# EEMIP: Energy-Efficient Communication Using Timing Channels and Prioritization in ZigBee
## 5 Conclusions  
In this article, we have presented a new method (called EEMIP) of energy-efficient communication using time intervals and data priority in ZigBee communication for a star network topology. It is most useful for sensor devices, which send collected data periodically. The main contribution is making the  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Advantages** & **Disadvantages** \\ \hline increased energy efficiency & increased control overhead \\ eliminated processing of periodic beacon frames & limited to star topology \\ reduced end-device waiting time & single point of failure (coordinator) \\ reduced number of collisions & benefits limited to frequent periodic communications \\ reduced number of retransmissions & \\ increased quality of service & \\ \hline \hline \end{tabular}
\end{table}
Table 13: Advantages and disadvantages of the EEMIP method.  
communication more energy-efficient while still being effective. The central device in the topology (i.e., coordinator) is aware of all end sensory devices in the network, to which it assigns a time slot for communication and a priority-based time interval. It enables the end devices to communicate in various intervals according to their requirements and eliminates the need to wait for synchronization frames, which wastes the energy. It also handles the congestion, in which it prioritizes the critical data and, thus, ensures reliable delivery. For evaluation of the proposed method, we have implemented a simulator, which was used to compare the standard nonbeacon ZigBee mode and the EEMIP mode. The experimental results confirmed that the EEMIP mode is more energy efficient for most of the cases, in which collisions occur and sensor devices collect various amounts of data with different priorities (often the case of ZigBee networks). For networks without data loss (i.e., less frequent, small amount of devices, environment without interferences, etc.), the proposed EEMIP method is unsuitable due to the increased overhead. Further work can be targeted to the implementation of the EEMIP method in hardware, and evaluating the method using real data.  
Conceptualization, P.G. and D.M.; methodology, D.M.; software, P.G.; validation, D.M.; formal analysis, D.M.; investigation, P.G.; resources, P.G.; data curation, P.G.; writing--original draft preparation, P.G. and D.M.; writing--review and editing, D.M.; visualization, D.M.; supervision, D.M.; funding acquisition, D.M.  
This research was partially funded by by the Slovak Research and Development Agency (APVV-15-0789), the Slovak Cultural and Educational Grant Agency (KEGA 011 STU-4/ 2017), the Slovak Scientific Grant Agency (VEGA 1/0836/16), the project \"University Science Park of STU Bratislava\" (ITMS 26240220084), co-funded by the European Regional Development Fund, and the projects no. 2018/14427:1-26C0 and 002 STU-2-1/2018.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} IoT & Internet of Things \\ WSN & wireless sensor networks \\ BLE & Bluetooth Low Energy \\ QoS & quality of service \\ NOMA & NonOrthogonal Multiple Access \\ TDMA & Time Division Multiple Access \\ EEMIP & Energy-Efficient Method using Intervals and Prioritization \\ WPAN & wireless personal area network \\ \end{tabular}