Some industrial applications require deterministic and bounded gathering delays. We focus on the joint time slots and channel assignment that minimizes the time of data collection and provides conflict-free schedules. This assignment allows nodes to sleep in any slot where they are not involved in transmissions. Hence, these schedules save the energy budjet of sensors. We calculate the minimum number of time slots needed to complete raw data convergecast for a sink equipped with multiple radio interfaces and heterogeneous nodes traffic. We also give optimal schedules that achieve the optimal bounds. We then propose MODESA, a centralized joint slots and channels assignment algorithm. We prove the optimality of MODESA in specific topologies. Through simulations, we show that MODESA is better than TMCP, a centralized subtree based scheduling algorithm. We improve MODESA with different strategies for channels allocation. In addition, we show that the use of a multi-path routing reduces the time of data collection .Nevertheless, the joint time slot and channels assignment must be able to adapt to changing traffic demands of the nodes (alarms, additional requests for temporary traffic) . We propose AMSA , an adaptive joint time slots and channel assignment based on incremental technical solution. To address the issue of scalability, we propose, WAVE, a distributed scheduling algorithm for convergecat that operates in centralized or distributed mode. We show the equivalence of schedules provided by the two modes.
Wireless sensor networks in industrial environment : energy efficiency, delay and scalability