Evaluation of asynchronous average consensus algorithms in pure broadcasting infrastructure-free networksRevista : 2017 IEEE Conference on Control Technology and Applications (CCTA)
Páginas : 61-66
Tipo de publicación : Conferencia No DCC Ir a publicación
Distributed and cooperative algorithms are of preponderant importance for the correct operation of multiagent systems. In particular, average consensus algorithms represent an appealing alternative for combining measurements in large-scale networks of low-capable sensors, due to their low computational cost and strong convergence properties. However, the actual performance of average consensus algorithms in real scenarios, where the interaction between agents involves a communication network introducing stochastic delays, sequential transmissions and receptions, and unreliability in the information exchanging process, is yet to be investigated. This work presents an evaluation on a pure broadcasting infrastructure-free sensor network of two popular average consensus strategies: the broadcast gossip algorithm (which can be regarded as an asynchronous version of the discrete-time average consensus algorithm), and the push-sum algorithm (also known as double linear iterations). To understand the operating principles behind the algorithms, a hybrid model is first introduced that is used to conduct numerical simulations. An implementation in microprocessor-based development boards is then presented to evaluate the performance in a real environment. Results of the evaluation show that the push-sum algorithm outperforms the broadcast gossip algorithm for practical values of the reception probability.