Collecting and Analyzing Failure Data of Bluetooth Personal Area Networks

This work presents a failure data analysis campaign on Bluetooth Personal Area Networks (PANs) conducted on two kind of heterogeneous testbeds (working for more than one year). The obtained results reveal how failures distribution are characterized and suggest how to improve the dependability of Bluetooth PANs. Specically, we dene the failure model and we then identify the most effective recovery actions and masking strategies that can be adopted for each failure. We then integrate the discovered recovery actions and masking strategies in our testbeds, improving the availability and the reliability of 3.64% (up to 36.6%) and 202% (referred to the Mean Time To Failure), respectively.