Multi-criteria optimization of wireless connectivity over sparse networks

In this article, we propose a machine learning algorithm that aims to increase the number of contacts between mobile nodes by using a smarter WiFi access point selection heuristic. The algorithm is based on properly balancing signal strength, latency, bandwidth, and, most importantly, the number of friends predicted to connect to the respective access point. We show through simulations based on real-life tracing data-sets that our proposed solution not only increases the likelihood of opportunistic contacts, but it also evenly distributes social subgraphs of users over wireless networks while improving the overall hit rate.