Energy efficiency is a main issue in a wireless local area network. Reducing energy consumption lowers the environmental impact of the network and it prolongs the lifetime of the devices, which are usually powered by means of batteries. The basic mechanisms for energy savings specified in the IEEE 802.11 standard are transmit power control, which directly affects the energy cost of the communication, and alternation of awake and sleep states, as the battery consumption in sleep state is negligible. However, low transmission power and long sleeping time reduce the message success rate and the responsiveness of the network. This paper presents a fuzzy logic solution for dynamically adjusting both transmission power and sleeping time in an IEEE 802.11 wireless network. The proposed approach is validated through simulations, which show a battery life 20% longer than other state-of-the-art approaches, and by means of a real testbed, which confirms the simulated results.

A fuzzy approach for power savings in both infrastructure and ad hoc WLANs

Mario Collotta;
2018-01-01

Abstract

Energy efficiency is a main issue in a wireless local area network. Reducing energy consumption lowers the environmental impact of the network and it prolongs the lifetime of the devices, which are usually powered by means of batteries. The basic mechanisms for energy savings specified in the IEEE 802.11 standard are transmit power control, which directly affects the energy cost of the communication, and alternation of awake and sleep states, as the battery consumption in sleep state is negligible. However, low transmission power and long sleeping time reduce the message success rate and the responsiveness of the network. This paper presents a fuzzy logic solution for dynamically adjusting both transmission power and sleeping time in an IEEE 802.11 wireless network. The proposed approach is validated through simulations, which show a battery life 20% longer than other state-of-the-art approaches, and by means of a real testbed, which confirms the simulated results.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11387/129819
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