A context-aware cross-layer energy-efficient adaptive routing algorithm for WLAN communications

Smart phones have gained great popularity all around the world, supporting rich media applications with Internet connectivity. Since increasing number of people own powerful mobile devices, ad-hoc WLANs can be deployed in public areas part of heterogeneous networks environments, as flexible and inexpensive alternatives to infrastructure-based approaches. However, these mobile devices are powered by battery with limited energy budgets, which introduces big energy-related challenges in ad-hoc WLAN routing algorithm design. This paper proposes a context-aware cross-layer energy-efficient adaptive routing algorithm for WLAN communications (AWERA) that performs energy-efficient context differentiated routing in wireless communications. It introduces a cross layer self-learning solution that monitors the context of device usage, and takes routing decisions based on current energy-oriented context. Compared with other state-of-the-art wireless routing protocols, simulation results show both better performance and energy efficiency context-based differentiation.