BeeCup: A bio-inspired energy-efficient clustering protocol for mobile learning

• We explore clustering to improve energy efficiency of mobile learning network systems.
• A bio-inspired dynamic clustering protocol called BeeCup is proposed.
• We find a suitable fitness function of artificial bee colony for mobile learning.
• We propose two intelligent clustering maintenance methods to achieve load balance.
• Extensive simulations have been conducted to evaluate the performance of BeeCup.

Mobile devices have become a popular tool for ubiquitous learning in recent years. Multiple mobile users can be connected via ad hoc networks for the purpose of learning. In this context, due to limited battery capacity, energy efficiency of mobile devices becomes a very important factor that remarkably affects the user experience of mobile learning. Based on the artificial bee colony (ABC) algorithm, we propose a new clustering protocol, namely BeeCup, to save the energy of mobile devices while guaranteeing the quality of learning. The BeeCup protocol takes advantage of biologically-inspired computation, with focus on improving the energy efficiency of mobile devices. It first estimates the number of cluster heads (CHs) adaptively according to the network scale, and then selects the CHs by employing the ABC algorithm. In case some CHs consume energy excessively, clusters will be dynamically updated to keep energy consumption balanced within the whole network. Simulation results demonstrate the effectiveness and superiority of the proposed protocol.