الفهرس 
IntroductionOnly 14 pages are availabe for public view
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Abstract
As energy is considered one of the most valuable resources in the IoT, in this thesis we aim to achieve e ective management of energy utilization and maxi mize the lifetime of the IoT network. We can do this by applying the clustering approach, where the optimal selection for the cluster heads (CHs) in the IoT network will lead to consuming less energy. Consequently, the network will op erate for a longer time. So, we used one of the most recent swarm intelligence (SI) algorithms for selecting the optimal CHs. This algorithm is the Sun ower Optimization Algorithm (SFO) combined with the levy ight operator. First, we applied this algorithm in the wireless sensor network (WSN) and it demon strated its superiority in terms of reducing energy consumption for the sensor nodes in WSNs. After that we applied this algorithm in the IoT-WSN and it achieved more superiority in terms of reducing energy consumption for the IoT devices and maximizing IoT-WSN lifetime. Finally, to verify the performance of the proposed algorithm, we compare it with number of other previous algo rithms and the comparison showed that its superiority against other algorithms.