Network discovery is a fundamental task in different scenarios of IEEE 802.15.4-based wireless personal area networks. Scenario examples are body sensor networks requiring health- and wellness-related patient monitoring or situations requiring opportunistic message propagation. In this paper, we investigate optimized discovery of IEEE 802.15.4 static and mobile networks operating in multiple frequency bands and with different beacon intervals. We present a linear programming model that allows finding two optimized strategies, named OPT and SWOPT, to deal with the asynchronous and multichannel discovery problem. We also propose a simplified discovery solution, named SUBOPT, featuring a low-complexity algorithm requiring less memory usage. A cross validation between analytical, simulation, and experimental evaluation methods is performed. Finally, a more detailed simulation-based evaluation is presented, when considering varying sets of parameters (i.e., number of channels, network density, beacon intervals, etc.) and using static and mobile scenarios. The performance studies confirm improvements achieved by our solutions in terms of first, average, and last discovery time as well as discovery ratio, when compared to IEEE 802.15.4 standard approach and the SWEEP approach known from the literature.

We consider the problem of neighbor discovery in wireless networks with nodes operating in multiple frequency bands and with asymmetric beacon intervals. This is a challenging task when considering such heterogenous operation conditions and when performed without any external assistance. We present linear programming (LP) optimization and two strategies, named OPT and SWOPT, allowing nodes performing fast, asynchronous, and passive discovery. Our optimization is slotted based and determines a listening schedule describing when to listen, for how long, and on which channel. We compare our strategies with the passive discovery of the IEEE 802.15.4 standard. The results confirm that our optimization improves the performance in terms of first, average, and last discovery time.