# Energy Efficiency in Short and Wide-Area IoT Technologies--A Survey
## 4 Classification of Energy Efficiency Methods
### Mechanisms for RFID Active Tags
#### 4.1.2 Zigbee
The table also includes other information on the neighbors, such as:  
* _Depth (D)_, that is, the number of hops the neighbor node needs for achieving the destination;
* _Device Type (DT)_, it gives information if the node has routing capability or not;
* _Link Quality Indicator (LQI)_, it reports the quality of the received signal on the link with the neighbor;
* _Node Cost (NC)_, it counts the number of packets that are sent or received by a neighbor node;
* _Tree Index (TI)_, it represents the path that data travel from the coordinator to the node under consideration. ESTR uses TI to calculate, for each neighbor, the number of hops that a data packet would take to arrive at destination. Then, it uses NC to estimate the congestion level of its neighbors, and LQI to find the most reliable links. This way, ESTR balances network traffic, distributing the workload on the intermediate and less-congested nodes. Simulation results show that ESTR performs better compared to EAMTR and the Improved Routing Protocol, in terms of energy efficiency and network lifetime, since it balances the consumption across the nodes in the network. Another algorithm taking roots from AODV was presented in [121], where the energy of the nodes is classified as _enough, low, and critical_ levels. Nodes with enough energy choose the routing algorithm they will use, while nodes with low energy choose the same mechanism used in AODV to send flood packets (a large number of packets at the same time), while critical nodes only respond to the nodes that have its address as destination. A Zigbee network generally adopts a cluster-tree hierarchy for organizing the nodes [121]. In a cluster-tree hierarchy, the nodes are grouped in a hierarchy of clusters, with the clusters represented in a tree structure. The network is composed of a coordinator node and children nodes. The nodes are also divided into three categories: RN+, RN\(-\), and RFD. RN\(+\) and RN\(-\) nodes belong to fully functioning nodes, while the RFD nodes act as leaf nodes, which forward information to the parent nodes. RN\(-\) nodes are able to use only the static cluster-tree algorithm, using an already established route, while the RN+ nodes use AODVjr to search for the best possible route. Hence, RN+ nodes consume more energy, since they are responsible for collecting information, route discovery and data forwarding. A disadvantage for such nodes is that they are prone to failure more easily that the other nodes. When a RN+ node turns into a failure node, the network partitions, because RN+ nodes are in charge of routing the traffic to the destination node. The algorithm in [121] focuses on reducing the load of the RN+ nodes. Simulations show significant improvements in terms of node and network lifetime and power consumption, while also reducing the percentage of node that fail to work properly. Several other works proposed clustering schemes for Zigbee networks. A new algorithm, called CLZBR was proposed in [122], and was outperformed later in terms of efficiency by another routing algorithm, called NCLZHR [123]. The nodes in the Zigbee network that employs NCLZHR, are grouped into clusters, with nodes being grouped in three types, that is, CH, gateway node (GW, a node selected to serve as a router), and cluster member. NCLZHR adds a node cluster label, making it possible for the node to know whether the destination node is in the same cluster or not, in order to optimize the data forwarding. NCLZHR also reduces redundant RREQ packets, since CHs and GWs are the only nodes in the network that can broadcast RREQ. The cluster members can only transmit data based on the tree routing algorithm, which is based on the neighbor tables. Simulations showed that CLZBR requires a large amount of broadcasting during the clustering process, whereas NCLZHR significantly reduces the number of broadcasting, and in turn the energy consumption of the network. Another algorithm based on the AODVjr is presented in [124].