# Multiparameter Fusion Decision Routing Algorithm for Energy-Constrained Wireless Sensor Networks
## 1 Introduction
### Related Work
Among them, a routing algorithm derived from a Nonlinear Weighted Particle Swarm Optimization algorithm (NWPSO) is introduced in [20] to prolong the network lifetime. By combining energy efficiency with transmission distance, the network can provide a better distributed and balanced sensor cluster system, thus improving the network life cycle. In [21], an ant colony routing algorithm has been developed; the algorithm uses the enhanced heuristic function and analyzes the distance of nodes, transmitting direction, and remaining energy, and it can work out the optimal route between source and destination. Considering the trade-off between the transmission radius and substantial transmission energy cost, the authors of [22] propose a WSN energy utilization model to achieve a higher packet of successful acceptance. To solve the energy hole problem, [23] proposes a dynamic routing algorithmbased on a transmission distance adjustment method, which changes the nodes coverage with its residual energy and the distance to anchors, so that each node can attain energy balance. Those methods roughly resolve the imbalance obstacle of energy consumption in WSNs from the perspective of the residual energy or node transmission distance. The implementation of energy balance routings in [24; 25; 26; 27; 28] is also an effective means of extending the life of the network. In [24], to minimize the total energy consumption minimize and equilibrate the network load, the authors put forward a General Self-organized Tree-based Energy Balance routing protocol (GSTEB). This protocol uses a process to build a routing tree and select a new root node in the process of each round. Then, each node selects its parent node depending on its neighbor's information. In [25], the authors propose a distributed routing algorithm based on game theory. The proposed protocol achieves a prolonged network lifetime by balancing communication loads across nodes in the region and within the region. In [26], to balance energy consumption, the authors designed a next-hop node selection algorithm based on a fuzzy classifier. It classifies nodes at relative levels with node's gradient. The maximum residual energy node at each level has the opportunity as the next hop. Then, in consideration of these algorithms and directed diffusion, this paper proposes an energy-balanced routing protocol to rationally utilize the limited energy, reduce the average energy consumption, and achieve WSN lifetime maximization. In [27], the authors model the monitoring region as a concentric centered on the sink and propose a mechanism to eliminate energy holes. This mechanism equalizes the energy loss of total nodes in the ring and extends the network lifetime. To effectively reduce and keep network energy balance, the authors in [28] analyzed different energy and flow models and proposed an Energy-balanced Distance-based Routing Algorithm (EDRA). The algorithm enables all nodes to utilize energy at a similar rate when the distance has been given. It is one of the primary design objectives of WSNs to save and equalize the used energy and maximize the network survival time [29; 30]. Important works from the literature, including the above-listed algorithms [13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27; 28], provide some referential solutions. However, in a WSN, information congestion may occur when many sensors send data concurrently. In other words, congestion is more likely to happen when a sensor sends packets continuously. Because of this, the network packet loss ratio will increase, and the transmission efficiency of the network will be affected. Therefore, congestion control [31; 32] becomes a key challenge. In [31], by taking advantage of the node's hop-by-hop feedback information mechanism, the Distributed Predictive Congestion Control algorithm (DPCC) is proposed. DPCC uses a queue utilization rate and an embedded channel estimation algorithm for congestion detection.