One of the most significant difficulty in Wireless Sensors Network (WSN) is the development of an effective topology control method that can support the quality of the network, respect the limited memory and at the same time increase the lifetime of the network. This paper introduces a new approach by mixing a non-cooperative Game Theory technique with a decentralized clustering algorithm to address the problem of maximizing the network lifetime. More precisely, this approach uses Game Theory techniques to control the activities of a sensor node and its neighbors to limit the number of the forwarding messages and to maximize the lifetime of the sensor's battery. In other words, the approach will decrease the energy consumed by the WSN by decreasing the number of forwarded packets and improve the network lifetime by harvesting energy from the environment. The simulations results show that the performances in terms of energy saving and increasing the number of data packets received by base station outperforms those with distributed based clustering algorithms without GT, such as low energy and location based clustering LELC and LEACH algorithms. 2. Related work 2.1. Clustering

Wireless Sensor Networks (WSNs) are extensively used in monitoring applications such as humidity and temperature sensing in smart buildings, industrial automation, and predicting crop health. Sensor nodes are deployed in remote places to sense the data information from the environment and to transmit the sensing data to the Base Station (BS). When a sensor is drained of energy, it can no longer achieve its role without a substituted source of energy. However, limited energy in a sensor's battery prevents the long-term process in such applications. In addition, replacing the sensors' batteries and redeploying the sensors is very expensive in terms of time and budget. To overcome the energy limitation without changing the size of sensors, researchers have proposed the use of energy harvesting to reload the rechargeable battery by power. Therefore, efficient power management is required to increase the benefits of having additional environmental energy. This paper presents a new selfmanagement of energy based on Proportional Integral Derivative controller (PID) to tune the energy harvesting and Microprocessor Controller Unit (MCU) to control the sensor modes.

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Wireless Human Body Sensors Network LifetimeOne of the most critical challenge concerning Wireless Human Body Sensors Network is how to prolong the lifetime of the network. There is not only one definition of lifetime.

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