Artificial immune algorithm applied to short-term prediction for mobile object location

Mobility prediction is one of the most essential issues that need to be explored for management in a location-based service. The purpose of this study is to present a novel approach for predicting the next location of a mobile object. Existing prediction methods are generally based on mass history information. However, they cannot work well on the prediction of an object which has the features of short moving time and an elusive moving tendency. Taking into account these characteristics, proposed is a short-term prediction algorithm based on the artificial immune system. Simulated experimental results show that the proposed algorithm obtains higher accuracy and scalability than the traditional method.