Layer scheduling in a multiple-layer self-organizing wireless network

We consider the layer scheduling problem associated with a multiple-layer self-organizing low-power wireless network. Each layer has a root node, which maintains a rooted spanning tree through which data messages are routed to the root. Each root node is capable of broadcasting a message to its destination node directly. We exploit layer scheduling algorithms that adapt to network load fluctuations in order to optimize the performance. For optimality we consider a load balancing objective and a minimum delay objective respectively, the former attempts to optimize the overall network performance while the latter strives to optimize the per-message performance. Four algorithms are presented with the associated load information exchange protocols and simulations were used to evaluate and compare their performance. We show that the presented algorithms have superior performance in terms of data throughput and/or message delay, compared to a heuristic approach that does not account for network load fluctuations. Policies with a load balancing objective do Indeed yield a superior overall network performance over the policy based on a minimum delay objective.