FailDetect: Gossip-Based Failure Estimator for Large-Scale Dynamic Networks

Ubiquitous and wirelessly connected devices are the present status quo in terms of networks around us. With the ever increase of scale, there comes also the problem of various communication failures. They are usually caused by hardware, software, or any other medium access contention. For the case of mobile networks, path uncertainty comes also into picture due to node mobility. All this leads to low quality of service and reduced user experience. The main contribution of the paper is the introduction of a novel distributed algorithm called FailDetect for the statistical estimation of the average packet loss in large-scale wireless distributed systems. It is based on a gossip mechanism, with the adding of periodic resets of the exchanged values. FailDetect is a fully-distributed scheme that does not presume time synchronization among the reset intervals for various nodes. A model and an evaluation by means of simulation and experiments show that FailDetect succeeds in evaluating the average packet loss of the network, while exhibiting low message-complexity.