Author:
Hosni Ines, ,Boubaker Ourida Ben,
Abstract
IEEE802.15.4e-TSCH is a mode exploited by the Internet of Things. Time Slotted Channel Hopping (TSCH) presents an upgrade to the IEEE 802.15.4 to build a Medium Access Control (MAC) for low power and loss network applications in IoT. This norm defines the concept of TSCH based on channel hopping and reservation of bandwidth to achieve energy efficiency, as well as consistent transmissions. Centralized approaches have been proposed for planning TSCH. They have succeeded in increasing network efficiency and reducing latency, but the scheduling length remains not reduced. However, distributed solutions appear to be more stable in the face of change, without creating a priori assumptions about the topology of the network or the amount of traffic to be transmitted. A distributed scheduling allowing neighboring nodes to decide on a coordination system operated by a minimal scheduling feature is currently proposed by the 6TiSCH working group. This scheduling allows sensor nodes to determine when data is to be sent or received. However, the details of scheduling time intervals are not specified by the TSCH-mode IEEE802.15.4e standard. In this work, we propose a distributed Optimized Minimum Scheduling Function (OMSF) that is based on the 802.15.4e standard TSCH mode. For this purpose, a distributed algorithm is being implemented to predict the scheduling requirements over the next slotframe, focused on the Poisson model and using a cluster tree topology. As a consequence, it will reduce the negotiation operations between the pairs of nodes in each cluster to decide on a schedule. This prediction allowed us to deduce the number of cells needed in the next slotframe. Clustering decreases, the overhead processing costs that produce the prediction model. So, an energy-efficient data collection model focused on clustering and prediction has been proposed. As a result, the energy consumption, traffic load, latency, and queue size in the network, have been reduced.
Publisher
International Journal of Advanced and Applied Sciences