# Energy-Efficient Connected-Coverage Scheme in Wireless Sensor Networks
## 1 Introduction
Based on the DEEC protocol, we jointly consider the remaining energy of the node and the distance between the sensor node and the base station to construct clusters with non-uniform size and avoid the use of low-energy nodes. Although above works can enhance the lifetime of the network, they only optimize energy consumption from one aspect, node scheduling or routing optimization. In fact, the energy consumption is determined by the number of redundant sensor nodes and the choice of routing jointly. The scheme combining the sensor nodes scheduling with the routing protocol designing can further improve the energy efficiency and network lifetime. In this paper, we try to achieve higher energy efficiency of the network through jointing the sensor nodes scheduling with the routing protocol optimization. When comparing with previous works, both two practical factors are considered, which has not been proposed before. Firstly, an efficient heuristic solution that is based on genetic algorithm (GA) is proposed to solve SCP. Therefore, the sensing energy can be reduced. A scheme is also proposed to select sleep sensor nodes to replace dead nodes. The network lifetime can be improved. After determining the fewest sensor nodes that can cover all MTPs, in order to enable the large network to run reliably and efficiently, we then optimize the routing protocol. An improved routing protocol, named the Improved-Distributed Energy-Efficient Clustering (I-DEEC), is proposed. The probability of cluster heads (CHs) is adjusted, according to the distance to the sink, the residual energy, and the average energy of sensor nodes. The network is then divided into many uneven clusters in order to make the energy consumed on data communicating more balanced. Each CH node is responsible to send collected data from other sensor nodes to the sink using the I-DEEC. Meanwhile, the data communication way of sensor nodes around the sink is also optimized, so that more energy can be saved. According to above discussion, our contributions are concluded as follows. 1. The scheme considering the scheduling of sensor nodes and optimization of the routing protocol jointly are proposed in order to improve the lifetime of the network. 2. Aiming at the multi-objective scheduling problem composed of three conflicting objectives: the largest network coverage, the least number of active nodes and awakening the sensor nodes with more residual energy, an Minimum Coverage Control Algorithm (MCCA) based on genetic algorithm is proposed to dynamically find the minimizing sensor set. Through activating the minimum number of sensor nodes to cover all MTPs, the problem of the redundant coverage can be avoided. At the same time, to keep the monitoring work, we also present the wake-up scheme to activate the sleep neighbor with high remaining energy to replace the exhausted node and keep the minimum active sensor node. 3. Considering the distance from sensor nodes to the sink and the energy distribution of the network, the I-DEEC routing protocol is designed to improve the clustering policy, optimize routing selection, and data transmission way. The sensor node can finds the most suitable way to send the data to the sink and the lifetime of the WSN is further prolonged. The remaining part is organized, as follows. Section 2 shows some related works on the node scheduling and routing protocol optimization. Section 3 introduces the system model, including system network model, energy consumption model and problem formulation. To solve the set covering problem, Section 4 presents an minimum coverage Control algorithm based on genetic algorithm. The I-DEEC routing protocol is also proposed in Section 5 to make the communication more efficient. Section 6 shows the performance of proposed algorithms. At last, Section 7 concludes this paper.