arXiv subjects

Francesco Malandrino

Publications and source records attributed to Francesco Malandrino.

At least 55 records · Page 3Linked to original sources

arXiv2019

Planning UAV Activities for Efficient User Coverage in Disaster Areas

Climate changes brought about by global warming as well as man-made environmental changes are often the cause of sever natural disasters. ICT, which is itself responsible for global warming due to its high carbon footprint, can play a role in alleviating the consequences of such hazards by providing reliable, resilient means of communication during a disaster crisis. In this paper, we explore the provision of wireless coverage through UAVs (Unmanned Aerial Vehicles) to complement, or replace, the traditional communication infrastructure. The use of UAVs is indeed crucial in emergency scenarios, as they allow for the quick and easy deployment of micro and pico cellular base stations where needed. We characterize the movements of UAVs and define an optimization problem to determine the best UAV coverage that maximizes the user throughput, while maintaining fairness across the different parts of the geographical area that has been affected by the disaster. To evaluate our strategy, we simulate a flooding in San Francisco and the car traffic resulting from people seeking safety on higher ground.

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arXiv2019

Getting the Most Out of Your VNFs: Flexible Assignment of Service Priorities in 5G

Through their computational and forwarding capabilities, 5G networks can support multiple vertical services. Such services may include several common virtual (network) functions (VNFs), which could be shared to increase resource efficiency. In this paper, we focus on the seldom studied VNF-sharing problem, and decide (i) whether sharing a VNF instance is possible/beneficial or not, (ii) how to scale virtual machines hosting the VNFs to share, and (iii) the priorities of the different services sharing the same VNF. These decisions are made with the aim to minimize the mobile operator's costs while meeting the verticals' performance requirements. Importantly, we show that the aforementioned priorities should not be determined a priori on a per-service basis, rather they should change across VNFs since such additional flexibility allows for more efficient solutions. We then present an effective methodology called FlexShare, enabling near-optimal VNF-sharing decisions in polynomial time. Our performance evaluation, using real-world VNF graphs, confirms the effectiveness of our approach, which consistently outperforms baseline solutions using per-service priorities.

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arXiv2019

Towards Failure Resiliency in 5G: Service Shifting

Many real-world services can be provided through multiple VNF graphs, corresponding, e.g., to high- and low-quality variants of the service itself. Based on this observation, we extend the concept of service scaling in network orchestration to service shifting, i.e., switching between the VNF graphs implementing the same service. Service shifting can serve multiple goals, from reducing operational costs to reacting to infrastructure problems. Furthermore, it enhances the flexibility of service-level agreements between network operators and third party content providers ("verticals"). In this paper, we introduce and describe the service shifting concept, its benefits, and the associated challenges, with special reference to how service shifting can be integrated within real-world 5G architectures and implementations. We conclude that existing network orchestration frameworks can be easily extended to support service shifting, and its adoption has the potential to make 5G network slices easier for the operators to manage under high-load conditions, while still meeting the verticals' requirements.

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arXiv2019

5G Traffic Forecasting: If Verticals and Mobile Operators Cooperate

In 5G research, it is traditionally assumed that vertical industries (a.k.a verticals) set the performance requirements for the services they want to offer to mobile users, and the mobile operators alone are in charge of orchestrating their resources so as to meet such requirements. Motivated by the observation that successful orchestration requires reliable traffic predictions, in this paper we investigate the effects of having the verticals, instead of the mobile operators, performing such predictions. Leveraging a real-world, large-scale, crowd-sourced trace, we find that involving the verticals in the prediction process reduces the prediction errors and improves the quality of the resulting orchestration decisions.

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arXiv2018

VNF Placement and Resource Allocation for the Support of Vertical Services in 5G Networks

One of the main goals of 5G networks is to support the technological and business needs of various industries (the so-called verticals), which wish to offer to their customers a wide range of services characterized by diverse performance requirements. In this context, a critical challenge lies in mapping in an automated manner the requirements of verticals into decisions concerning the network infrastructure, including VNF placement, resource assignment, and traffic routing. In this paper, we seek to make such decisions jointly, accounting for their mutual interaction, and efficiently. To this end, we formulate a queuing-based model and use it at the network orchestrator to optimally match the vertical's requirements to the available system resources. We then propose a fast and efficient solution strategy, called MaxZ, which allows us to reduce the solution complexity. Our performance evaluation, carried out accounting for multiple scenarios representative of real-world services, shows that MaxZ performs substantially better than state-of-the-art alternatives and consistently close to the optimum.

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arXiv2018

From Megabits to CPU~Ticks: Enriching a Demand Trace in the Age of MEC

All the content consumed by mobile users, be it a web page or a live stream, undergoes some processing along the way; as an example, web pages and videos are transcoded to fit each device's screen. The recent multi-access edge computing (MEC) paradigm envisions performing such processing within the cellular network, as opposed to resorting to a cloud server on the Internet. Designing a MEC network, i.e., placing and dimensioning the computational facilities therein, requires information on how much computational power is required to produce the contents needed by the users. However, real-world demand traces only contain information on how much data is downloaded. In this paper, we demonstrate how to {\em enrich} demand traces with information about the computational power needed to process the different types of content, and we show the substantial benefit that can be obtained from using such enriched traces for the design of MEC-based networks.

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arXiv2018

Characterizing the Power Cost of Virtualization Environments

Virtualization is a key building block of next-generation mobile networks. It can be implemented through two main approaches: traditional virtual machines and lighter-weight containers. Our objective in this paper is to compare these approaches and study the power consumption they are associated with. To this end, we perform a large set of real-world measurements, using both synthetic workloads and real-world applications, and use them to model the relationship between the resource usage of the hosted application and the power consumption of both virtual machines and containers hosting it. We find that containers incur substantially lower power consumption than virtual machines, and that such consumption increases more slowly with the application load.

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arXiv2018

Mining the Air -- for Research in Social Science and Networking Measurement

Smartphone apps provide a vitally important opportunity for monitoring human mobility, human experience of ubiquitous information aids, and human activity in our increasingly well-instrumented spaces. As wireless data capabilities move steadily up in performance, from 2&3G to 4G (today's LTE) and 5G, it has become more important to measure human activity in this connected world from the phones themselves. The newer protocols serve larger areas than ever before and a wider range of data, not just voice calls, so only the phone can accurately measure its location. Access to the application activity permits not only monitoring the performance and spatial coverage with which the users are served, but as a crowd-sourced, unbiased background source of input on all these subjects, becomes a uniquely valuable resource for input to social science and government as well as telecom providers

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arXiv2018

Scheduling Advertisement Delivery in Vehicular Networks

Vehicular users are emerging as a prime market for targeted advertisement, where advertisements (ads) are sent from network points of access to vehicles, and displayed to passengers only if they are relevant to them. In this study, we take the viewpoint of a broker managing the advertisement system, and getting paid every time a relevant ad is displayed to an interested user. The broker selects the ads to broadcast at each point of access so as to maximize its revenue. In this context, we observe that choosing the ads that best fit the users' interest could actually hurt the broker's revenue. In light of this conflict, we present Volfied, an algorithm allowing for conflict-free, near-optimal ad selection with very low computational complexity. Our performance evaluation, carried out through real-world vehicular traces, shows that Volfied increases the broker revenue by up to 70% with provably low computational complexity, compared to state-of-the-art alternatives.

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arXiv2018

Optimization-in-the-Loop for Energy-Efficient 5G

We consider the problem of energy-efficient network management in 5G systems, where backhaul and fronthaul nodes have both networking and computational capabilities. We devise an optimization model accounting for the main features of 5G backhaul and fronthaul, and jointly solve the problems of (i) node switch on/off, (ii) VNF placement, and (iii) traffic routing. We implement an optimization module within an application on top of an SDN controller and NFV orchestrator, thus enabling swift, high-quality decisions based on current network conditions. Finally, we validate and test our scheme with real-world power consumption, network topology and traffic demand, assessing its performance as well as the relative importance of the main contributions to the total power consumption of the system.

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arXiv2018

Area formation and content assignment for LTE broadcasting

Broadcasting and multicasting services in LTE networks are shaping up to be an effective way to provide popular content. A key requirement is that cells are aggregated into areas where a tight time synchronization among transmissions is enforced, so as to broadcast the same radio resources. Our paper addresses a facet of LTE broadcasting that has so far received little attention: the creation of broadcasting areas and the assignment of content to them in order to efficiently exploit radio resources and satisfy user requests. Our original clustering approach, named Single-Content Fusion, achieves these goals by initially aggregating cells into single-content areas and maximizing cell similarity in content interests. Aggregated areas are then merged into multiple-content areas by virtue of similar spatial coverage. We show the validity of our solution pointing out the advantages it provides in comparison to other approaches. We also discuss the impact of various system factors (e.g., number of served users, broadcast data rate, area size) and the scalability of our proposal in large, realistic scenarios with both static and time-varying user interest.

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arXiv2018

Cellular Network Traces Towards 5G: Usage, Analysis and Generation

Deployment and demand traces are a crucial tool to study today's LTE systems, as well as their evolution toward 5G. In this paper, we use a set of real-world, crowdsourced traces, coming from the WeFi and OpenSignal apps, to investigate how present-day networks are deployed, and the load they serve. Given this information, we present a way to generate synthetic deployment and demand profiles, retaining the same features of their real-world counterparts. We further discuss a methodology using traces (both real-world and synthetic) to assess (i) to which extent the current deployment is adequate to the current and future demand, and (ii) the effectiveness of the existing strategies to improve network capacity. Applying our methodology to real-world traces, we find that present-day LTE deployments consist of multiple, entangled, medium- to large-sized cells. Furthermore, although today's LTE networks are overprovisioned when compared to the present traffic demand, they will need substantial capacity improvements in order to face the load increase forecasted between now and 2020.

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arXiv2018

Performance Analysis of C-V2I-based Automotive Collision Avoidance

One of the key applications envisioned for C-V2I (Cellular Vehicle-to-Infrastructure) networks pertains to safety on the road. Thanks to the exchange of Cooperative Awareness Messages (CAMs), vehicles and other road users (e.g., pedestrians) can advertise their position, heading and speed and sophisticated algorithms can detect potentially dangerous situations leading to a crash. In this paper, we focus on the safety application for automotive collision avoidance at intersections, and study the effectiveness of its deployment in a C-V2I-based infrastructure. In our study, we also account for the location of the server running the application as a factor in the system design. Our simulation-based results, derived in real-world scenarios, provide indication on the reliability of algorithms for car-to-car and car-to-pedestrian collision avoidance, both when a human driver is considered and when automated vehicles (with faster reaction times) populate the streets.

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arXiv2018

Characterizing Docker Overhead in Mobile Edge Computing Scenarios

Mobile Edge Computing (MEC) is an emerging network paradigm that provides cloud and IT services at the point of access of the network. Such proximity to the end user translates into ultra-low latency and high bandwidth, while, at the same time, it alleviates traffic congestion in the network core. Due to the need to run servers on edge nodes (e.g., an LTE-A macro eNodeB), a key element of MEC architectures is to ensure server portability and low overhead. A possible tool that can be used for this purpose is Docker, a framework that allows easy, fast deployment of Linux containers. This paper addresses the suitability of Docker in MEC scenar- ios by quantifying the CPU consumed by Docker when running two different containerized services: multiplayer gam- ing and video streaming. Our tests, run with varying numbers of clients and servers, yield different results for the two case studies: for the gaming service, the overhead logged by Docker increases only with the number of servers; con- versely, for the video streaming case, the overhead is not affected by the number of either clients or servers.

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arXiv2018

Virtualization-based Evaluation of Backhaul Performance in Vehicular Applications

Next-generation networks, based on SDN and NFV, are expected to support a wide array of services, including vehicular safety applications. These services come with strict delay constraints, and our goal in this paper is to ascertain to which extent SDN/NFV-based networks are able to meet them. To this end, we build and emulate a vehicular collision detection system, using the popular Mininet and Docker tools, on a real-world topology with mobility information. Using different core network topologies and open-source SDN controllers, we measure (i) the delay with which vehicle beacons are processed and (ii) the associated overhead and energy consumption. We find that we can indeed meet the latency constraints associated with vehicular safety applications, and that SDN controllers represent a moderate contribution to the overall energy consumption but a significant source of additional delay.

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arXiv2016

How Close to the Edge? Delay/utilization tradeoffs in MEC

Virtually all of the rapidly increasing data traffic consumed by mobile users requires some kind of processing, normally performed at cloud servers. A recent thrust, {\em mobile edge computing}, moves such processing to servers {\em within} the cellular mobile network. The large temporal and spatial variations to which mobile data usage is subject could make the reduced latency that edge clouds offer come at an unacceptable cost in redundant and underutilized infrastructure. We present some first empirical results on this question, based on large scale sampled crowd-sourced traces from several major cities spanning multiple operators and identifying the applications in use. We find opportunities to obtain both high server utilization and low application latency, but the best approaches will depend on the individual network operator's deployment strategy and geographic specifics of the cities we study.

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arXiv2016

The Impact of Vehicular Traffic Demand on 5G Caching Architectures: a Data-Driven Study

The emergence of in-vehicle entertainment systems and self-driving vehicles, and the latter's need for high-resolution, up-to-date maps, will bring a further increase in the amount of data vehicles consume. Considering how difficult WiFi offloading in vehicular environments is, the bulk of this additional load will be served by cellular networks. Cellular networks, in turn, will resort to caching at the network edge in order to reduce the strain on their core network, an approach also known as mobile edge computing, or fog computing. In this work, we exploit a real-world, large-scale trace coming from the users of the We-Fi app in order to (i) understand how significant the contribution of vehicular users is to the global traffic demand; (ii) compare the performance of different caching architectures; and (iii) studying how such a performance is influenced by recommendation systems and content locality. We express the price of fog computing through a metric called price-of-fog, accounting for the extra caches to deploy compared to a traditional, centralized approach. We find that fog computing allows a very significant reduction of the load on the core network, and the price thereof is low in all cases and becomes negligible if content demand is location specific. We can therefore conclude that vehicular networks make an excellent case for the transition to mobile-edge caching: thanks to the peculiar features of vehicular demand, we can obtain all the benefits of fog computing, including a reduction of the load on the core network, reducing the disadvantages to a minimum.

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arXiv2016

What is LTE actually used for? An answer through multi-operator, crowd-sourced measurement

LTE networks are commonplace nowadays; however, comparatively little is known about where (and why) they are deployed, and the demand they serve. We shed some light on these issues through large-scale, crowd-sourced measurement. Our data, collected by users of the WeFi app, spans multiple operators and multiple cities, allowing us to observe a wide variety of deployment patterns. Surprisingly, we find that LTE is frequently used to improve the {\em coverage} of network rather than the capacity thereof, and that no evidence shows that video traffic be a primary driver for its deployment. Our insights suggest that such factors as pre-existing networks and commercial policies have a deeper impact on deployment decisions than purely technical considerations.

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