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Most sensor networks are deployed at hostile environments to sense and gather specific information. As sensor nodes have battery constraints, therefore, the research community is trying to propose energyefficient solutions for wireless sensor networks (WSNs) to prolong the lifetime of the network. In this paper, we propose an energy-efficient multi-level and distance-aware clustering (EEMDC) mechanism for WSNs. In this mechanism, the area of the network is divided into three logical layers, which depends upon the hop-count-based distance from the base station. The simulation outcomes show that EEMDC is more energy efficient than other existing conventional approaches. Figure 15. Number of nodes alive over simulation time (seconds).

The range of applications of Wireless Sensor Networks (WSNs) is increasing continuously despite of their serious constraints of the sensor nodes' resources such as storage, processing capacity, communication range and energy. The main issues in WSN are the energy consumption and the delay relaying data. This becomes extremely important when deploying a big number of nodes, like the case of industry pollution monitoring. We propose an energy-efficient load-balancing group-based WSN called ELDC, where groups may have different sizes and different routing protocols. We use a group chief node selection technique for each group which is based on an artificial neural network and allows intelligent group organization. Our proposed technique is highly energy-efficient capable to increase sensor nodes' lifetime. Simulation results show that it outperforms LEACH protocol by 42%, and other implemented protocols by more than 15%.

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