996 research outputs found
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
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.Comment: ACM IoV-VoI 2016 MobiHoc Workshop, The 17th ACM International
Symposium on Mobile Ad Hoc Networking and Computing: MobiHoc 2016-IoV-VoI
Workshop, Paderborn, German
Performance of Linear Field Reconstruction Techniques with Noise and Uncertain Sensor Locations
We consider a wireless sensor network, sampling a bandlimited field,
described by a limited number of harmonics. Sensor nodes are irregularly
deployed over the area of interest or subject to random motion; in addition
sensors measurements are affected by noise. Our goal is to obtain a high
quality reconstruction of the field, with the mean square error (MSE) of the
estimate as performance metric. In particular, we analytically derive the
performance of several reconstruction/estimation techniques based on linear
filtering. For each technique, we obtain the MSE, as well as its asymptotic
expression in the case where the field number of harmonics and the number of
sensors grow to infinity, while their ratio is kept constant. Through numerical
simulations, we show the validity of the asymptotic analysis, even for a small
number of sensors. We provide some novel guidelines for the design of sensor
networks when many parameters, such as field bandwidth, number of sensors,
reconstruction quality, sensor motion characteristics, and noise level of the
measures, have to be traded off
Traffic Offloading/Onloading in Multi-RAT Cellular Networks
We analyze next generation cellular networks, offering connectivity to mobile users through multiple radio access technologies (RATs), namely LTE and WiFi. We develop a framework based on the Markovian agent formalism, which can model several aspects of the system, including user traffic dynamics and radio resource allocation. In particular, through a mean-field solution, we show the ability of our framework to capture the system behavior in flash-crowd scenarios, i.e., when a burst of traffic requests takes place in some parts of the network service area. We consider a distributed strategy for the user RAT selection, which aims at ensuring high user throughput, and investigate its performance under different resource allocation scheme
Upper Bounds to the Performance of Cooperative Traffic Relaying in Wireless Linear Networks
Wireless networks with linear topology, where nodes generate their own traffic and relay other nodes' traffic, have attracted increasing attention. Indeed, they well represent sensor networks monitoring paths or streets, as well as multihop networks for videosurveillance of roads or vehicular traffic. We study the performance limits of such network systems when (i) the nodes' transmissions can reach receivers farther than one-hop distance from the sender, (ii) the transmitters cooperate in the data delivery, and (iii) interference due to concurrent transmissions is taken into account. By adopting an information-theoretic approach, we derive analytical bounds to the achievable data rate in both the cases where the nodes have full-duplex and half-duplex radios. The expressions we provide are mathematically tractable and allow the analysis of multihop networks with a large number of nodes. Our analysis highlights that increasing the number of coop- erating transmitters beyond two leads to a very limited gain in the achievable data rate. Also, for half-duplex radios, it indicates the existence of dominant network states, which have a major influence on the bound. It follows that efficient, yet simple, communication strategies can be designed by considering at most two cooperating transmitters and by letting half-duplex nodes operate according to the aforementioned dominant state
Output Statistics of MIMO Channels with General Input Distribution
The information that can be conveyed through a wireless channel, with multiple-antenna equipped transmitter and receiver, crucially depends on the channel behavior as well as on the input structure. In this paper, we derive analytical results, concerning the probability density function (pdf) of the output of a single-user, multiple-antenna communication. The analysis is carried out under the assumption of an optimized input structure, and assuming Gaussian noise and a Rayleigh block-fading channel. Our analysis therefore provides a quite general and compact expression for the conditional output pdf. We also highlight the relation between such an expression and the results already available in the literature for some specific input structure
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