Water quality sensor networks are widely used in water resource monitoring. However, due to the fact that the energy of these networks cannot be supplemented in time, it is necessary to study effective routing protocols to extend their lifecycle. To address the problem of limited resources, a routing optimization algorithm based on a small-world network model is proposed. In this paper, a small-world network model is introduced for water quality sensor networks, in which the short average path and large clustering coefficient of the model are used to construct a super link. A short average path can reduce the network’s energy consumption, and a large coefficient can improve its fault-tolerance ability. However, the energy consumption of the relay nodes near the heterogeneous node is too great, and as such the energy threshold and non-uniform clustering are constructed to improve the lifecycle of the network. Simulation results show that, compared with the low-energy adaptive clustering hierarchy routing algorithm and the best sink location clustering heterogeneous network routing algorithm, the proposed improved routing model can effectively enhance the energy-utilization. The lifecycle of the network can be extended and the data transmission amount can be greatly increased.
Environmental protection is an important topic, and safeguarding ecology and the environment has become a global research focus. In particular, the protection of the water environment is an important part of ecological protection [
Although scholars carried out numerous pertinent studies, the problem of the limited network lifecycle caused by limited resources is still severe. To solve this problem, we propose a non-uniform clustering routing optimization algorithm based on small-world characteristics. Compared with the traditional routing protocol, it can effectively improve resource utilization, and has practical operability for water environment monitoring.
To protect the water environment, a flow model was built to simulate the working process of a water quality sensor network under practical water environment conditions. Water quality sensors were deployed to measure water quality parameters. The water quality sensor network was formed by a routing protocol and fed back to the monitoring and control center. Throughout the monitoring process, the water quality sensor nodes were powered by batteries, and the total energy of the entire network was limited. As shown in
The small-world characteristics of complex networks were analyzed to address the energy problem. The concept of small-world characteristics was proposed by Watts and Strogatz in 1998. A small-world network requires that a network with a small average path length still has a large clustering coefficient. The definition of a small-world network is as follows: if the distance L between two randomly selected nodes in the network (i.e., the number of hops required to access each other) increases proportionally with the logarithm of the number of nodes n in the network, i.e.,
Heterogeneous nodes are deployed to form a small-world network model with super links. The preset common nodes are powered by batteries, and their energies are limited. However, the energies of heterogeneous nodes can be supplemented. In the network model, sink nodes exist in the monitored area, and ordinary nodes transmit the monitored information to the sink node through multiple hops or super links. It is specified that each node in the network cannot move and has a unique ID. The steps of constructing a Watts–Strogatz small-world model (WS small-world model) are as follows: starting from the regular graph, n nodes form a ring, in which each node is connected with each K/2 node that is adjacent to it, where K is an even number [
In wireless sensor networks, a shorter average path can reduce the energy consumption of the network, and a larger clustering coefficient can improve the fault tolerance ability of the network. Therefore, the network can continue to work when some nodes are dead, which can improve the network lifecycle [
A routing protocol based on small-world characteristics (RPSC) is introduced in this paper. We find that there are still some shortcomings in the RPSC. In heterogeneous sensor networks with small-world characteristics, ordinary nodes adopt a greedy routing strategy according to their location [
To solve the problem of fast energy consumption and data redundancy of the nodes that are near sink and heterogeneous nodes, an improved routing protocol based on small-world characteristics (IRPSC) is proposed by introducing the idea of non-uniform clustering. In a non-uniform cluster, the cluster head is the manager of the data transmission. An energy threshold is proposed to select the cluster head through multiple iterations. Thus, an effective energy consumption model is established.
The common nodes that are close to the heterogeneous nodes are responsible for the relay task and exhibit a high energy consumption. The same problem exists near the sink nodes. The idea of non-uniform clustering is used for optimization [
The energy consumption of the nodes closer to the heterogeneous nodes
where
Clusters of different sizes are formed according to the distance between the ordinary nodes and heterogeneous nodes, and cluster heads are selected in rounds. Because the cluster head is responsible for the information transmission between heterogeneous nodes, the node with the largest energy value in the cluster is selected as the cluster head node. On this basis, the energy threshold
where
The data transmission mode in the network is shown in
In IRPSC, by using the idea of non-uniform clustering, ordinary nodes transmit data to the cluster head. The cluster head can compress the data of the member nodes in the cluster to reduce energy consumption during data transmission. However, due to the rotation of the cluster head, the transmission path between nodes changes, and thus the energy consumption of network nodes is uniform and the lifecycle of the entire network is improved. In addition, the effective energy threshold and sleep state control can balance the energy consumption of the network and further improve the overall lifecycle of the network.
The number of heterogeneous nodes to be deployed in the water quality sensor network is specified as β, and the deployment locations of β heterogeneous nodes are found by an ant colony algorithm [
To prove the effectiveness of the IRPSC algorithm, two kinds of heterogeneous algorithms were introduced: the improved LEACH-C (ILC), and best sink locations (BSL). To analyze the experimental results, MatLab (MathWorks, USA) was used to carry out simulation experiments. It was assumed that 100 nodes were randomly distributed in the 100 × 100-m2 network area, and the sink node was located in the interior of the sensor network area.
The data transmission amount of the four algorithms is compared in
In view of the limited resources available to water quality sensor networks, the energy consumption of the network can be reduced by constructing super links by introducing the small-world model of complex networks. However, the network is still inadequate. Based on the construction of a water quality sensor network with a small-world model, a heterogeneous sensor network is built based on the idea of heterogeneous clustering. Data compression and other processes are used to reduce energy consumption in the data transmission process. A cluster head rotation mechanism shortens the transmission path of nodes and controls the sleep state so that the energy consumption of network nodes is uniform and the network lifecycle is prolonged.