# Escalator: An Autonomous Scheduling Scheme for Convergecast in TSCH
## 7 Conclusions  
In this paper, we propose a new autonomous scheduling scheme for the convergecast. Escalator provides a slotframe schedule for a network in which all nodes can send packets to the sink in every slotframe cycle, regardless of the network topology. Escalator minimizes the end-to-end delay from a source node to the sink by creating a schedule that considers multichannel and packet forwarding order. Escalator schedules using only the DODAG topology and node IDs and does not generate traffic overhead used for network information collection and scheduling negotiation between nodes. We prove the conflict-freeness of the schedule generated by Escalator using the wireless conflict model. Furthermore, we analyze the average end-to-end delay of packet transmission and the available bandwidth for each node in the network. We implement Escalator based on Contiki, which is widely used as the OS platform of IoT. The performance is evaluated by comparing with the existing autonomous scheduling schemes using a testbed and simulation. As a result, it is confirmed that Escalator maintains the delay of the packet \begin{table}
\begin{tabular}{l c c c c c c c c} \hline \hline  & \multicolumn{8}{c}{**Duty Cycle (\%)**} \\ \cline{2-10}  & \multicolumn{2}{c}{**4 \(\times\) 4 grid, 20 s**} & \multicolumn{2}{c}{**4 \(\times\) 4 grid, 5 s**} & \multicolumn{2}{c}{**6 \(\times\) 6 grid, 20 s**} & \multicolumn{2}{c}{**6 \(\times\) 6 grid, 5 s**} \\ \cline{2-10}  & **Average** & **Max** & **Average** & **Max** & **Average** & **Max** & **Average** & **Max** \\ \hline minimal & 2.40 & 2.47 & 2.44 & 2.77 & 2.41 & 2.61 & 2.48 & 2.96 \\ Orchestra 37 & 1.06 & 1.65 & 1.20 & 2.56 & 1.15 & 2.46 & 1.31 & 2.83 \\ Orchestra 53 & 0.89 & 1.34 & 1.02 & 1.96 & 0.96 & 1.68 & 1.08 & 2.10 \\ Escalator 73 & 0.92 & 2.67 & 1.12 & 3.65 & 1.20 & 3.05 & 1.54 & 5.31 \\ Escalator 107 & 0.78 & 1.64 & 0.98 & 2.39 & 0.99 & 4.01 & 1.32 & 6.85 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Measured average and max duty cycle in the simulations. Figure 13: Duty cycle per number of routing entries in a node: (**a**) a packet transmission interval of 20 s on the 4 \(\times\) 4 grid; (**b**) a packet transmission interval of 5 s on the 4 \(\times\) 4 grid; (**c**) a packet transmission interval of 20 s on the 6 \(\times\) 6 grid; (**d**) a packet transmission interval of 5 s on the 6 \(\times\) 6 grid. transmission at a constant level irrespective of the increase of the number of nodes and the increase of the traffic. In addition, Escalator shows lower end-to-end delay and a higher packet delivery ratio for the convergecast compared to existing autonomous scheduling schemes. Experimental results show that Escalator does not significantly increase the average duty cycle, even for better performance in the PDR and the end-to-end delay compared to the existing autonomous scheduling schemes. In addition, we can see that the duty cycle increase for the number of routing entries of the node is higher in Escalator than in the other scheduling schemes. This phenomenon means that the energy consumption of the nodes around the sink is increased, and as a result, the network lifetime can be reduced. We will study the routing considering the balance of the remaining energy and routing topology for the increase of the network lifetime [33; 34; 35]. In addition, Escalator provides a conflict-free schedule for convergecast traffic only. We consider not only the monitoring, but also the reliability improvement through the conflict-free schedule for the control plane. To this end, we will continue to work on the creation of schedules for downward traffic that can be used with Escalator. This work was supported by the Technology development Program (C0511664) funded by the Ministry of SMEs and Startups (MSS, Korea). [PERSON], [PERSON] and [PERSON] contributed to the main idea of this paper; [PERSON] and [PERSON] conceived and designed the experiments; [PERSON] and [PERSON] performed the experiments; [PERSON] analyzed the data; [PERSON] and [PERSON] wrote the paper.