An Energy-Efficient Clustering Protocol Based On Artificial Bee Colony

In today’s world, with the rapid development of mobile computing and mobile Internet technology, network communication has been applied to applications of mobile devices more frequently, such as mobile learning and mobile ad-hoc sensor network. These mobile applications greatly facilitate people’s life greatly, and improve the students’ interest in learning.However, for the battery-powered devices such as smart phones, tablet PC and sensors in the wireless sensor network, energy consumption is an import factor which directly affects the mobile devices’quality of communication and the network lifetime. Especially in these years, with the improvement of mobile devices’screen size, CPU’s processing speed, capacity of storage and communication year by year, the battery life which grows very slowly has become the bottleneck for energy intensive network application scenarios. This will also reduce the user experience to some extent.For the network applications composed of battery-powered mobile devices, we came up with a bio-inspired energy efficient clustering protocol which mainly includes three parts: firstly, we estimate the number of CH adaptively according to the nodes distribution and speed; secondly, select the cluster heads by using ABC algorithm while considering several factors mostly affecting the energy consumption and learning quality in real mobile terminal applications such as nodes’residual energy, mobility, communication radius and the distance to the server; thirdly, in case that the structure of clusters may unstable due to the CHs’ mobility or some CHs consume their energy excessively, our protocol also includes two cluster maintenance methods, utmost to maintain the stability of the cluster structure.We also carried out some simulation experiments under different application scenes and different parameters. Simulation results demonstrate that our protocol can substantially save the energy of mobile terminals and efficiently prolong the network lifetime by balancing the energy consumption of all devices, then improves the performance under energy-intense applications and the users’experience.