Internet DRAFT - draft-vazquez-nfvrg-netcod-function-virtualization
draft-vazquez-nfvrg-netcod-function-virtualization
NFVRG M. A. Vazquez-Castro
Internet-Draft T. Do-Duy
Intended status: Informational UAB
Expires: May 20, 2018 S. P. Romano
A. M. Tulino
Unina
November 16, 2017
Network Coding Function Virtualization
draft-vazquez-nfvrg-netcod-function-virtualization-02
Abstract
This document describes network coding as a network function. It
also describes how a network coding function can be virtualized and
integrated with virtual network functions architectures. The network
coding function is not a traditionally implemented network function
in dedicated hardware as those that have triggered network function
virtualization. It refers to a novel network functionality that
generalizes classic packet-level end-to-end coding. Classic packet-
level end-to-end coding helps in the provision of quality of service
by trading off delay and reliability. Network coding goes beyond
that by enabling in-network optimized re-encoding, which can provide
both throughput gains and diverse network-controlled degrees of
reliability. Consequently, a virtualized network coding function can
serve as a flow engineering tool over virtualized networks (e.g. over
network slices).
Status of This Memo
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Conventions used in this document . . . . . . . . . . . . . . 4
3. Network coding as a network function . . . . . . . . . . . . 5
3.1. Design domains of the network coding function . . . . . . 6
3.1.1. Coding domain . . . . . . . . . . . . . . . . . . . . 6
3.1.2. Functional domain . . . . . . . . . . . . . . . . . . 6
3.1.3. Protocol domain . . . . . . . . . . . . . . . . . . . 7
3.2. Flexible modular design via sets of subfunctions . . . . 7
3.2.1. Coding/Re-encoding/Decoding Functionalities (CRDF) . 7
3.2.2. Flow Engineering Functionalities (FEF) . . . . . . . 7
3.2.3. Physical/Abstraction Functionalities (PAF) . . . . . 7
4. Virtual Network Coding Function . . . . . . . . . . . . . . . 7
4.1. Virtualization of flows . . . . . . . . . . . . . . . . . 7
4.2. Integration with ETSI NFV architecture . . . . . . . . . 8
4.3. Example . . . . . . . . . . . . . . . . . . . . . . . . . 9
4.3.1. The SHINE use case . . . . . . . . . . . . . . . . . 10
5. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . 14
6. Differences with respect to version -01 . . . . . . . . . . . 14
7. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 14
8. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 14
9. Security Considerations . . . . . . . . . . . . . . . . . . . 15
10. References . . . . . . . . . . . . . . . . . . . . . . . . . 15
10.1. Normative Information References . . . . . . . . . . . . 15
10.2. Conceptual ground basis . . . . . . . . . . . . . . . . 15
10.3. Application references . . . . . . . . . . . . . . . . . 15
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 17
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1. Introduction
Network coding(NC) is a novel technology that can be seen as the
generalization of classic point to point coding to coding for network
flows. As with classic coding, both information theoretical and
algebraic codes literature provide the conceptual solid basis of NC.
Such conceptual basis has clarified NC benefits and corresponding
tradeoffs, which need to be considered in practical implementations
of the technology.
NC does not replace end-to-end (packet-level block) coding, which is
a well-established technology for the per-flow provision of quality
of service by trading off delay and reliability. Instead, NC
provides coding within and across network flows relying on in-network
re-encoding based on service-intent-oriented policy strategies. By
means of such policy strategies, the provision of quality of service
that NC can offer can be tailored according to desired network
service intent.
For its operation, NC relies on having access to network, computation
and storage resources throughout the network. Such novel networking,
computational and storage ingredients of a coding technology calls
for novel practical design approaches to truly exploit the potential
capabilities of NC.
On the other hand, Network Function Virtualization (NFV) and NC can
be seen as different ways to address different challenges in the
design of upcoming network technologies. Moreover, NC is not a
traditionally implemented network function in dedicated hardware,
which are the network functions that have triggered the design of NFV
architectures. However, in this document we show the feasibility and
benefits of virtualizing the network coding function.
The objective of this document is not to explain network coding
technology. The interested reader should find this information
outside this document.
The objective of this document is fundamentally two fold. First, we
show that NC can be designed as a (modular) network function. The
modularity is convenient for the user and is given as sets of
elementary functionalities (toolboxes) that are defined independent
of the physical network. Second, we show that the NC function
requirements of connectivity, computation and storage resources find
a natural practical design solution in the integration of the NC
function with available NFV architectural frameworks. Such solution
is described here and it combines network protocol-driven and system
modular-driven design approaches.
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The resulting Virtual Network Coding Function (VNCF) can be useful
for upcoming networking needs derived from network virtualization.
In order to provide the readers with a flavor of how the ideas
presented in this draft might be applied to real-world communication
scenarios, we will describe an interesting use case related to the
creation of a hybrid satellite-terrestrial infrastructure for the
effective delivery of multimedia contents to end-users. The
architecture in question envisages a combination of multicast,
simulcast and unicast communication scenarios where satellite links
are exploited to support local in-network caching. The satellite
acts as the interconnection link between distributed in-network
caches and terrestrial CDN (Cotent Delivery Network) and/or feeds
edge-network caches at micro-centre locations.
The example architecture will be orchestrated through an enhanced NFV
management framework exposing Network Coding functionality as a
Virtual Network Function (VNF). Such a function will in our case
implement a novel "combined coding" technique targeting the
optimization of multicast-enabled transmissions in the presence of
caching. More precisely, it will leverage cutting-edge solutions for
decentralized random caching which, combined with an original content
distribution technique based on coded multicast, will allow us to
abtain "order-optimal" performance.
In a nutshell, the above mentioned technique allows us to somehow
multiplex multiple transmission chunks on a single packet, thus
enabling us to meet the twofold objective of optimizing the use of
the broadcast communication medium while at the same time
dramatically increasing the security level of satellite-enabled
transmissions, by making them resilient to network attacks like
snooping and eavesdropping.
2. Conventions used in this document
The following terms defined in this document can be found in the ETSI
NFV [etsi_gs_nfv_002_v1.2.1] and the IETF [I-D.irtf-nwcrg-network-
coding-taxonomy].
Coherent Network Coding: Source and destination nodes know network
topology and coding operations at intermediate nodes.
Noncoherent Network Coding: Source and destination nodes do not know
network topology and intermediate coding operations. In this case,
random network coding can be applied.
Flow: A stream of physical packets logically grouped from the network
coding perspective. These packets may come from the same application
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(in that case they are identified by the five-tuple: source and
destination IP address, transport protocol ID, and source and
destination port of the transport protocol), or come from the same
source host (in which case they are identified by the 3-tuple source
and destination IP address, Type of Service (TOS) or Diffserv code
point(DSCP)). This distinction depends on the use-case where network
coding is applied.
Intra-flow coding: Network coding over payloads belonging to the same
flow.
Inter-flow coding: Network coding over payloads belonging to multiple
flows.
End-to-end coding : Transport stream is coded and decoded at end-
points.
Coding node: Node performing coding operations.
Virtualized Infrastructure Manager (VIM): functional block that is
responsible for controlling and managing the NFVI compute, storage
and network resources, usually within one operator's Infrastructure
Domain.
Virtualized Network Function (VNF): implementation of a Network
Function that can be deployed on a Network Function Virtualization
Infrastructure (NFVI).
Virtualized Network Function Manager (VNFM): functional block that is
responsible for the lifecycle management of VNF.
NFV Infrastructure (NFVI): totality of all hardware and software
components which build up the environment in which VNFs are deployed.
NFV Orchestrator (NFVO): functional block that manages the Network
Service (NS) lifecycle and coordinates the management of NS
lifecycle, VNF lifecycle (supported by the VNFM) and NFVI resources
(supported by the VIM) to ensure an optimized allocation of the
necessary resources and connectivity.
NFV Management and Orchestration (NFV-MANO): functions collectively
provided by NFVO, VNFM, and VIM.
3. Network coding as a network function
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3.1. Design domains of the network coding function
NC design involves different domains. There are three reasons to
identify such different domains for the design of network coding
functions.
First, network coding is intrinsically multidisciplinary involving at
least dealing with the design of codes and networking using codes.
Therefore development of solutions can benefit from a clear
distinction of in which domain experts are contributing.
Second, a network coding function is a transversal network function
that can be used to provide solutions to different types of problems
such as congestion problems, bottleneck problems, losses problems,
security problems, etc. Therefore, there should be more design
domains other than purely protocol domain as it is the case with
standard protocols.
Finally, a network coding function that will operate over softwarised
networks with cloud storage and computational resources, needs to be
designed in a way that is close to a functional software
architecture.
We identify at least the three domains, as illustrated in the
following subsections.
3.1.1. Coding domain
This is th domain for the design of network coding codebooks,
coherent or noncoherent encoding/decoding schemes, performance
benchmarks, appropriate mathematical-to-logic maps, etc. This is a
domain fundamentally designed by coding theorists.
[Editor's note] To be completed...
3.1.2. Functional domain
This is the domain for the design of the different sub-functions for
network coding to achieve the desired design objectives upon
abstractions of networks and systems.
This domain jointly requires to consider physical-logical
abstraction, identification of network coding application to either
inter-flow or intra-flow network coding, service intent and related
networking for the provision of quality of service.
[Editor's note] To be completed...
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3.1.3. Protocol domain
This is the domain for the design of headers, initial settings, etc
for the physical transporting of the network coded information flow
as one way or interactive protocols.
[Editor's note] To be completed...
3.2. Flexible modular design via sets of subfunctions
In order to provide the designer with sufficient flexibility, NC
elementary sub-functionalities can be grouped in the functional
domain as a set of toolboxes that the designer can use.
We define the three toolboxes described in the following subsections.
3.2.1. Coding/Re-encoding/Decoding Functionalities (CRDF)
[Editor's note] To be completed...
3.2.2. Flow Engineering Functionalities (FEF)
These subfunctionalities perform optimization of available network
resources to optimally perform NC to meet the service design targets
depending on the (statistical) status of the networks (congestion,
link failures, etc).
[Editor's note] To be completed...
3.2.3. Physical/Abstraction Functionalities (PAF)
These subfunctionalities performing interaction with available
storage and computation physical resources that are abstracted by the
other toolboxes.
[Editor's note] To be completed...
4. Virtual Network Coding Function
4.1. Virtualization of flows
An important differentiating aspect of NC with respect to traditional
networking technologies is the following. A network flow for a NC
network function is understood as a stream of physical packets
logically grouped from the network coding perspective.
NC can optimize the NC operation abstracting such physical flow as a
mathematical model, which can be subject of computational
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manipulation. This makes NC to be naturally integrated into a
virtualized framework of abstract entities such as virtual network or
network slices. This is because in the NC case, not only the network
and resources are abstracted, but also the stream of packets is
abstracted.
Consequently, when interpreting NC as a functionality provided to the
network, NC function virtualization simply consists of integrating
the NC functional toolboxes described in the previous section into
existing architectural NFV frameworks. The virtualization of the
network flow is managed by the NC function (CRDF toolbox), and the
virtualization of all the functionalities described in Section 3 has
no difference with respect to any other network function.
4.2. Integration with ETSI NFV architecture
Figure 1 shows our proposed virtual NC network function (VNCF). It
is integrated with the ETSI NFV architecture given the abstracted
underlying physical system/network as part of NFVI.
The integration naturally includes too exchanges between VNCF and
NFV-MANO over reference points.
Clearly, the functionalities of the FEF toolbox need to interact with
the NFVO, VNFM, and VIM. Note that the NFVO two main
responsibilities of orchestration of NFVI resources across VIMs and
the life-cycle management of network services, fit perfectly the
needs of the FEF and PAF toolboxes. Specifically, the FEF can obtain
available network, connectivity and computation resources, geo-
statistical status of the networks such as congestion, link failures,
etc. With these, NC operation can be optimized to meet the service
design targets given the service-specific design constraints. The
optimization may result into manipulation of the (non-physical) flows
and other flow engineering policies. On the other hand, the FEF can
interact with the VIM to obtain the allocation, upgrade, release, etc
of NFVI resources.
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+-------------------------------------------+ +---------------+
| Virtualized Network Functions (VNFs) | | |
| ------- ------- ------- ------- | | |
| | | | | | | | | | | |
| | VNF | | VNF | |VNCF | | VNF | | | |
| | | | | | | | | | | |
| ------- ------- ------- ------- | | |
+-------------------------------------------+ | |
+-------------------------------------------+ | |
| NFV Infrastructure (NFVI) | | NFV |
| ----------- ----------- ----------- | | Management |
| | Virtual | | Virtual | | Virtual | | | and |
| | Compute | | Storage | | Network | | | Orchestration |
| ----------- ----------- ----------- | | |
| +---------------------------------------+ | | |
| | Virtualization Layer | | | |
| +---------------------------------------+ | | |
| +---------------------------------------+ | | |
| | ----------- ----------- ----------- | | | |
| | | Compute | | Storage | | Network | | | | |
| | ----------- ----------- ----------- | | | |
| | Hardware resources | | | |
| +---------------------------------------+ | | |
+-------------------------------------------+ +---------------+
Figure 1: ETSI NFV framework with one VNCF box as part of the set of
available VNFs
4.3. Example
We describe here a high-level example of a general procedure of
interaction between the VNCF and the NFV-MANO. The NFV-MANO has
repositories that hold different information regarding network
services (NSs) and VNFs (VNCF is part of VNFs). There are four types
of repositories as follows:
o VNF catalogue represents the repository of all usable VNF
packages, supporting the creation and management of the VNF
packages.
o NS catalogue represents the repository of all usable NSs.
o NFV instances is the repository that holds details of all VNF
instances and NS instances, represented by either a VNF record or
a NS record, respectively, during the execution of VNF/NS life-
cycle management operations.
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o NFVI resources is the repository that holds information about NFVI
resources utilized for the establishment of NS and VNF instances.
Assume a network abstracted as a set of N coding nodes, each with
encoding/re-encoding/decoding and (possibly) multi-link connectivity.
A user of the VNCF wants to provide an ultra-reliable service (e.g.
mission-critical communications) to the N nodes. The performance
objectives are given as a set of N reliability and delay objective
performance metrics, which are geo-location dependent. We call this
VNCF instantiation as a virtual geo-network coding function (VGNCF),
which is activated and its management and orchestration take place.
A detailed interaction with the architectural blocks (some under
definition) is as follows.
o TBD
The next section will briefly introduce a real-world application
scenario associated woth the effective deivery of multimedia content
in a hybrid satellite-terrestrial network.
4.3.1. The SHINE use case
SHINE stands for "Secure Hybrid In Network caching Environment". It
has two main distinctive features, associated with, respectively, the
broadcast-enabled satellite core and the edge distribution networks.
Within the former part of the network, we rely on network coding in
order to define a coded multicast technique allowing us to improve
both performance and security of communications. At the edges of the
distribution network, which also act as in-network caches, we instead
leverage cutting-edge streaming technologies (namely, MPEG-DASH and/
or WebRTC) in order to optimize content distribution towards the end
users of the network.
A high-level view of the SHINE architecture is reported in Figure 2.
The picture highlights the main logical components of the
architecture, in terms of macro-blocks and related functionality.
Namely, we identify the following elements:
1. a source encoder block, taking on the responsibility of properly
encoding the original content in order to allow for the
subsequent coded multicast transmission over the satellite
network;
2. the core satellite-enabled communication infrastructure, looking
after DVB-enabled transmission of coded multicast frames from the
content provider to the edge caches, both during the cache
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population phase and during the steady-state operation of the
CDN;
3. two different "flavors"" of edge access networks: (i) a WebRTC-
enabled access network, included in the architecture in order to
demonstrate SHINE's operation in the presence of this novel real-
time communication infrastructure at the edges of the overall
content delivery architecture; (ii) an MPEG-DASH enabled access
network, included in the architecture in order to demonstrate
SHINE's capability of leveraging such a well-assessed web-based
distribution approach.
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+-------+ Satellite GW
/-| | -
/--- | | \-
/--- +-------+ \-
/-- /- | \ Network encoder
/--- /- | \- +-------+
/--- /- / \- | |
/-- /- | \- | |
/--- /- | \| |
/--- /- | | |
-- /- | | |
+---+ /- / +-------+
| | /- Coded Multicast| -/
| |Edge cache /- Transmission | -/
| | /- | -/
| | /- / +----------------+
+---------------+ /- | | |
| +---+| /- | | |
| | /- | |Content Provider|
| | /- | | |
| | /- / | |
| | - | | |
| | +---+ | +----------------+
+---------------+ | | +-|-+ +---+
| | Edge cache | | | | Origin
| | Edge cache| | | |---+ server
| | | | | | | farm
+---------------+ | | | | +-|-+
| +---+ | +---------------+ | | | | |
| | | +---+| +---+ | | |
| | | | | | | |
| | | | +---+ |
| | | | | |
| | | | +---+
+---------------+ | |
Edge distribution network +---------------+
Edge distribution network
Figure 2: The SHINE use case
The system components which are of uttermost importance in this
document, in view of the observation that they can highly benefit
from the effective utilization of Network Coding as a Virtual Network
Function are analyzed in further detail in the following.
The source encoder is a software module implementing the main logic
behind the proposed coded multicast technique. It is in charge of
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transforming the original content and applying the required
transformations in order to arrive at a representation format that is
suitable for the subsequent coded multicast transmission. The
component in question has indeed to look after both the cache
population phase and the actual content delivery phase. The cache
population phase envisages that the edge caches pre-fetch some
content, based on appropriate functions of the content library, as
well as on information about estimated future users' demand for
content. During the delivery phase, on the other hand, the source
forms a multicast "codeword" to be transmitted over the shared link
in order to meet the actual users' content demands. As already
stated, we envisage that the cache population phase is carried out
through transmission (over the satellite core network connecting
source node with edge caches) of content chunks. As to the content
delivery phase, it takes place through DVB-encapsulated transmission,
over the satellite network, of coded multicast frames.
Satellite Core Network is the network segment that basically
interconnects the Source Encoder, which produces and processes
multimedia contents, and several Edge Networks, where the in-network
caches represent the boundary network elements. The satellite
network trunk leverages standard DVB-S or DVB-S2 broadcast
The delivery phase hence occurs after the placement phase, when
traffic is high and network resources are scarce and expensive (e.g.,
in the evening). At the beginning of this phase, each user reveals
its request for one of the m files. The server is informed of these
K requested files. In response, the server sends RF bits (or the
equivalent of R files) over the shared link. The number R is called
the rate of the server transmission or equivalently load of the
satellite link. From the server transmission and its local cache
content, each user needs to be able to recover their requested files.
As already anticipated, SHINE looks after both the content placement
and delivery phases. The objective is to minimize the rate R with
which every possible set of user demands can be satisfied. The
constraints are the storage limit during content placement and the
recovery requirement during content delivery. Both phases are
generic for both coded and uncoded schemes, but naively performed in
the uncoded case. In fact, when relying on uncoded or naive
multicasting during the delivery phase, it is well known that the
optimal caching strategy is to cache the top M most popular files at
each user cache. Though, this is in general far from optimal when
coding can be used in the delivery phase. Thanks to the adoption of
the dynamically provided Virtual Network Coding Function, SHINE
discloses the potential of caching-aided code design and illustrates
its major advantages compared to the optimal caching policy under
uncoded (naive) multicasting. In a nutshell, the designed
architecture shows how the combined use of edge caching and coded
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multicasting represents a promising approach to simultaneously serve
multiple unicast demands via coded multicast transmissions, leading
to order-of-magnitude bandwidth efficiency gains.
5. Conclusions
This memo presents a preliminary version of proposal for the design
of NC as a network function. It is also discussed that it can be
virtualized and integrated into a NFV architecture.
6. Differences with respect to version -01
Major restructuring of section 3.
7. Acknowledgements
The authors want to thank Dr. Harald Skinnemoen for useful comments
and discussions. The first author wants to thank Dr. Carlos J.
Bernardos and Luis M. Contreras for useful discussions.
The authors also want to acknowledge the following ongoing projects.
1. GEO-VISION - GNSS driven EO and Verifiable Image and Sensor
Integration for mission-critical Operational Networks. EU funded
project under the call H2020-GALILEO-2014-1 by the European
Global Navigation Satellite Systems Agency (project reference
641451).
2. SatNetCode - Satellite Network-Coding for high performance,
semantic-aware mission-critical visual communications. This
project is funded by the European Space Agency, under contract
No. 4000115046/15/NL/US.
3. HENCSAT - Highly Efficient Network Coding for Satellite
Applications Test-bed. This project is funded by the European
Space Agency, under contract No. 4000118143/16/NL/EM.
4. SHINE - Secure Hybrid In Network caching Environment. This
project is funded by the European Space Agency, under Contract
No. 4000118273/16/NL/CLP.
8. IANA Considerations
This memo includes no request to IANA.
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9. Security Considerations
This memo includes no Network Coding Function Virtualization -
specific security definitions yet.
10. References
10.1. Normative Information References
[etsi_gs_nfv_002_v1.2.1]
"Network Function Virtualisation (NFV); Architectural
Framework", 2014.
[etsi_nvf_whitepaper]
"Network Functions Virtualisation (NFV). White Paper 2",
2014.
[I-D.irtf-nwcrg-network-coding-taxonomy]
Firoiu, V., Adamson, B., Roca, V., Adjih, C., Bilbao, J.,
Fitzek, F., Masucci, A., and M. Montpetit, "Network Coding
Taxonomy", draft-irtf-nwcrg-network-coding-taxonomy-01
(work in progress), October 2016.
[RFC6363] Watson, M., Begen, A., and V. Roca, "Forward Error
Correction (FEC) Framework", RFC 6363, 2011.
10.2. Conceptual ground basis
[AHL00] Ahlswede, R., Cai, N., Y. R. Li, S., and R. W. Yeung,
"Network information flow", in IEEE Trans. Inform. Theory,
vol. 46, pp. 1204-1216, July 2000.
[KOE03] Koetter, R. and M. Medard, "An algebraic approach to
network coding", in IEEE/ACM Trans. on Networking, vol.
11, n. 5., pp. 782-795, October 2003.
[LI03] Y.R.Li, S., W. Yeung, R., and N. Cai, "Linear network
coding", in IEEE Trans. Inform. Theory, vol. 49, n. 2.,
pp. 371-381, February 2003.
10.3. Application references
[ALE13] Alegre-Godoy, R. and M. A. Vazquez-Castro, "Spatial
Diversity with Network Coding for ON/OFF Satellite
Channels", in IEEE Communications Letters, vol. 17, No. 8,
pp. 1612-1615, August 2013.
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[ALE15] Alegre-Godoy, R. and M. A. Vazquez-Castro, "Network Coded
Multicast over Multi-beam Satellite Systems", in
Mathematical Problems in Engineering, vol. 2015, Article
ID 364234, May 2015.
[DO16.1] Do-Duy, T. and M. A. Vazquez-Castro, "Design of
Virtualized Network Coding Functionality foR Reliability
Control of Communication Services over Satellite",
submitted to Special Issue on Network Coding.
International Journal of Satellite Communications and
Networking, 2016.
[Do16.2] Do-Duy, T. and M. A. Vazquez-Castro, "Network coding
function virtualization", in IEEE 17th International
Workshop on Signal Processing Advances in Wireless
Communications (SPAWC), September 2016, INVIED PAPER.
[HAN15] Hansen, J., E. Lucani, D., Krigslund, J., Medard, M., and
F. H. P. Fitzek, "Network coded software defined
networking: enabling 5G transmission and storage
networks", in IEEE Communications Magazine, 2015.
[HEI09] Heide, J., V. Pedersen, M., H. P. Fitzek, F., and T.
Larsen, "Network Coding for Mobile Devices - Systematic
Binary Random Rateless Codes", in ICC Workshops, 2009.
[SAX15] Saxena, P. and M. A. Vazquez-Castro, "DARE: DoF-Aided
Random Encoding for Network Coding over Lossy Line
Networks", in IEEE Communications Letters, vol. 19, No. 8,
pp. 1374-1377, August 2015.
[SZA15] Szabo, D., Nemeth, F., Sonkoly, B., Gulyas, A., and F. H.
P. Fitzek, "Towards the 5G revolution: A software defined
network architecture exploiting network coding as a
service", in SIGCOMM Comput. Commun, 2015.
[VAZ15.1] A. Vazquez-Castro, M., "A Geometric Approach to Dynamic
Network Coding", in Information Theory Workshop, Jeju,
Korea, October 2015.
[VAZ15.2] A. Vazquez-Castro, M., "Subspace coding over Fq-linear
erasure satellite channels", in 12th International
Symposium on Wireless Communication Systems, pp. 216-220,
August 2015.
A. Vazquez-Castro, et al. Expires May 20, 2018 [Page 16]
Internet-Draft Network Coding Function Virtualization November 2017
[VAZ15.3] A. Vazquez-Castro, M. and P. Saxena, "Network Coding over
Satellite: From Theory to Design and Performance", in
Volume 154 of the series Lecture Notes of the Institute
for Computer Sciences, Social Informatics and
Telecommunications Engineering, pp. 315-327, September
2015, INVITED PAPER.
Authors' Addresses
M.A. Vazquez-Castro
Autonomus University of Barcelona
Campus de Bellaterra
Barcelona, 08391
Spain
Email: angeles.vazquez@uab.es
Tan Do-Duy
Autonomus University of Barcelona
Campus de Bellaterra
Barcelona, 08391
Spain
Email: tan.doduy@uab.es
Simon Pietro Romano
University of Napoli Federico II
Via Claudio 21
Napoli, 80125
Italy
Email: spromano@unina.it
Antonia Maria Tulino
University of Napoli Federico II
Via Claudio 21
Napoli, 80125
Italy
Email: antoniamaria.tulino@unina.it
A. Vazquez-Castro, et al. Expires May 20, 2018 [Page 17]
