Giovanni Rigazzi

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—Machine-to-Machine (M2M) communications is one of the key enablers of the Internet of Things (IoT). Billions of devices are expected to be deployed in the next future for novel M2M applications demanding ubiquitous access and global connectivity. In order to cope with the massive number of machines, there is a need for new techniques to coordinate the(More)
Machine-to-Machine (M2M) communications are gaining momentum due to the rapid deployment of smart devices with self-organizing capabilities, able to interact each other without the human operator support. Ultimately, M2M paradigm allows Machine-Type Communication Devices (MTCD) to exchange data in Peer-to-Peer (P2P) mode, avoiding the need of a core network(More)
—This paper presents a novel energy-aware communication scheme based on random network coding that is suitable for multicast and broadcast data delivery over Long Term Evolution (LTE) and LTE-Advanced networks. The proposed energy-aware transmission scheme minimises the average energy consumption of the macro base station that is required to deliver a(More)
Recently, the self organization approach has been incorporated into the 3rd Generation Partnership Project (3GPP) standards in order to implement mechanisms such as auto configuration, auto healing, and self optimization of the deployed network architecture. However, the Self Organization Networks (SONs) functionalities in Long Term Evolution (LTE) do not(More)
This paper investigates traffic related performance for TCP/UDP-based traffic flows in a MANET powered by OLSR with various routing metrics. Besides the ETX (expected transmission count), an alternative is proposed that resorts on a cross-layer approach to obtain PER (packet error rate) estimates from the physical layer. Throughput and latency performance(More)
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