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- Context-based caching in mobile information-centric networksPublication . Leira, Luís; Luís, Miguel; Sargento, SusanaWireless networking is expected to sustain the direct interaction between personal users’ devices, and to provide connectivity on large-scale resource-constrained devices. However, conventional networking protocols fail in large scale mobile wireless environments, due to node mobility, dynamic topologies, and intermittent connectivity. Information-Centric Networking (ICN) has been considered the most promising candidate to overcome the drawbacks of host-centric architectures where Named Data Networking (NDN) is one of the well-known and studied architectures within the ICN paradigm. The main objective of this work is to improve both content availability and network performance in mobile environments regarding the ICN paradigm. This is provided through a context-based approach for the caching admission policy providing in-network caching and content replication, facilitating the efficient and timely delivery of information. Content popularity, freshness, proximity, source mobility type and network density are some of the metrics considered in the caching decision. We conducted a comparative study between our proposal and the NDN caching strategy by using two different datasets with real mobility and connectivity traces, addressing intermittent communication. According to our results, we observed that using a multi-criteria context-based cache admission policy improves cache hits, cache evictions, and request satisfaction ratios in mobile environments, thus improving content delivery and network efficiency.
- A multi-layer probing approach for video over 5G in vehicular scenariosPublication . LOPES, RUI; Rocha, Filipe; Sargento, Susana; Luís, Miguel; Leitão, Ricardo; Marques, Eduardo; Antunes, BrunoFifth generation (5G) technologies are becoming a reality throughout the world. In parallel, vehicular networks rise their pace in terms of utilization; moreover, multimedia content transmissions are also getting an always increasing demand by their users. Besides the promised performance of 5G networks, several questions still arise among the community: are these networks capable of delivering high quality video streaming services in moving scenarios? What is the relationship between the network conditions and the video quality of experience? To answer to the previous questions, in this paper we propose a multi-layer probing approach able to assess video transmissions over 5G and 4G, combining data from all layers of a communication model, relating events from its origin layers. The probe's potential is thoroughly evaluated in two distinct video streaming use cases, both targeting a vehicular scenario supported by cellular 4G and 5G networks. Regarding the probe's performance, we show that a multitude of performance and quality indicators, from different stack layers, can be obtained. As for the performance of 4G and 5G networks in video streaming scenarios, the results have shown that the 5G links show a better overall performance in terms of video quality-of-experience, granting lower delays and jitter conditions, thus allowing video delay to be diminished and segment buffering to be better performed in comparison to 4G, while still showing adaptability in lightly traffic-saturated vehicular-to-vehicular scenarios.