# EEMIP: Energy-Efficient Communication Using Timing Channels and Prioritization in ZigBee
## 1 Introduction
In [13], the authors focused on the ODMAC protocol, which serves to reduce the energy consumption of devices at the data link layer. The reduction of energy was achieved by so-called duty cycles, which are specific for each device. The ODMAC was designed on the basis of three key objectives: sustainability, efficiency and application performance. Devices using ODMAC adapt their duty cycles based on ENO (Energy Neutral Operation); the node is sustainable, if for a certain period of time, the energy consumed is less than or equal to the energy harvested. All nodes in the network dynamically set the beacon frame and modify duty cycles to obtain maximum performance status. This means that when the energy used is higher than the energy obtained, the duty cycles are reduced to reduce energy consumption. The authors of [14] proposed dividing BLE (Bluetooth Low Energy) communication into time channels. Information is divided into time intervals. Improving energy efficiency is achieved by adding additional information at the time of inactivity between sending BLE packet advertisements. Added bits are encoded without increasing work cycles, thus reducing BLE transmitter power consumption. It has been proven that usage of time channels, in which information is sent at intervals, will reduce energy consumption and increase energy efficiency by more than 10%. There is a number of other approaches developed to utilize duty cycles in the communication to minimize energy consumption [15], which use various ways to synchronize devices and to enable them to be put into a power-saving state for some time period. The last class of energy efficient techniques is based on a topology control. The key idea is to create and maintain a reduced topology while preserving the original connectivity and coverage. In this class, there are also techniques that use a distributed environment of WSNs to reduce overall energy. An approach, proposed by [16], utilizes proactive planning in sharing Internet connection among multiple IoT devices. IoT already enables to discover devices and create a communication connection among them autonomously. It is beneficial not only for sharing information, but also for sharing Internet access, which can save energy. This way, the proposed framework proactively plans Internet services in a cooperating IoT environment. In [17], the authors focused on an energy-saving solution using ZigBee devices in IoT. The idea was based on the fact that the IoT domain has more and more devices that are capable of computational operations. Devices could use the processing capabilities and calculations of other devices to achieve the desired goal. One of the main aspects was to mediate network collaboration. ZigBee devices usually communicate on a local network and are not connected to the Internet. As a solution of this problem, the Internet-of-Things Group Distributed Computing Platform (IGDCP) was proposed. IGDCP includes IoT devices and devices connected to the local network. In general, IoT connects heterogeneous devices, communication technologies, sensors and transferred data. To increase efficiency, shared gateways provide Internet connections for such heterogeneous technologies and data. However, some data are critical and others are not; therefore, a system should provide some mechanism to minimize latency or increase reliability of delivery of critical data. It means that there is an increasing importance to incorporate so-called quality of service (QoS) and implied prioritization into IoT sphere [18; 19; 20]. Another way of dealing with heterogeneity in IoT is to use some 5G network technologies [21; 22], such as NOMA (NonOrthogonal Multiple Access) [23]. NOMA increases spectral efficiency by enabling simultaneous communication of nodes and using power differences and successive interference cancellation to demultiplex the signals. It enables us to use different bandwidth/power for different communication nodes. It is more efficient for networks with a large number of devices with a high variety of communication requirements.