Caching-Aided Collaborative D2D Operation for Predictive Data Dissemination in Industrial IoT

Industrial automation deployments constitute challenging environments where moving IoT machines may produce high-definition video and other heavy sensor data during surveying and inspection operations. Transporting massive contents to the edge network infrastructure and then eventually to the remote human operator requires reliable and high-rate radio links supported by intelligent data caching and delivery mechanisms. In this work, we address the challenges of contents dissemination in characteristic factory automation scenarios by proposing to engage moving industrial machines as device-to-device (D2D) caching helpers. With the goal to improve reliability of high-rate millimeter-wave (mmWave) data connections, we introduce the alternative contents dissemination modes and then construct a novel mobility-aware methodology that helps develop predictive mode selection strategies based on the anticipated radio link conditions. We also conduct a thorough system-level evaluation of representative data dissemination strategies to confirm the benefits of predictive solutions that employ D2D-enabled collaborative caching at the wireless edge to lower contents delivery latency and improve data acquisition reliability

Energy Efficient IoT Data Collection in Smart Cities Exploiting D2D Communications

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

Valutazione di tecniche di allocazione di risorse in reti cellulari di quarta generazione

Il problema della gestione dello spettro radio, è stato ampiamente affrontato in letteratura, anche con buoni risultati. Quello che propone questo elaborato, è integrare uno schema di controllo di potenza, con quello che viene definito come Spectrum Sharing, dove due operatori mettono in condivisone una porzione della loro banda che può venire usata da tutti gli utenti attraverso delle politiche di gestione delle contese. E’ definito, quindi, un algoritmo di controllo di potenza, compatibile con lo standard LTE, che ci permetterà di dimostrare come in alcuni casi, considerando dei parametri come l’SINR, la potenza di ogni sotto-canale e la porzione di banda condivisa, unitamente all’algoritmo da noi proposto, la capacità dell’intero sistema aumenti, senza compromettere in modo evidente la qualità delle trasmission

Multi-scale mobility models in the forthcoming 5G era : a general overview

The forthcoming fifth generation (5G) mobile wireless system is likely to lead to an increasingly heterogeneous data demand pattern, including a small number of high data-rate mobile broadband links and a large number of low data-rate Internet-of-Things (IoT) applications. Aspects which govern seamless mobility between different access-technologies, cell tiers, cell sectors, and frequency bands will be sensitive to the mobility model of the people, their devices, and the machines. An understanding about how such entities will play a fundamental role in the future standardization and exploiting of the 5G technologies. In this article, we provide a comprehensive and general overview about existing mobility models useful to characterizing movements patterns across multiple distance and populations scales. In doing so, all the models are critically discussed, providing strengths and weaknesses. Finally, open issues and critical design choices are highlighted to serve as guidelines for future research in this topic

Validating information security framework for offloading from LTE onto D2D links

D2D communications is one of the key technologies to enable aggressive spatial frequency reuse in future evolution of cellular systems. While the standardization efforts are far from their final stage there is clear understanding that security is one of the major concerns for proximity services. This is especially the case when one or more communicating stations in a logical cluster do not have an active connection to the serving base station. In this paper we propose a solution for secure throughput optimized communications in D2D-assisted cellular system. In order to provide additional throughput, a game-theoretic optimization approach is considered by taking into account social relationships and devices proximity. The proposed solution is agnostic to the chosen D2D communications technology (i.e., WiFi or LTE) and suitable for any possible cluster combination in full and partial cellular coverage. Performance evaluation of the proposed security framework show that social proximity information available at the D2D devices may substantially improves the system performance in term of throughput with respect to the standard security procedures. Finally, for sake of completeness, the effect of mobility for the reference scenario is evaluated

NB-IoT for D2D-enhanced content uploading with social trustworthiness in 5G systems

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.publishedVersionPeer reviewe

Effective RAT Selection Approach for 5G Dense Wireless Networks

Dense Networks (DenseNet) and Multi-Radio Access Technologies (Multi-RATs) are considered as key features of the emerging fifth generation (5G) wireless systems. A Multi-RAT DenseNet is characterized by a very dense deployment of low-power base stations (BSs) and by a multi-tier architecture consisting of heterogeneous radio access technologies. Such a network aims to guarantee high data-rates, low latency and low energy consumption. Although the usage of a Multi RAT DenseNet solves problems such as coverage holes and low performance at the cell edge, frequent and unnecessary RAT handovers may occur with a consequent high signaling load. In this work, we propose an effective RAT selection algorithm that efficiently manages the RAT handover procedure by \emph{(i)} choosing the most suitable RAT that guarantees high system and user performance, and \emph{(ii)} reducing unnecessary handover events. In particular, the decision to trigger a handover is based on a new system parameter named Reference Base Station Efficiency (RBSE). This parameter takes into account metrics related to both the system and the user: the BS transmitted power, the BS traffic load and the users' spectral efficiency. We compare, by simulation, the proposed scheme with the standardized 3GPP policies. Results show that the proposed RAT selection scheme significantly reduces the number of handovers and the end-to-end delay while maintaining high system throughput and user spectral efficiency.Comment: We just realized that the submitted version is not compliant with the final version of the manuscript. In addition, there are also crucial error in the formulation of the analytical result