will consume more energy resources. If there is no energy heterogeneity, computational heterogeneity and link heterogeneity will have a negative impact to the whole sensor network, _i.e._, decreasing the network lifetime. In wireless sensor networks, due to the widespread presence of heterogeneous resource nodes, many researchers have done profound work probing into HWSNs. In [19], [PERSON] _et al._ proposed an energy efficient heterogeneous clustered (EEHC) scheme for heterogeneous wireless sensor networks, which particularly presented the setting, the energy model, and how the optimal number of clusters could be computed. In order to make more rational use of network energy and prolong the lifetime of multilevel heterogeneous wireless sensor networks, [PERSON] _et al._ proposed a new heterogeneous sensor network model with heterogeneity of monitored objects and energy heterogeneity of all nodes, called energy-efficient prediction clustering algorithm (EEPCA) [20]. The low-energy nodes will die more quickly than the high-energy ones, because these clustering algorithms are unable to treat each node discriminator in terms of the energy discrepancy. Therefore, a heterogeneous network model in term of different initial energies was discussed in [20]. From the viewpoint of a scheme for the selection of cluster heads, models with energy heterogeneity can be separated into two categories: models with fixed cluster heads and models with periodically selected cluster heads. The former consider that the node with more initial energy will act as a cluster head directly, while the others do the basic sensing as well as data transmission in a cluster. However, in many application scenes, it is always impossible to deploy the cluster head nodes for an optimal distribution between different types of nodes, which may weaken the energy efficient strategies in HWSNs. As for the latter, all nodes will have chances to be selected as cluster heads under the LEACH protocol, and most algorithms select cluster heads based on some weighted probability of each node related to the residual energy. In [21], [PERSON] _et al._ proposed a novel stable selection and reliable transmission protocol for clustering in heterogeneous wireless sensor networks, which can be applied to networks with three different kinds of heterogeneous nodes. Nodes in this protocol were divided into two common types: one performing the function of managing information and the others collecting different data (type 0, type 1). Type 1 had more complex hardware and software architectures, so they had more initial energy and greater data transfer capability, but the application of this protocol had been limited to networks with only two types of ordinary nodes. In [22], [PERSON] and [PERSON] proposed a new evolutionary algorithm based on a routing protocol for heterogeneous wireless sensor networks, which had an appropriate fitness function and the intrinsic properties of clustering in mind.