BeeCup: A Bio-Inspired Energy-Efficient Clustering Protocol for Mobile Learning

TL;DR

BeeCup is a novel bio-inspired clustering protocol based on the artificial bee colony algorithm designed to enhance energy efficiency in mobile learning ad hoc networks, dynamically balancing energy consumption among devices.

Contribution

It introduces a new energy-efficient clustering protocol for mobile learning networks using ABC algorithm, with adaptive cluster head selection and dynamic cluster updates.

Findings

Demonstrates improved energy efficiency over existing protocols

Achieves balanced energy consumption among mobile devices

Shows superior performance in simulation tests

Abstract

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.