General and mixed linear regressions to estimate inter-contact times and contact duration in opportunistic networks

Abstract

Abstract In the context of Opportunistic Networking (OppNet), routing and delivery algorithms used for content dissemination employ different metrics to perform accurate decisions. It has been shown that of these metrics, the inter-contact time and the contact duration are very useful for characterising OppNet scenarios. In this article, we show that the exponential moving averages of the historical values of these metrics are correlated with future observed values, in addition to also being good estimators for them. Moreover, we go a step further to investigate how to locally, from the OppNet node perspective, improve the estimations for these metrics by defining two novel estimation functions. These estimation functions are based on two different linear models: a general regression model and a mixed regression model, where future values of the studied metrics are explained in terms of their corresponding exponential moving averages. Experimentation using real mobility traces from well-known OppNet scenarios show that our estimation functions greatly reduce the estimation error of the future values of both metrics when compared to representative state of the art proposals.