# Energy Efficiency in Short and Wide-Area IoT Technologies--A Survey
## 5 Open Challenges
### Open Challenges for LPSANs  
In the context of LPSANs, the literature related to energy efficiency mechanisms for RFID is split between solutions for readers and solutions for active or passive tags.  
For the readers, clustering-based methods often assume mobile devices, thus neglecting stationary situations. Moreover, these schemes require the readers to have high initial energy levels and similar mobility patterns, which could be limiting assumptions compared to real scenarios. Clustering-based solutions may also lead to latency increases, since readers could wait a large amount of time before exchanging data with the CH (e.g., see GDRA algorithm [103; 104]).  
For active tags, most of the methods are based on the Free2 move protocol [106], where the tags wait for ACKs from the readers to enter the sleep mode. Hence, the main drawbacks in energy efficiency happen when the ACK is received with large delays or even not received by the tags. In parallel, the improvements obtained by polling-based techniques, such as GMLE protocol [107], are dependent on how the polling is executed and regulated, particularly in terms of the interrogation range of the readers, [107], thus requiring further analyses for optimizing this procedure.  
Finally, most of methods for passive tags are based on the use of Query Trees [113], as mentioned in Section 4. Here, the energy consumption is dependent on several factors, including the number of identification queries and tree levels.  
Moving on Zigbee, the proposed solutions mostly rely on routing protocols, for example, AODVjr [117]. Since the AODVjr process of establishing the route is highly energy consuming, other protocols in order to build the cluster-tree formation. This causes higher energy consumption for such nodes, making them prone to failure and causing unwanted network partitions. This is an important issue to study, in order to achieve a better balance in creating a cluster-tree network while enhancing the energy efficiency, so that an increase in the number of clusters does not relate to an increase in energy consumption.  
As regards Bluetooth, the literature shows how important is to create energy-aware scatterers. All the solutions focusing on this aspect adopt the cluster tree approach, where a CH can be replaced by another master/slave node when its energy level falls below a predefined threshold. However, substituting a CH requires further exchange of control messages and, in turn, energy consumption increases. The multi-hop scatternets proposed in [126] aim at dealing with such an issue; however, the consumption decrease comes with latency increase, which is often the most challenging trade-off to handle in Bluetooth networks.  
Polling schemes are also proposed for Bluetooth networks. They are mostly evaluated under the assumption that the slaves in the scatternet go from sleep to wake-up mode thanks to a a dedicated polling. However, data packets have no fixed time of arrival in real scenarios, making it difficult to predict when they arrive so that the slave device can wake-up. The master node needs to be able to detect when the traffic load fluctuate. the master transmits the polls at different data rates, so that it can be able to detect traffic fluctuation. In the methods based on the scatternet, the energy consumption is dependent on data rate. If the data rate increases, so does the energy consumption, making the energy consumption dependent on the transmission data rate, and calling for further proposal for better handling this limiting trade-off.