# Autonomous Load Regulation Based Energy Balanced Routing in Reshargeable Wireless Sensor Networks
## 2 Related Work  
Many scientists have devoted efforts to optimize charging schemes that can prolong the lifetime of WSN. A number of studies have focused on the adjustments of the traverse route of a single MCV to improve charging efficiency and extend network lifetime. [PERSON] [11] proposed an optimization model to select the minimum number of landmarks according to the locations and energy replenishment requirements of the sensors. [PERSON] [12] developed a near-optimal solution by a piecewise linear approximation technique to optimize the traverse route. An MCV can only charge a single node at a time in the algorithm mentioned above. For higher charging efficiency and less travel distance, [PERSON] [13] used Reformulation-Linearization Technique (RLT) to optimize the charging algorithm with multi-node charging technology. [PERSON] [14] used the algorithm Multi-node Renewable based on Charging Range (MRCR) to obtain a shortest length in every round to improve charging efficiency. However, the algorithms above ignored the importance of reasonable power allocation for multiple nodes. Due to the high transmission loss rate of wireless energy, an MCV should allocate power for each node in the same cell according to their charging efficiencies and energy states reasonably. Our algorithm uses an efficient power allocation scheme to charge for low energy nodes in a timely manner, and can thus extend the network lifetime. Another effective way to extend the lifetime of WSN is by optimizing routing algorithms. Numerous multi-hop routing algorithms balance load through next-hop selection. [PERSON] [15] used the principles of fuzzy ant colony optimization routing (FACOR) to develop a suitable problem solution. [PERSON] [16] proposed the gravitation model to balance energy by'space gravitation', considering the spatial relationship of nodes and 'time gravitation', which takes into account the waiting time of data packets. [PERSON] [17] proposed a dynamic energy balance max flow routing algorithm to maximize the load flow within the network lifetime and balance energy consumption to prolong the network lifetime. [PERSON] [18] proposed a solution to sufficiently maintain energy efficiency and avoid congestion for energy-unlimited WSN. [PERSON] [19] proposed an improved ant colony algorithm that can be used to construct the sensor node transfer function and pheromone update rule; it can also adaptively choose a data route by adopting the advantages of the dynamic state of the network. However, current energy-efficient routing strategies and charging technologies are relatively mature. The effect of extending the network lifetime is limited by simply relying on the optimization of a routing strategy. Our algorithm connects wireless charging technology with a routing strategy effectively, where the nodes with low energy can obtain energy replenishment in a timely manner. Thus, the network lifetime can be extended greatly. Inspired by the effects of extending network lifetime, some works have connected the multi-hop routing strategy with charging technology. [PERSON] [20] attempted an approach based on the shortest path algorithm and grid clustering to save and renew power in a way that minimizes energy consumption and prolongs the overall network lifetime of WSN. [PERSON] [21] proposed an optimization algorithm from the aspects of both charging and routing processes. In [22], a joint energy supply and routing path selection algorithm was proposed to extend the network lifetime based on an initiative power supply. However, the node accepts the relay request of its neighbor unconditionally in the routing algorithms above and cannot remove its overload by itself in a timely manner. The load balancing efficiency of the network is limited by this passive mechanism. Furthermore, the energy balance efficiency of an MCV may be reduced due to the energy replenishment of a few high-load nodes over a long time period.