Fifth Generation (5G) wireless systems are expected to connect an avalanche of “smart” objects disseminated from the largest “Smart City” to the smallest “Smart Home”. In this vision, Long Term Evolution-Advanced (LTE-A) is deemed to play a fundamental role in the Internet of Things (IoT) arena providing a large coherent infrastructure and a wide wireless connectivity to the devices. However, since LTE-A was originally designed to support high data rates and large data size, novel solutions are required to enable an efficient use of radio resources to convey small data packets typically exchanged by IoT applications in “smart” environments. On the other hand, the typically high energy consumption required by cellular communications is a serious obstacle to large scale IoT deployments under cellular connectivity as in the case of Smart City scenarios. Network-assisted Device-to-Device (D2D) communications are considered as a viable solution to reduce the energy consumption for the devices. The particular approach presented in this paper consists in appointing one of the IoT smart devices as a collector of all data from a cluster of objects using D2D links, thus acting as an aggregator toward the eNodeB. By smartly adapting the Modulation and Coding Scheme (MCS) on the communication links, we will show it is possible to maximize the radio resource utilization as a function of the total amount of data to be sent. A further benefit that we will highlight is the possibility to reduce the transmission power when a more robust MCS is adopted. A comprehensive performance evaluation in a wide set of scenarios will testify the achievable gains in terms of energy efficiency and resource utilization in the envisaged D2D-based IoT data collection.

Future fifth-generation (5G) cellular systems are set to give a strong boost to the large-scale deployment of Internet of things (IoT). In the view of a future converged 5G-IoT infrastructure, cellular IoT solutions such as narrowband IoT (NB-IoT) and device-to-device (D2D) communications are key technologies for supporting IoT scenarios and applications. However, some open issues still need careful investigation. An example is the risk of threats to privacy and security when IoT mobile services rely on D2D communications. To guarantee efficient and secure connections to IoT services involving exchange of sensitive data, reputation-based mechanisms to identify and avoid malicious devices are fast gaining ground. In order to tackle the presence of malicious nodes in the network, this paper introduces reliability and reputation notions to model the level of trust among devices engaged in an opportunistic hop-by-hop D2D-based content uploading scheme. To this end, social awareness of devices is considered as a means to enhance the identification of trustworthy nodes. A performance evaluation study shows that the negative effects due to malicious nodes can be drastically reduced by adopting the proposed solution. The performance metrics that proved to benefit from the proposed solution are data loss, energy consumption, and content uploading time.