# Accurate Energy Consumption Modeling of IEEE 802.15.4e TSCH Using Dual-Band OpenMote Hardware
## 6 Conclusions  
In this paper, we propose a more accurate energy model for IEEE 802.15.4e TSCH using dual-band OpenMote hardware. The model differs from previous work in several ways. First, it includes an elaborate and up-to-date set of time slots and states and accurately models variable packet sizes. Second, we present state durations and energy consumption measurements for both the 868 MHz and 2.4 GHz frequency bands, using the CC1200 and CC2538 radio, respectively. We have experimentally verified the accuracy of the proposed model by comparing measured values of all time slots to their modeled counterpart. Furthermore, the energy consumption of a small-scale TSCH network was compared with its modeled consumption. For both the time slot comparison and the small-scale network experiment, the average error was less than 3%, including measurement inaccuracies and variations of the guard time. Using the measured energy slot consumption for both 868 MHz and 2.4 GHz communication, we also conducted several TSCH network simulations to observe the energy  
Figure 12: Comparison of the lifetime of a TSCH node, running on two AA batteries, between 2.4 GHz and 868 MHz communication for different packet periods in a grid topology of 25 nodes. (**a**) 1 packet/s, 2.4 GHz; (**b**) 1 packet/s, 868 GHz; (**c**) 1 packet/min, 2.4 GHz; (**d**) 1 packet/min, 868 GHz; (**e**) 1 packet/h, 2.4 GHz; (**f**) 1 packet/h, 868 GHz.  
consumption effects for both frequency bands in an end-to-end context. We have also shown that the proposed model can accurately model all packet sizes, a feature absent in current TSCH energy consumption models, which only consider the maximum packet size. These results prove that our model is suitable to accurately predict the energy consumption of TSCH networks.  
Part of this research was funded by the Flemish FWO SBO S004017N IDEAL-IoT (Intelligent DEnse and Longe range IoT networks) project and by the Interdisciplinair Cooperatief Onderzoek (ICON) projects Multimodal Sub-Gigahertz Communication and Localisation for Low-Power IoT applications (MuSCLe-IoT) and Continuous Athlete Monitoring (CONAMO). MuSCLe-IoT is a project realized in collaboration with imec, with project support from Agentschap Innoveren en Ondermemen (VLAIO). Project partners are imec, Flash Private Mobile Networks, Engie M2M, Sensolus and Aertssen. CONAMO is a project realized in collaboration with imec, with project support from VLAIO. Project partners are imec, Rombit, Energy Lab and Vlaamse Radio- en Televisiecnroeporganisatie (VRT).  
The work was realized with the collaboration of all of the authors. [PERSON], [PERSON] and [PERSON] conceived of, designed and performed the experiments. [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] analyzed the data. [PERSON] completed the CC1200 driver integration. [PERSON] and [PERSON] contributed analysis tools and assistance. [PERSON] and [PERSON] wrote the paper. [PERSON] and [PERSON] revised the paper and defined and supervised the research. All authors have contributed to the production of the paper and the reviewing of the intellectual content of this article and have approved the manuscript.  
The authors declare no conflicts of interest.