Exploiting traffic sampling techniques to optimize energy efficiency in mobile peer networks

Abstract

Wireless infrastructures have seen a drastic increase in energy requirements as technology shifted towards higher frequencies in an attempt to increase bandwidth. Driven by the increase in demand from an always increasing subscriber base, large cities are also demanding more base stations and access points to guarantee adequate quality of service. Mobile peer networking is a possible solution for power-efficient communication, since transmission over short distances demands less power. A novel algorithm based on peer nodal hierarchies, traffic mapping and neural networks is proposed. Results show that this technique presents a remarkable power efficiency improvement over standard peer-to-peer networks.