论文标题
Beecup：用于移动学习的生物启发的节能聚类协议
BeeCup: A Bio-Inspired Energy-Efficient Clustering Protocol for Mobile Learning
论文作者
论文摘要
近年来，移动设备已成为无处不在学习的流行工具。可以通过临时网络连接多个移动用户，以进行学习。在这种情况下，由于电池容量有限，移动设备的能源效率成为一个非常重要的因素，它极大地影响了移动学习的用户体验。根据人工蜜蜂殖民地（ABC）算法，我们提出了一种新的聚类协议，即Beecup，以节省移动设备的能量，同时保证学习质量。 BeeCup协议利用了以生物学启发的计算，重点是提高移动设备的能源效率。它首先根据网络量表自适应地估算簇头（CHS）的数量，然后通过使用ABC算法选择CHS。如果某些CHS过度消耗能量，将动态更新集群以保持能耗在整个网络中保持平衡。仿真结果证明了所提出的方案的有效性和优势。
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.
