Mohammad Amin Sadeghi - Department of Computer Engineering, Instructor, Jahrom Islamic Azad University, Jahrom, Iran
Reza Asadinejad - Department of Computer Engineering, Jahrom Islamic Azad University, Jahrom, Iran
Fatimah golkar - Department of Computer Engineering, Jahrom Islamic Azad University, Jahrom, Iran

In recent years a strong tendency to use artificial intelligence techniques to reduce energy consumption in wireless sensor network was created. Especially artificial neural networks due to unique features such as automatic data classification, dimension reduction, easy processing and so on as effective and powerful tool for almost every aspect of reducing energy consumption in wireless sensor network applications. To achieve this goal, a joint practical and efficient routing, called J-ROC, offered to prolong the life of the sensor network and now design, implement common routing, charging plan, assess the effectiveness and benefits of long-wetting energy demand in the routing common charging scheme can significantly extend the lifetime of the sensor network. To collect periodic data, E2C method that delivers energy efficient and balanced clustering. Results show that clusters of energy-efficient performance and increased lifetime of the network node provides the same level of energy. Compared with known clustering algorithms such as LEACH, HEED, EECS, in terms of energy conservation and equality, energy-efficient cluster better.

Data Aggregation, Wireless Sensor Network, Cluster Head, Mobile Charging Technology, E2c, J-Roc