A bio-inspired approach for network selection in dense heterogeneous networks

The emerging dense heterogeneous networks comprising different types of small cells enable consumers to employ multiple radio access technologies to communicate. In such a dymica network environment, development of robust and self-adaptive network selection mechanisms is required to satisfy the growing demand on ubiquitous network access. Besides, the energy consumed at wireless interface accounts for the great proportion of the total energy consumption of user devices and the battery lifetime has become a important factor affecting quality of experience (QoE). Hence in this paper, we propose an adaptive network selection approach where each user autonomously choose desired wireless network interface that offers the best energy-quality tradeoff. For this purpose, we adopt an attractor selection model, which is developed from autonomous and adaptive behavior of biological systems. The high adaptability to fluctuating network environment and the simple control rules allow users to dynamically select the best network that provide satisfactory QoE while achieve a acceptable device battery lifetime.