# Energy Efficient IoT Data Collection in Smart Cities Exploiting D2D Communications
## 6 Conclusions  
A novel energy efficient data collection scheme for the IoT in a Smart City scenario has been proposed, based on network-assisted D2D communications under LTE-A networks. A device, optimally selected by the eNodeB, acts as an aggregator to upload the data from the all neighboring devices, which form a cluster. All the devices in the cluster send their data to the aggregator over low power D2D links. With this approach, it is possible to overcome the low efficiency of LTE-A to handle small data transmissions. The optimal MCS is selected both on the cell-mode transmissions between the aggregator and the eNodeB and on the D2D links within a cluster to attain the maximum energy efficiency by adjusting the Transport Block Size to the total amount of data to be transmitted. The performance evaluation presented in this paper, covering a wide range of study cases, has shown that the proposed D2D-EE solution outperforms the standard LTE-A data uploading and an optimal energy efficient LTE-A data uploading scheme where D2D communication is not considered, named LTE-EE. The performance has been evaluated both in terms of radio resource utilization and of energy efficiency. Specifically, the most important results obtained with the proposed solution are that it allows a Transport Block utilization of 62% with 100 bytes to send per device and 50 devices and it  
Figure 8: Performance with aggregator role shifting among the devices (50 devices and 10 Bytes data).  
Figure 7: Performance for varying number of devices and data size: Aggregator _vs_. cluster devices. (a) Transport Block utilization; (b) Energy efficiency; (c) Energy consumption.  
is up to about 6 times more energy efficient than the LTE-EE and 11 times more efficient than the LTE-A solution, when the data size is of 10 byte and with 500 IoT devices. Noteworthy, thanks to the energy efficient solution and the lower transmission power over the D2D links, energy savings w.r.t. the standard LTE-A data uploading are obtained both for the devices in the cluster transmitting over D2D and for the aggregator node.  
The study of the impact of the proposed solution on the end-to-end delay, as well as the study of the energy-delay trade-off introduced by this approach, remains part of our ongoing and future research work. In addition, we plan to investigate on the modeling of solutions with larger amounts of data to upload and scenarios where a multitude of IoT objects are disseminated in a Smart City (_i.e._, in different position and with different multimedia applications) thus having different QoS requirements, as those posed by remote control and alarm applications. In these cases, large data to be sent would require several TTIs to be transferred to the eNodeB and the radio resource utilization should be optimized over several consecutive TTIs data frames. Another aspect for future analysis is the impact of mobility patterns for the IoT devices on the system-level performance for the signaling overhead in executing the proposed approach, for the radio resource allocation, the transmission mode selection and the power consumption.  
The research was not funded by any industry or academia entity. The authors gratefully acknowledge and thank the reviewers for the provided suggestions, which helped to improve the overall quality of the paper.  
In this paper, the first three authors [PERSON], [PERSON] and [PERSON] conceived the idea, organized the work and with support of [PERSON] they designed the analytical model and the proposed algorithms; [PERSON] and [PERSON] conceived and designed the experiments, analyzed the results and wrote the paper; [PERSON] performed the experiments; [PERSON] and [PERSON] supervised the work; all the authors reviewed the writing of the paper, its structure and its intellectual content.  
The authors declare no conflict of interest.