Abstarct: Internet of Things networks are one of the most important tools for obtaining information and understanding the environment, nowadays. Internet of Things applications usage have increased in various fields, it is very important to address the challenges of this field. On the other hand, one of the most important issues in these field is reducing energy consumption or increasing lifespan. Therefore, it is important to design appropriate protocols in order to save energy consumption. The cluster network is one of the most efficient architectures in terms of energy consumption and performance improvement. In this thesis, we intend to use the Manta Ray algorithm to address mentioned issues with proper clustering, optimal cluster head selection along with the optimal cluster head rotation and etc. The proposed method increases intra-cluster and extra-cluster communication rates due to the limited transmission range of each node. It is also possible to create the desired route in advance in order to increase the lifetime of the network, which is known as Customized Proactive Route. To keep in mind forming a neighborhood table is suggested method for systems improvement which plays an important role, especially in specific and emergency situations where the previous route is inactive. The results of this method were compared with rival approaches in literature under same conditions (transmission speed, transmission range, etc.) for different scenarios. In summary, the obtained results illustrate that the proposed method has improved the delivery ratio, network lifespan, number of dead network nodes, energy consumption and etc.