A Grey Prediction for Optimization Technique in Mobile Computing

With the rapid advances in mobile computing technologies and mobile devices, it is an important issue to maximize the number of served tasks for quality of service (QoS) provisioning in a mobile computing environment. One of many potential approaches is based on radio resource management (RRM). However, RRM suffers a problem that the task arrival rate, the task duration and the communication overhead between mobile nodes are uncertain under a mobile environment. To alleviate the obstacle, this paper proposes a Gray-RRM method to predict the load status of mobile nodes. Our approach is on the application-level of mobile computing, and can directly support existing facility. The Grey-RRM scheme exhibits better adaptability, and outperforms other recent algorithms. The simulation results show that the proposed algorithm can yield lower task blocking rate, lower task dropping rate, less load information updated overhead, and shorter radio resource carrier acquisition delays.