arXiv subjects

Francesco Malandrino

Publications and source records attributed to Francesco Malandrino.

58 records · Page 4Linked to original sources

arXiv2016

The Price of Fog: a Data-Driven Study on Caching Architectures in Vehicular Networks

Vehicular users are expected to consume large amounts of data, for both entertainment and navigation purposes. This will put a strain on cellular networks, which will be able to cope with such a load only if proper caching is in place, this in turn begs the question of which caching architecture is the best-suited to deal with vehicular content consumption. In this paper, we leverage a large-scale, crowd-collected trace to (i) characterize the vehicular traffic demand, in terms of overall magnitude and content breakup, (ii) assess how different caching approaches perform against such a real-world load, (iii) study the effect of recommendation systems and local contents. We define a price-of-fog metric, expressing the additional caching capacity to deploy when moving from traditional, centralized caching architectures to a "fog computing" approach, where caches are closer to the network edge. We find that for location-specific contents, such as the ones that vehicular users are most likely to request, such a price almost disappears. Vehicular networks thus make a strong case for the adoption of mobile-edge caching, as we are able to reap the benefit thereof -- including a reduction in the distance traveled by data, within the core network -- with little or no of the associated disadvantages.

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arXiv2015

A Sharing- and Competition-Aware Framework for Cellular Network Evolution Planning

Mobile network operators are facing the difficult task of significantly increasing capacity to meet projected demand while keeping CAPEX and OPEX down. We argue that infrastructure sharing is a key consideration in operators' planning of the evolution of their networks, and that such planning can be viewed as a stage in the cognitive cycle. In this paper, we present a framework to model this planning process while taking into account both the ability to share resources and the constraints imposed by competition regulation (the latter quantified using the Herfindahl index). Using real-world demand and deployment data, we find that the ability to share infrastructure essentially moves capacity from rural, sparsely populated areas (where some of the current infrastructure can be decommissioned) to urban ones (where most of the next-generation base stations would be deployed), with significant increases in resource efficiency. Tight competition regulation somewhat limits the ability to share but does not entirely jeopardize those gains, while having the secondary effect of encouraging the wider deployment of next-generation technologies.

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arXiv2014

Real-Time Scheduling for Content Broadcasting in LTE

Broadcasting capabilities are one of the most promising features of upcoming LTE-Advanced networks. However, the task of scheduling broadcasting sessions is far from trivial, since it affects the available resources of several contiguous cells as well as the amount of resources that can be devoted to unicast traffic. In this paper, we present a compact, convenient model for broadcasting in LTE, as well as a set of efficient algorithms to define broadcasting areas and to actually perform content scheduling. We study the performance of our algorithms in a realistic scenario, deriving interesting insights on the possible trade-offs between effectiveness and computational efficiency.

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arXiv2013

Fast Resource Scheduling in HetNets with D2D Support

Resource allocation in LTE networks is known to be an NP-hard problem. In this paper, we address an even more complex scenario: an LTE-based, 2-tier heterogeneous network where D2D mode is supported under the network control. All communications (macrocell, microcell and D2D-based) share the same frequency bands, hence they may interfere. We then determine (i) the network node that should serve each user and (ii) the radio resources to be scheduled for such communication. To this end, we develop an accurate model of the system and apply approximate dynamic programming to solve it. Our algorithms allow us to deal with realistic, large-scale scenarios. In such scenarios, we compare our approach to today's networks where eICIC techniques and proportional fairness scheduling are implemented. Results highlight that our solution increases the system throughput while greatly reducing energy consumption. We also show that D2D mode can effectively support content delivery without significantly harming macrocells or microcells traffic, leading to an increased system capacity. Interestingly, we find that D2D mode can be a low-cost alternative to microcells.

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