# Energy Efficiency in Short and Wide-Area IoT Technologies--A Survey
## 4 Classification of Energy Efficiency Methods
### Mechanisms for RFID Active Tags
ESiM achieves optimal energy efficiency when all the tags are wanted tags, meaning specific tagsthat the reader was specifically searching for, and not random tags that are simply part of the interrogation range. Mechanisms for RFID Passive Tags  
**Resource Allocation techniques. ** When compared to their Active counterpart, Passive tags are cost-efficient but also more prone to collision. Several protocols have been thus proposed that attempt to avoid collisions, such as three versions of ALOHA, referred to as--Frame Slotted Aloha (FSA), Dynamic Frame Slotted ALOHA (DSFA), and Multiframe Maximum Likelihood DFSA (MFML-DFSA) [110; 111; 112; 114], as well as the so-called Query and Binary Tree schemes. * FSA is a protocol derived from Slotted ALOHA, where the timeslots are divided into frames, with the user (tag) able to only transmit a single packet per frame in a timeslot chosen randomly;
* DFSA is an anti-collision algorithm, which helps to avoid the collision of responses sent by different tags at the same time. This is done by dynamically changing the frame length, based on the feedback that comes from the last collision. In the case that the frame size, used for transmission, is small, this will lead to this frames contending for the same slots, it could cause a large number of collisions and waste the bandwidth assigned for transmission, while a large frame size on the other hand it could cause for a larger number of slots to remain idle and also waste the bandwidth. To avoid these situations, the reader should have the ability to dynamically adjust its frame size in accordance to the number of unidentified tags;
* MFML-DFSA is based on DFSA, and uses statistical information from different previous frames in order to implement a maximum likelihood estimator to compute the number of tags that are expected to compete with each other for transmission. In [113], a combination of Query Tree and DFSA algorithms, referred to as energy-efficient Query-DFSA (EEQDFSA) was proposed to improve energy efficiency. In Query tree, the reader transmits a query prefix to the tags, to be matched with their IDs. If there is one identification, where the query prefix matches the tags ID, it starts a new round of identification with a longer prefix compared to the first one. This process is called tag identification, and helps the reader to identify all the tags that are part of its query tree. EEQDFSA optimizes Query Tree, by minimizing the number identification queries, used to identify the tags, thus lowering the energy consumed by the identification queries process. Moreover, it classifies the timeslots in three categories, denoted as Successful, Empty, and Collision Slot. The latter ones are undesirable and contribute to lower the energy efficiency. EEQDFSA does not use the entire tag ID, but only a part of it called the _serial number_, which is unique; the algorithm proceeds to match serial numbers with the prefix transmitted by the reader. This process is more energy efficient, using less energy to transmit the serial number, compared to the energy spent when sending the entire tag ID. In Query tree the energy consumption is dependent on the number of tree levels, where each level consists of different readers and connected tags. The higher the level, the higher the energy consumption. With the increase of tree levels, it increases the complexity of the tree and therefore the higher the consumed energy. An important element in Query Trees is the maximum number of prefixes that are transmitted by the reader in the case when there are \(N\) tags in total, with the Query Tree composed of \(b\) levels. The higher the number of prefixes transmitted, the higher the consumed energy. In [113], the energy efficiency is evaluated by introducing the energy cost \(E_{C}\), as follows:  
\[E_{C}=B_{t}\cdot D, \tag{16}\]  
where \(B_{t}\) is the total number of transmitted bits and \(D\) is the delay introduced by the tag identification process.