ICNRG K. Pentikousis, Ed.
Internet-Draft Huawei Technologies
Intended Status: Informational B. Ohlman
Expires: September 12, 2013 Ericsson
D. Corujo
Universidade de Aveiro
G. Boggia
Politecnico di Bari
G. Tyson
Queen Mary College, London
E. Davies
Trinity College Dublin
D. Gellert
InterDigital
P. Mahadevan
PARC
March 11, 2013
ICN Baseline Scenarios
draft-pentikousis-icn-scenarios-02
Abstract
This document aims at establishing a common understanding about
potential experimental setups where different information-centric
networking (ICN) approaches can be tested and compared against each
other while showcasing their advantages. Towards this end, we
develop several scenarios in an iterative fashion, starting by
reviewing pertinent ICN evaluations from the published literature.
That is, the document includes scenarios which have all been
considered in one or more performance evaluation studies and are
already available to the community. The scenarios selected aim to
exercise a variety of aspects that an ICN solution can address. On
the one hand, we consider general aspects, such as, network
efficiency, reduced complexity, increased scalability and
reliability, mobility support, multicast and caching performance,
real-time communication efficacy, energy consumption frugality, and
disruption and delay tolerance. On the other hand, we focus on ICN-
specific aspects, such as, information security and trust,
persistence, availability, provenance, and location independence.
Status of this Memo
This Internet-Draft is submitted to IETF in full conformance with the
provisions of BCP 78 and BCP 79.
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Table of Contents
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 3
2 Toward ICN Baseline Scenarios . . . . . . . . . . . . . . . . . 4
2.1 Social Networking . . . . . . . . . . . . . . . . . . . . . 4
2.2 Real-time A/V Communications . . . . . . . . . . . . . . . 6
2.3 Mobile Networking . . . . . . . . . . . . . . . . . . . . . 7
2.4 Infrastructure Sharing . . . . . . . . . . . . . . . . . . 8
2.5 Content Dissemination . . . . . . . . . . . . . . . . . . . 9
2.6 Network Interaction . . . . . . . . . . . . . . . . . . . . 11
2.7 Energy Efficiency . . . . . . . . . . . . . . . . . . . . . 14
2.8 Delay and Disruption Tolerance . . . . . . . . . . . . . . 15
2.9 Internet of Things . . . . . . . . . . . . . . . . . . . . 16
2.10 Smart City . . . . . . . . . . . . . . . . . . . . . . . . 18
3 Evaluation Methodology . . . . . . . . . . . . . . . . . . . . 20
3.1 ICN Simulators and Testbeds . . . . . . . . . . . . . . . . 20
3.1.1 CCN and NDN . . . . . . . . . . . . . . . . . . . . . . 21
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3.1.2 Publish/Subscribe Internet Architecture . . . . . . . . 21
3.1.3 NetInf . . . . . . . . . . . . . . . . . . . . . . . . 22
3.2 Topology Selection . . . . . . . . . . . . . . . . . . . . 22
3.3 Traffic Load . . . . . . . . . . . . . . . . . . . . . . . 23
3.4 Choosing Relevant Metrics . . . . . . . . . . . . . . . . . 24
3.4.1 Traffic Metrics . . . . . . . . . . . . . . . . . . . . 24
3.4.2 System Metrics . . . . . . . . . . . . . . . . . . . . 24
3.5 Resource Equivalence and Tradeoffs . . . . . . . . . . . . 25
3.6 Technology Evolution Assumptions . . . . . . . . . . . . . 25
4 Security Considerations . . . . . . . . . . . . . . . . . . . . 25
5 IANA Considerations . . . . . . . . . . . . . . . . . . . . . . 26
6 Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . 26
7 Informative References . . . . . . . . . . . . . . . . . . . . 26
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 32
1 Introduction
Information-centric networking (ICN) marks a fundamental shift in
communications and networking. In contrast with the omnipresent and
very successful host-centric paradigm, which is based on perpetual
connectivity and the end-to-end principle, ICN changes the focal
point of the network architecture from the "end host" to
"information" (or content, or data). In this paradigm, connectivity
may well be intermittent. End-host and in-network storage can be
capitalized upon transparently, as bits in the network and on storage
devices have exactly the same value. Mobility and multiaccess are
the norm. Any-, multi-, and broadcasting are supported by default,
and energy efficiency is a design consideration from the beginning.
Although interest in ICN is growing rapidly, ongoing work on
different architectures, such as, for example, NetInf [NetInf], CCN
and NDN [CCN], the publish-subscribe Internet (PSI) architecture
[PSI], and the data-oriented architecture [DONA] is far from being
completed. The development phase that ICN is going through and the
plethora of approaches to tackle the hardest problems make this a
very active and appealing research area but, on the downside, it also
makes it more difficult to compare different proposals on an equal
footing.
Ahlgren et al. note [SoA] that describing ICN architectures is akin
to shooting a moving target. We find that comparing these different
approaches is often even more tricky. It is not uncommon that
different researchers select different performance evaluation
scenarios, typically with good reasons, in order to highlight the
advantages of their approach. This should be expected to some degree
at this early stage of development. Nevertheless, we argue that
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certain scenarios seem to emerge where ICN architectures could
showcase their superiority over current systems, in general, and
against each other, in particular.
This document starts in Section 2 by collecting several scenarios
from the published ICN literature and aims to use them as foundation
for the baseline scenarios to be considered by the IRTF Information-
Centric Networking Research Group (ICNRG) in its future work. The
list of scenarios can obviously change, as input from the research
group is received. For example, this revision adds scenarios
stemming from recent work exploring "Network Interaction" in ICN.
Furthermore, a first draft outline for an ICN evaluation methodology
is introduced in Section 3.
2 Toward ICN Baseline Scenarios
This section presents a number of scenarios grouped into several
categories. Note that certain evaluation scenarios span across these
categories, so the boundaries between them should not be considered
rigid and inflexible. The goal is that each scenario should be
described at a sufficient level of detail so that it can serve as the
base for comparative evaluations of different approaches. This will
need to include reference configurations, topologies, specifications
of traffic mixes and traffic loads. These specifications (or
configurations) should preferably come as sets that describe extremes
as well as "typical" usage scenarios.
2.1 Social Networking
Social networking applications proliferated over the past decade
based on overlay content dissemination systems that require large
infrastructure investments to rollout and maintain. Content
dissemination is at the heart of the ICN paradigm and, therefore, we
would expect that they are a "natural fit" for showcasing the
superiority of ICN over traditional client-server TCP/IP-based
systems.
Mathieu et al. [ICN-SN], for instance, illustrate how an Internet
Service Provider (ISP) can capitalize on CCN to deploy a short-
message service akin to Twitter at a fraction of the complexity of
today's systems. Their key observation is that such a service can be
seen as a combination of multicast delivery and caching. That is, a
single user addresses a large number of recipients, some of which
receive the new message immediately as they are online at that
instant, while others receive the message whenever they connect to
the network.
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Along similar lines, Kim et al. [VPC] present an ICN-based social
networking platform in which a user shares content with her/his
family and friends without the need for centralized content server;
see also section 2.4, below, and [CBIS]. Based on the CCN naming
scheme, [VPC] takes a user name to represent a set of devices that
belong to the person. Other users in this in-network, serverless
social sharing scenario can access the user's content not via a
device name/address but with the user's name. In [VPC], signature
verification does not require any centralized authentication server.
Kim and Lee [VPC2] present a proof-of-concept evaluation in which
users with ordinary smartphones can browse a list of members or
content using a name, and download the content selected from the
list.
In short, in both evaluations there is no need for a classic client-
server architecture (let alone a cloud-based infrastructure) to
intermediate between content providers and consumers in a hub-and-
spoke fashion.
Earlier work by Arianfar et al. [CCR] considers a similar pull-based
content retrieval scenario using a different architecture, pointing
to significant performance advantages. Although the authors consider
a network topology (redrawn in Fig. 1 for convenience) that has
certain interesting characteristics, they do not explicitly address
social networking in their evaluation scenario. Nonetheless,
similarities are easy to spot: "followers" (such as C0, C1, ..., and
Cz in Fig. 1) obtain content put "on the network" (I1, ..., Im, and
B1, B2) by a single user (e.g. Px) relying solely on network
primitives.
\--/
|C0|
/--\ +--+ +--+ +--+ +--+
*=== |I0| === |I1| ... |In| |P0|
\--/ +--+ +--+ +--+ +--+
|C1| \ / o
/--\ +--+ +--+ o
o |B1| === |B2| o
o o o o o +--+ +--+ o
o / \ o
o +--+ +--+ +--+ +--+
o *=== |Ik| === |Il| ... |Im| |Px|
\--/ +--+ +--+ +--+ +--+
|Cz|
/--\
Figure 1. Dumbbell with linear daisy chains
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The social networking scenario aims to exercise each ICN architecture
in terms of network efficiency, multicast support, caching
performance and its reliance on centralized mechanisms (or lack
thereof).
2.2 Real-time A/V Communications
Real-time audio and video (A/V) communications include an array of
services ranging from one-to-one voice calls to multi-party multi-
media conferences with video and whiteboard support to augmented
reality. Real-time communications have been studied and deployed in
the context of packet- and circuit-switched networks for decades.
The stringent quality of service requirements that this type of
communication imposes on network infrastructure is well-known. Some
could argue that network primitives which are excellent for
information dissemination are not well-suited for conversational
services.
Notably, Jacobson et al. [VoCCN] presented an early evaluation where
the performance of a VoIP call over an information-centric approach
was compared with that of an off-the-shelf VoIP implementation using
RTP/UTP. The results indicated that despite the extra cost of adding
security support in the former case, performance was virtually
identical in the two cases evaluated in a testbed. However, the
experimental setup presented is quite rudimentary and the evaluation
considered a single voice call only. This scenario does illustrate
that quality telephony services are feasible with at least one ICN
approach, but it would need to be further enhanced to include more
comprehensive metrics as well as standardized call arrival patterns,
for example, following well-established methodologies from the
quality of service/experience (QoS/QoE) evaluation toolbox.
Given the wide-spread deployment of real-time A/V communications, an
ICN approach should demonstrate more than feasibility. For example,
with respect to multimedia conferencing, Zhu et al. [ACT] describe
the design of a distributed audio conference tool based on NDN. The
design includes ICN-based conference discovery, speakers discovery
and voice data distribution. The reported evaluation results point
to gains in scalability and security. Moreover, Chen et al. [G-
COPSS] explore the feasibility of implementing a Massively
Multiplayer Online Role Playing Game (MMORPG) based on CCNx and show
that stringent temporal requirements can be met while scalability is
significantly improved when compared to an IP client-server system.
This type of work points to benefits both in the data path and the
control path of a modern network infrastructure.
All in all, however, the ICN research community has hitherto only
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scratched the surface of this area with respect to illustrating the
benefits of adopting an information-centric approach as opposed to a
host-centric one. Arguably, more work is needed in this direction.
In short, scenarios in this category should illustrate not only
feasibility but reduced complexity, increased scalability,
reliability, and capacity to meet stringent QoS/QoE requirements when
compared to established host-centric solutions.
2.3 Mobile Networking
IP mobility management relies on mobility anchors to provide
ubiquitous connectivity to end-hosts as well as moving networks.
This is a natural choice for a host-centric paradigm that requires
end-to-end connectivity and continuous network presence [SCES]. An
implicit assumption in host-centric mobility management frameworks is
that the mobile node aims at connecting to a particular peer, not at
retrieving information [EEMN]. However, with ICN new ideas about
mobility management should come to the forefront, which capitalize on
the different nature of the paradigm.
For example, Dannewitz et al. [N-Scen], consider a scenario where a
multiaccess end-host can retrieve email securely using a combination
of cellular and wireless local area network (WLAN) connectivity.
This scenario borrows elements from previous work, e.g. [DTI], and
develops them further with respect to multiaccess. Unfortunately,
Dannewitz et al. [N-Scen] do not present any results demonstrating
that an ICN approach is indeed better. That said, the scenario is
interesting as it considers content specific to a single user (i.e.
her mailbox) and does point to reduced complexity. It is also
compatible with recent work in the Distributed Mobility Management
(DMM) Working Group within the IETF. Finally, Xylomenos et al.
[PSIMob] as well as [EEMN] argue that an information-centric
architecture can avoid the complexity of having to manage tunnels to
maintain end-to-end connectivity as is the case with mobile anchor-
based protocols such as Mobile IP (and its variants).
Overall, mobile networking scenarios have not been developed in
detail, let alone evaluated in a wide scale. We expect that in the
coming period more papers will address this topic, each perhaps
proposing its own evaluation scenario. Earlier work [mNetInf] argues
that for mobile and multiaccess networking scenarios we need go
beyond the current mobility management mechanisms in order to
capitalize on the core ICN features. They present a testbed setup
(redrawn in Fig. 2) which can serve as the basis for other ICN
evaluations. Lindgren [HybICN] explores this scenario further using
simulation for an urban setting and reports sizable gains in terms of
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reduction of object retrieval times and core network capacity use.
One would expect that mobile networking scenarios will be naturally
coupled with those discussed in the previous sections, as more users
access social networking and multimedia applications through mobile
devices. Further, the constraints of real-time A/V applications
create interesting challenges handling mobility, particularly in
terms of maintaining service continuity.
+-----------+ +-----------+
| Network 0 | | Network C |
| | | |
| +--+ | ==== | +--+ |
| |I2| | | |P1| |
| +--+ | | +--+ |
| \--/ | | |
+-----|C0|--+ | |
| /--\ | | |
| +--+ | | |
| |I3| | | +--+ |
| +--+ | ==== | |P2| |
| | | +--+ |
| Network 1 | | |
+-----------+ +-----------+
Figure 2. Overlapping wireless multiaccess
Mobile networking scenarios should aim to exercise service continuity
for those applications that require it, decrease complexity and
control signaling for the network infrastructure, as well as increase
wireless capacity utilization by taking advantage of the broadcast
nature of the medium.
2.4 Infrastructure Sharing
A key idea in ICN is that the network should secure information
objects per se, not the communications channel that they are
delivered over. This means that hosts attached to an information-
centric network can share resources on an unprecedented scale,
especially when compared to what is possible in an IP network. All
devices with network access and storage capacity can contribute their
resources increasing the value of an information-centric network
(perhaps) much faster than Metcalfe's law.
For example, Jacobson et al. [CBIS] argue that in ICN the "where and
how" to obtain information are new degrees of freedom. They
illustrate this with a scenario involving a photo sharing application
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which takes advantage of whichever access network connectivity is
available at the moment (WLAN, Bluetooth, and even SMS) without
requiring a centralized infrastructure to synchronize between
numerous devices. It is important to highlight that since the focus
of the communication changes, keep-alives in this scenario are simply
unnecessary, as devices participating in the testbed network
contribute resources in order to maintain user content consistency,
not link state information as is the case in the host-centric
paradigm. This means that the notion of "infrastructure" may be
completely different in the future.
Carofiglio et al., for instance, present early work on an analytical
framework that attempts to capture the storage/bandwidth tradeoffs
that ICN enables and can be used as foundation for a network planning
tool [SHARE]. In addition, Chai et al. [CL4M] explore the benefits
of ubiquitous caching throughout an information-centric network and
argue that "caching less can actually achieve more." These two
papers indicate that there is a lot of work to be done in the area of
how to use optimally all resources available to an information-
centric network.
Scenarios in this category, therefore, would cover the
communication/computation/storage tradeoffs that an ICN deployment
must consider, including network planning, perhaps capitalizing on
user-provided resources, as well as operational and economical
aspects to illustrate the superiority of ICN over other approaches,
including federations of IP-based Content Distribution Networks
(CDNs).
2.5 Content Dissemination
Content dissemination has attracted more attention than other aspects
of ICN, perhaps due to a misunderstanding of what the first "C" in
CCN stands for. Decentralized content dissemination with on-the-fly
aggregation of information sources was envisaged in [N-Scen] where
information objects can be dynamically assembled based on
hierarchically structured subcomponents. For example, a video stream
could be associated with different audio streams and subtitle sets,
which can all be obtained from different sources. Using the topology
depicted in Fig. 1 as an example, an application at C1 may end up
obtaining, say, the video content from I1, but the user-selected
subtitles from Px. Semantics and content negotiation, on behalf of
the user, were also considered, e.g. for the case of popular tunes
which may be available in different encoding formats. Effectively
this scenario has the information consumer issuing independent
requests for content based on information identifiers, and stitching
the pieces together irrespective of "where" or "how" they were
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obtained.
A case in point for content dissemination are vehicular ad-hoc
networks (VANETs), as an ICN approach may address their needs for
information dissemination between vehicles better than today's
solutions. VANETs, by nature, are characterized by intermittent
connectivity, mobility, and the possibility to combine information
from different sources as each vehicle does not care about "who"
originated the named data objects. Typical applications include road
safety data and infotainment. For example, Bai and Krishnamachari
[EWC] take advantage of the localized and dynamic nature of a VANET
to explore how a road congestion notification application can be
implemented. Wang et al. [DMND] consider data collection where Road-
Site Units (RSUs) collect information from vehicles by broadcasting
NDN-like INTEREST packets. The proposed architecture is evaluated
using simulation in a grid topology, and is compared against a host-
centric alternative based on Mobile IP indicating high efficiency
even at high speeds.
Fig. 2 could apply to VANET scenarios where C0 represents a vehicle
which can obtain named information objects via multiple wireless
peers and/or RSUs (I2 and I3 in the figure). Recently, Amadeo et al.
[CRoWN] used a Manhattan grid in their evaluation of an ICN framework
for VANETs on top of IEEE 802.11p. The critical part of information
dissemination in a VANET scenario revolves around "where" and "when".
For instance, one may be interested in traffic conditions 2 km ahead
while having no interest in similar information about the area around
the path origin. We argue that, due to the short sojourn time
between a vehicle and the RSU and the short time of sustained
connectivity between vehicles, VANET scenarios may provide fertile
ground for showcasing the ICN advantage with respect to content
dissemination especially when compared with current host-centric
approaches. That said, information integrity and filtering are
challenges that must be addressed.
Content dissemination scenarios, in general, have a large overlap
with the scenarios described in the previous sections and are
explored in several papers, such as [DONA] [PSI] [PSIMob] [NetInf]
[CCN] [CBIS] [CCR], just to name a few. In addition, Chai et al.
present a hop-by-hop hierarchical content resolution approach
[CURLING], which employs receiver-driven multicast over multiple
domains, advocating another content dissemination approach.
Scenarios in this category abound in the literature, including stored
and streaming A/V distribution, file distribution, mirroring and bulk
transfers, SVN-type of services, as well as traffic aggregation. We
expect that in particular for content dissemination both extreme as
well as typical scenarios can be specified drawing data from current
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CDN deployments.
2.6 Network Interaction
As ICN shifts the focus from nodes to information objects, the
interaction between networks evolves to capitalize on data location
independence, efficient and scalable in-network named object
availability and multi-access functionality. These interactions
become critical in evaluating the technical and economic impact of
ICN architecture choices, as noted in [ArgICN]. Additional
challenges are presented by the emergence of new types of networks,
such as Small Cell Networks (SCN), Heterogeneous Networks (HetNet),
virtual and overlay networks. Beyond simply adding diversity in
deployment options, these networks have the potential to alter the
incentives among existing, and future, we may add, network players,
as noted in [EconICN].
Moreover, such networks enable more numerous inter-network
relationships where exchange of information may be conditioned on a
set of multilateral policies. For example, shared SCNs are emerging
as a cost-effective way to address coverage of complex environments
such as sports stadiums, large office buildings, malls, etc. [OptSC]
[FEMTO]. Such networks are likely to be a complex mix of different
cellular and WLAN access technologies (such as HSPA, LTE, and Wi-Fi)
as well as ownership models. It is reasonable to assume that access
to content generated in such networks may depend on contextual
information such as the subscription type, timing, and location of
both the owner and requestor of the content. The availability of
such contextual information across diverse networks can lead to
network inefficiencies and data management issues that can benefit
from an information-centric approach.
Jacobson et al. [CCN] include interactions between networks in their
overall system design, and mention both "an edge-driven, bottom-up
incentive structure" and techniques based on evolutions of existing
mechanisms both for ICN router discovery by the end-user and for
interconnecting between autonomous systems (AS). For example, a BGP
extension for domain-level content prefix advertisement can be used
to enable efficient interconnection between AS's. Liu et al. [MLDHT]
proposed to address the "suffix-hole" issue found in prefix-based
name aggregation through the use of a combination of bloom-filter
based aggregation and multi-level DHT.
Name aggregation has been discussed for a flat naming design as well
in [NCOA], which also notes that based on estimations in [DONA] flat
naming may not require aggregation. This is a point that calls for
further study. Scenarios evaluating name aggregation, or lack
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thereof, should take into account the amount of state (e.g. size of
routing tables) maintained in edge routers as well as network
efficiency (e.g. amount of traffic generated).
DiBenedetto et al. [RP-NDN] study policy knobs made available by NDN
to network operators. New policies, which are not feasible in the
current Internet are described, including a "cache sharing peers"
policy, where two peers have an incentive to share content cached in,
but not originating from, their respective network. The simple
example used in the investigation considers several networks and
associated transit costs, as shown in Fig. 3. (based on Fig. 1 of
[RP-NDN]). Agyapong and Sirbu [EconICN] further establish that ICN
approaches should incorporate features that foster (new) business
relationships. For example, publishers should be able to indicate
their willingness to partake in the caching market, proper reporting
should be enabled to avoid fraud, and content should be made
cacheable as much as possible to increase cache hit ratios.
+---------------+
+---------->| Popular Video |
| +---------------+
| ^ ^
| | |
| +-+-+ $0/MB +-+-+
| | A +-------+ B |
| ++--+ +-+-+
| | ^ ^ |
| $8/MB | | | | $10/MB
| v | | v
+-+-+ $0/MB +--+---------+--+
| D +---------+ C |
+---+ +---------------+
Figure 3. Relationships and transit costs between networks A to D
Ahlgren et al. [SAIL-B3] enable network interactions in the NetInf
architecture using a name resolution service at domain edge routers,
and a BGP-like routing system in the NetInf Default Free Zone.
Business models and incentives are studied in [SAIL-A7] and [SAIL-
A8], including scenarios where the access network provider (or a
virtual CDN) guarantees QoS to end users using ICN. Fig. 4
illustrates a typical scenario topology from this work which involves
an interconnectivity provider.
Jokela et al. [LIPSIN] propose a two-layer approach where additional
rendezvous systems and topology formation functions are placed
logically above multiple networks and enable advertising and routing
content between them. Visala et al. [LANES] further describe an ICN
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architecture based on similar principles; notably, it relies on a
hierarchical DHT-based rendezvous interconnect. Rajahalme et al.
[PSIRP1] describe a rendezvous system using both a BGP-like routing
protocol at the edge and a DHT-based overlay at the core. Their
evaluation model is centered around policy-compliant path stretch,
latency introduced by overlay routing, caching efficacy, and overlay
routing node load distribution.
+----------+ +-----------------+ +------+
| Content | | Access Network/ | | End |
| Provider +---->| ICN Provider +---->| User |
+----------+ +-+-------------+-+ +------+
| |
| |
v v
+-------------------+ +----------------+ +------+
| Interconnectivity | | Access Network | | End |
| Provider +---->| Provider +------>| User |
+-------------------+ +----------------+ +------+
Figure 4. Setup and operating costs of network entities
Rajahalme et al. [ICCP] point out that ICN architectural changes may
conflict with the current tier-based peering model. For example,
changes leading to shorter paths between ISPs are likely to meet
resistance from Tier-1 ISPs. Rajahalme [IDMcast] shows how
incentives can help shape the design of specific ICN aspects, and in
[IDArch] he presents a modeling approach to exploit these incentives,
which includes a network model describing the relationship between AS
based on data inferred from the current Internet, a traffic model
taking into account business factors for each AS, and a routing model
integrating the valley-free model and policy-compliance. A typical
scenario topology is illustrated in Fig. 5, redrawn here based on
Fig. 1 of [ICCP]. Note that it relates well with the topology
illustrated in Fig. 1 of this document.
The evaluation of ICN architectures across multiple network types
should include a combination of technical and economic aspects.
These scenarios aim to illustrate scalability, efficiency and
manageability, as well as traditional and novel network policies.
Moreover, scenarios in this category should specifically address how
different actors have proper incentives, not only in a pure ICN
realm, but also during the migration phase towards this final state.
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+-----+
------+ J +------
| +--+--+ |
| * |
+--+--+ * +--+--+
| H +-----------+ I |
**+-----+ ** * ** +-----+***
* * * * *
* * * * *
+--+--+ ++-+-++ +--+--+
| E +--------+ F +---------+ G +
**+-----+*** +-----+ **+-----+**
* * * *
* * * *
+--+--+ +--+--+ +--+--+ +--+--+
| A | | B +-----------+ C | | D |
+-----+ +--+--+ +--+--+ +----++
| | ^^ | route
data | data | data || | to
v v || v data
+----+ +----+ +++--+
|User| |User| |Data|
+----+ +----+ +----+
Legend:
+***+ Transit link
+---+ Peering link
+---> Data delivery or route to data
Figure 5. Tier-based set of interconnections between AS A to J
2.7 Energy Efficiency
As mentioned earlier, energy efficiency can be tackled by different
ICN approaches in ways that it cannot in a host-centric paradigm. We
already mentioned that in ICN perpetual connectivity is not
necessary, therefore mechanisms that capitalize on powering down
network interfaces are easier to accommodate. For example, the work
by Guan et al. [EECCN] indicates that CCN may be much more energy-
efficient than traditional CDNs for delivering popular content given
the current networking equipment energy consumption levels.
Evaluating energy efficiency does not require the definition of new
scenarios, but does require the establishment of clear guidelines so
that different ICN approaches can be compared not only in terms of
scalability, for example, but also in terms to power consumption.
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2.8 Delay and Disruption Tolerance
Delay- and Disruption-Tolerant Networking (DTN) [DTN] [DTNICN]
originated as a means to extend the Internet to interplanetary
communications. However, it was subsequently found to be an
appropriate architecture for many terrestrial situations as well.
Typically, this was where delays were greater than protocols such as
TCP could handle, and where disruptions to communications were the
norm rather than occasional annoyances. DTN has now been applied to
many situations, including opportunistic content sharing, handling
infrastructural issues during emergency situations (e.g. earthquakes)
and providing connectivity to remote rural areas without existing
Internet provision and little or no communications or power
infrastructure.
The DTN architecture [RFC4838] is based on a "store, carry and
forward" paradigm that has been applied extensively to situations
where data is carried between network nodes by a "data mule", which
carries bundles of data stored in some convenient storage medium
(e.g., a USB memory stick). With the advent of sensor and peer-to-
peer (P2P) networks between mobile nodes, DTN is becoming a more
commonplace type of networking than originally envisioned. Since ICN
also does not rely on the familiar end-to-end communications
paradigm, there are, thus, clear synergies [DTN]. First, both
approaches rely on in-network storage. Second, both approaches
espouse late binding of names to locations and, third, both
approaches treat data as a long-term component that can exist in the
network for extended periods of time.
Through these similarities, it becomes possible to identify many DTN
principles already in existence within ICN architectures. For
example, ICN nodes will often retain publications locally, making
them accessible later on, much like DTN bundles do. Consequently,
these synergies suggest strong potential for marrying the two
technologies. This, for instance, could include building new
integrated Information-Centric Delay Tolerant Network (ICDTN)
protocols or, alternatively, building ICN schemes over existing DTN
protocols (or vice versa).
The above similarities suggest that integration of the two principles
would be certainly feasible. Beyond this, there are also a number of
direct benefits identifiable. Through caching and replication, ICN
offers strong information resilience, whilst, through store-and-
forward, DTN offers strong connectivity resilience. As such, both
architectures could benefit greatly from each other. Initial steps
have already been taken in the DTN community to integrate ICN
principles, e.g. the Bundle Protocol Query Block [BPQ]. Whilst,
similarly, initial steps have been taken in the ICN community too,
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such as [SLINKY].
A key baseline scenario in this context is opportunistic content
sharing. This occurs when mobile nodes create opportunistic links
between each other to share content of interest. For example, this
might occur on an underground train, in which people pass news items
between their mobile phones. Equally, content generated on the
phones (e.g. tweets [TWIMIGHT]) could be stored for later forwarding
(or even forwarded amongst interested passengers on the train).
Another key example of what is essentially the same scenario is use
in emergency and disaster situations where the local infrastructure
has either been destroyed or is otherwise inaccessible to first
responders. Being able to exchange and cache information without the
need for any installed infrastructure could greatly improve the
effectiveness of emergency responders. These kind of scenarios bode
well with those introduced earlier in Section 2.4 about (re)defining
what "infrastructure" may mean in practice in an information-centric
network.
Especially in the context of the scenarios discussed above, it is of
clear interest to evaluate different ICN approaches with respect both
to their delay- and disruption-tolerance, i.e., how effective is the
approach when used in a delay tolerant network situation; and to
their active support for operations in a DTN environment. Important
aspects to be evaluated in support of this application include, but
are not limited to, name resolution, routing and forwarding in
disconnected parts of the network; support for unidirectional links;
number of round trips needed to complete a data transfer; efficiency
in the face of disruption, and so on.
To assist in this evaluation, within the DTN community, a number of
important contact traces have emerged as de-facto evaluative tools.
They include Haggle's INFOCOM traces and MIT's Reality Mining.
Typically, these are used with the Opportunistic Network Environment
(ONE) simulator [ONE] to evaluate the above types of metrics. Based
on this, and with proper extensions, a strong platform for evaluating
the delay and disruption tolerance properties of different ICN
approaches could be developed.
2.9 Internet of Things
Advances in electronics miniaturization combined with low-power
wireless access technologies (e.g., ZigBee, NFC, Bluetooth and
others) have enabled the coupling of interconnected digital services
with everyday objects. As devices with sensors and actuators connect
into the network, they become "smart objects" and form the foundation
for the so-called Internet of Things (IoT). IoT is expected to
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increase significantly the amount of content carried by the network
due to machine-to-machine (M2M) communication as well as novel user
interaction possibilities.
Yet, the full potential of IoT does not lie on simple remote access
to smart object data. Instead, it is the intersection of Internet
services with the physical world that will bring about the most
dramatic changes. Burke [IoTEx], for instance, makes a very good
case for creating everyday experiences using interconnected things
through participatory sensing applications. In this case, inherent
ICN capabilities for data discovery, caching, and trusted
communication are leveraged to obtain sensor information and enable
content exchange between mobile users, repositories, and
applications.
Kutscher and Farrell [IWMT] discuss the benefits that ICN can provide
in these environments in terms of naming, caching, and optimized
transport. The Named Identifier scheme (ni) [NI] could be used for
globally unique smart object identification, although an actual
implementation report is not currently available. Access to
information generated by smart objects can be of varied nature and
often vital for the correct operation of large systems. As such,
supporting timestamping, security, scalability, and flexibility need
to be taken into account.
Ghodsi et al. [NCOA] examine hierarchical and self-certifying naming
schemes and point out that ensuring reliable and secure content
naming and retrieval may pose stringent requirements (e.g., necessity
for employing PKI), which can be too demanding for low-powered nodes,
such as sensors. That said, earlier work by Heidemann et al. [nWSN]
shows that, for dense sensor network deployments, disassociating
sensor naming from network topology and using named content at the
lowest level of communication in combination with in-network
processing of sensor data is feasible in practice and can be more
efficient than employing a host-centric binding between node locator
and the content existing therein.
J. Burke et al. [NDNl] describe the implementation of a lighting
control building automation system where the security, naming and
device discovery NDN mechanisms are leveraged to provide
configuration, installation and management of residential and
industrial lighting control systems. The goal is an inherently
resilient system, where even smartphones can be used for control.
Naming reflects fixtures with evolved identification and node
reaching capabilities thus simplifying bootstrapping, discovery, and
user interaction with nodes. The authors report that this ICN-based
system requires less maintenance and troubleshooting than typical IP-
based alternatives.
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IoT exposes ICN concepts to a stringent set of requirements which are
exacerbated by the amount of nodes, as well as by the type and volume
of information that must be handled. A way to address this is
[IoTScope], which tackles the problem of mapping named information to
an object, diverting from the currently typical centralized discovery
services and leveraging the intrinsic ICN scalability capabilities
for naming. It extends the base [PURSUIT] design with
hierarchically-based scopes, facilitating lookup, access, and
modifications of only the part of the object information that the
user is interested in. Another important aspect is how to
efficiently address resolution and location of the information
objects, particularly when large numbers of nodes are connected, as
in IoT deployments. In [ICN-DHT], Katsaros et al. propose a
Distributed Hash Table (DHT) which is compared with DONA [DONA].
Their results show how topological routing information has a positive
impact on resolution, at the expense of memory and processing
overhead.
ICN approaches, therefore, should be evaluated with respect to their
capacity to handle the content produced and consumed by extremely
large numbers of diverse devices. IoT scenarios aim to exercise ICN
deployment from different aspects, including ICN node design
requirements, scalability, efficient naming, transport, and caching
of time-restricted data.
2.10 Smart City
The rapid increase in urbanization sets the stage for the most
compelling and challenging environments for networking. By 2050 the
global population will reach nine billion people, 75% of which will
dwell in urban areas. In order to cope with this influx, many cities
around the world started their transformation toward the Smart City
vision. Smart cities will be based on the following innovation axes:
smart mobility, smart environment, smart people, smart living, and
smart governance. In development terms, the core goal of a smart
city is to become a business-competitive and attractive environment,
while serving citizen well being [CPG].
In a smart city, ICT plays a leading role and acts as the glue
bringing together all actors, services, resources (and their
interrelationships), that the urban environment is willing to host
and provide [MVM]. ICN appears particularly suitable for these
scenarios. Domains of interest include intelligent transportation
systems, health care, A/V communications, peer-to-peer and
collaborative platforms for citizens, social inclusion, active
participation in public life, e-government, safety and security,
sensor networks, and IoT.
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Nevertheless, the road to build a real information-centric digital
ecosystem will be long and more coordinated effort is required to
drive innovation in this domain. We argue that smart city needs and
ICN technologies can trigger a virtuous innovation cycle toward
future ICT platforms. Recent concrete ICN-based contributions have
been formulated for home energy management [iHEMS], geo-localized
services [ACC], smart city services [IB], and traffic information
dissemination in vehicular scenarios [WAK]. Some of the proposed
ICN-based solutions are implemented in real testbeds while others are
evaluated through simulation.
Zhang et al. [iHEMS] propose a secure publish-subscribe architecture
for handling the communication requirements of Home Energy Management
Systems (HEMS). The objective is to safely and effectively collect
measurement and status information from household elements, aggregate
and analyze the data, and ultimately enable intelligent control
decisions for actuation. They consider a simple experimental test-
bed for their proof-of-concept evaluation, exploiting open source
code for the ICN implementation, and emulating some node
functionality in order to facilitate system operation.
A different scenario is considered in [ACC], where DHTs are employed
for distributed, scalable, and geographically-aware service lookup in
a smart city. Also in this case, the ICN application is validated by
considering a small-scale testbed: a small number of nodes are
realized with simple embedded PCs or specific hardware boards (e.g.,
for some sensor nodes); other nodes realizing the network connecting
the principal actors of the tests are emulated with workstations.
The proposal in [IB] draws from a smart city scenario (mainly
oriented towards waste collection management) comprising sensors and
moving vehicles, as well as a cloud computing system that supports
data retrieval and storage operations. The main aspects of this
proposal are analyzed via simulation using open source code which is
publicly available. Some software applications are designed on real
systems (e.g., PCs and smartphones). Finally, Wang et al. [WAK]
discuss the adoption of named data networking in vehicular (V2V)
communication systems. They validate their work using simulation
based on a freely available network simulator but consider rather
simple traffic patterns.
Smart city scenarios aim to exercise several ICN aspects in an urban
environment. In particular, they can be useful to (i) analyze the
capacity of using ICN for managing extremely large data sets; (ii)
study ICN performance in terms of scalability in distributed
services; (iii) verify the feasibility of ICN in a very complex
application like vehicular communication systems; and (iv) examine
the possible drawbacks related to privacy and security issues in
complex networked environments.
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3 Evaluation Methodology
As we have seen in the previous section, different ICN approaches
have already been evaluated in the peer-reviewed literature using a
mixture of theoretical analysis, simulation studies, and empirical
(testbed) measurements. These are all popular techniques for
evaluating network protocols, architectures, and services in the
networking community. Typically, researchers follow a specific
methodology based on the goal of their experiment, e.g. whether they
want to evaluate scalability, quantify resource utilization, analyze
economic incentives, and so on, as we have discussed earlier. In
addition, though, we often observe that ease and convenience of
setting up and running experiments can sometimes be a factor in
published evaluations.
It is worth pointing out that for well-established protocols, such as
TCP, for example, performance evaluation using actual network
deployments has the benefit of realistic workloads and reflects the
environment where the service or protocol will be deployed. However,
sometimes results obtained in this environment are often difficult to
replicate independently. Moreover, for ICN in particular, it is not
yet clear what qualifies as a "realistic workload". Trace-based
analysis of ICN is at its infancy, and more work is needed towards
defining characteristic workloads for ICN evaluation studies.
This document recommends that attention must be paid while choosing
the evaluation methodology as well as the experimental setup process.
Numerous factors affect experimental results, including, for
instance, the topology selected, the background traffic that an
application is being subjected to, the available bandwidth, the link
delay and loss-rate characteristics throughout the selected topology,
the node mobility patterns, as well as practical aspects such as the
diversity of devices used, and so on, as we explain in the remainder
of this section.
3.1 ICN Simulators and Testbeds
Since ICN is still an emerging area the community is still in the
process of developing effective evaluation environments, including
simulators emulators, and testbeds. To date, none of the available
simulators can be seen as the one and only reference evaluation tool.
Furthermore, no single environment supports all well known ICN
approaches. Simulators and emulators should be able to capture
faithfully all features and operations of the respective ICN
architecture(s). It is also essential that these tools and
environments come with adequate logging facilities so that one can
use them for in-depth analysis as well as debugging. Additional
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requirements include the ability to support mid- to large-scale
experiments, the ability to quickly and correctly set various
configurations and parameters, as well as to support the playback of
traffic traces captured on a real testbed or network.
The rest of this subsection summarizes the ICN simulators and
testbeds currently available to the community.
3.1.1 CCN and NDN
ndnSIM is a module that can be plugged into the ns-3 simulator and
supports the core features of CCN. One can use ndnSIM to experiment
with various CCN applications and services as well as components
developed for CCN such as routing protocols, caching and forwarding
strategies. The code for ns-3 and ndnSIM is openly available to the
community and can be used as the basis for implementing ICN protocols
or applications. For more details interested readers should consult
http://www.nsnam.org and http://ndnsim.net.
ccnSim [ccnSim] is another CCN-specific simulator that was specially
designed to handle forwarding of a large number of CCN-chunks.
ccnSim is written in C++ for the OMNeT++ simulation framework; see
http://www.omnetpp.org for more details. Finally, a packet level
simulator for CCN is the Content Centric Networking Packet Level
Simulator [CCNPL].
An example of a testbed that supports CCN is the Open Network Lab
(see https://onl.wustl.edu/). The ONL testbed currently comprises 18
extensible gigabit routers and over a 100 computers representing
clients and is freely available to the public for running CCN
experiments. Nodes in ONL are preloaded with CCNx software. ONL
provides a graphical user interface for easy configuration and
testbed set up as per the experiment requirements, and also serves as
a control mechanism, allowing access to various control variables and
traffic counters. It is also possible to run and evaluate CCN over
popular testbeds such as PlanetLab (http://www.planet-lab.org/) and
Deter (http://www.isi.deterlab.net) by directly running the CCNx
open-source code on PlanetLab and Deter nodes, respectively.
3.1.2 Publish/Subscribe Internet Architecture
The PSIRP project has open-sourced its Blackhawk publish-subscribe
(Pub/Sub) implementation for FreeBSD; more details are available
online at http://www.psirp.org/downloads.html. Despite the
limitation to one operating system, it also provides a virtual image
to allow its deployment into other environments through
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virtualization. The code distribution features a kernel module, a
file system and scope daemon, as well as a set of tools and test
applications and scripts.
3.1.3 NetInf
The EU FP7 4WARD and SAIL projects have made a set of open-source
implementations available; see http://www.netinf.org/open-source for
more details. Of note, two software packages are available. The
first one is a set of tools for NetInf implementing different aspects
of the protocol (e.g., NetInf URI format, HTTP and UDP convergence
layer) using different programming languages. The Java
implementation is a very rich one, providing as well a local caching
proxy and client. The second one, is a OpenNetInf prototype from the
4WARD project. Besides a rich set of NetInf mechanisms implemented,
it also provides a browser plug in and video streaming software.
3.2 Topology Selection
Section 2 introduced several topologies that have been used in ICN
studies so far but, to date and to the best of our understanding,
there is no single topology that can can be used to easily evaluate
all aspects of the ICN paradigm. There is rough consensus that the
classic dumbbell topology cannot serve well future evaluations of ICN
approaches. Therefore, one should consider a range of topologies,
each of which would stress different aspects, as outlined earlier in
this document.
Besides defining the evaluation topology as a graph G = (V,E) where V
is the set of vertices (nodes) and E is the set of edges (links), one
should also clearly define and list the respective matrices that
correspond to the network, storage and computation capacities
available at each node as well as the delay characteristics of each
link, so that the results obtained can be easily replicated in other
studies. Recent work by Hussain and Chen [Montage], although
currently addressing host-centric networks, could also be leveraged
and be extended by the ICN community.
Finally, the topology dynamic aspects, such as node and content
mobility, packet loss rates as well as link and node failure rates,
to name a few, should also be carefully considered. As mentioned in
subsection 2.8, for example, contact traces from the DTN community
could also be used in ICN evaluations.
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3.3 Traffic Load
As we are still missing ICN-specific traffic workloads we can
currently only extrapolate from today's workloads. In this
subsection we provide a first draft of a set of common guidelines, in
the form of what we will refer to as a content catalog for different
scenarios. This catalog, which is based on previously published
work, could be used to evaluate different ICN proposals, for example,
on routing, congestion control, and performance, and can be
considered as other kinds of ICN contributions emerge.
We take scenarios from today's Web, file sharing (BitTorrent-like)
and User Generated Content (UGC) platforms (e.g., YouTube), as well
as Video on Demand (VoD) services. The content catalog for each
traffic is characterized by a specific set of parameters: the
cardinality of the estimated content catalog, the average size of the
exchanged contents (either chunks or entire named information
objects), and the statistical distribution that best reflect the
popularity of objects and their request frequency. Table I
summarizes the content catalog. With this shared point of reference,
the use of the same set of parameters (depending on the scenario of
interest) among researchers will be eased, and different proposals
could be compared on a common base.
Table I. Content catalog
Traffic | Catalog | Mean Object Size | Popularity Distribution
Load | Size | [L4][L5][L7][L8] | [L3][L5][L6][L11][L12]
| [L1][L2]| [L9][L10] |
| [L3][L5]| |
====================================================================
Web | 10^12 | Chunk: 1-10 kB | Zipf, 0.64 <= alpha <= 0.83
--------------------------------------------------------------------
File | 5x10^6 | Chunk: 250-4096 kB | Zipf, 0.75 <= alpha<= 0.82
sharing | | Object: ~800 MB |
--------------------------------------------------------------------
UGC | 10^8 | Object: ~10 MB | Zipf, alpha >= 2
--------------------------------------------------------------------
VoD | 10^4 | Object: ~100 MB | Zipf, 0.65 <= alpha <= 1
====================================================================
* UGC = User Generated Content ** VoD = Video on Demand
Several studies in the past years have stated that Zipf's law is the
discrete distribution that best represents the request frequency in a
number of application scenarios, ranging from the Web to VoD
services. The key aspect of this distribution is that the frequency
of a content request is inversely proportional to the rank of the
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content itself, i.e., the smaller the rank, the higher the request
frequency. If we denote with M the content catalog cardinality and
with 1 <= i <= M the rank of the i-th most popular content, we can
express the probability of requesting the content with rank "i" as:
P(X=i) = ( 1/i^(alpha) ) / C, with C = SUM(1 / j^(alpha)), alpha > 0
where the sum is obtained considering all values of j, 1 <= j <= M.
3.4 Choosing Relevant Metrics
Depending on the type of evaluation and the focal area of interest,
e.g. name resolution vs. routing efficiency vs. congestion control
and fair sharing of resources vs. QoS for A/V communications, the
metrics that are of prime importance may vary. That said, we should
in general consider two broad categories: traffic-related metrics and
system metrics.
3.4.1 Traffic Metrics
From the ICN application point of view, relevant metrics include
goodput (i.e. the application payload divided by the time needed to
deliver it) and delay, as well as more detailed quality of service
(QoS) and quality of experience (QoE) metrics. Typical QoS/QoE
metrics for A/V applications include Peak Signal to Noise Ratio
(PSNR), R and Mean Opinion Scores (MOS), and others from the
standardized A/V evaluation toolbox.
From the network point of view, relevant metrics include resource
efficiency and control plane overhead, among others.
3.4.2 System Metrics
Overall system metrics that need to be considered include
reliability, scalability, energy efficiency, and delay and
disconnection tolerance. In deployments where ICN is addressing
specific scenarios, system metrics could be derived from current
experience. For example, in IoT scenarios, which were discussed
earlier in subsection 2.9, it is reasonable to consider the current
generation of sensor nodes, sources of information, and even
measurement gateways (e.g., for smart metering at homes) or
smartphones. In this case, ICN operation ought to be evaluated with
respect not only to overall scalability and network efficiency, but
also the impact on the nodes themselves. Karnouskos et al.
[SensReqs] provide a comprehensive set of sensor and IoT-related
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requirements, for example, which include aspects such as resource
utilization, service life-cycle management and device management.
Conversely, ther specific metrics are also risen in such stringent
environments, such as CPU processing requirements, signaling
overhead, and memory allocation for caching procedures. Also, in
nodes acting as gateways, which typically not only act as point of
service to a large number of nodes, but also have to satisfy the
information requests from remote entities, need to consider
scalability-related metrics, such as frequency and processing of
successfully satisfied information requests.
3.5 Resource Equivalence and Tradeoffs
As we have seen above, every ICN network is built from a set of
resources, which include link capacities, different types of memory
structures and repositories used for storing named information
objects and chunks temporarily (i.e. caching) or persistently, as
well as name resolution and other lookup services. Complexity and
processing needs in terms of forwarding decisions, management (e.g.
need for manual configuration, explicit garbage collection, and so
on), and routing (i.e. amount of state needed, need for manual
configuration of routing tables, support for mobility, etc.) set the
stage for a range of engineering tradeoffs.
In order to be able to compare different ICN approaches it would be
beneficial to be able to define equivalence in terms of different
resources which today are considered incomparable. For example,
would provisioning an additional 5 Mb/s link capacity lead to better
performance than adding 100 GB of in-network storage? Within this
context one would consider resource equivalence (and the associated
tradeoffs) for example for cache hit ratios per GB of cache,
forwarding decision times, CPU cycles per forwarding decision, and so
on.
3.6 Technology Evolution Assumptions
TBD
4 Security Considerations
TBD
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5 IANA Considerations
This document presents no IANA considerations.
6 Acknowledgments
This document has benefited from comments and proposed text provided
by the following members of the IRTF Information-Centric Networking
Research Group (ICNRG):
Section 2.1: Myeong-Wuk Jang (Samsung).
Section 2.5: Ren Jing (University of Electronic Science and
Technology of China), Will Liu (Huawei Technologies), and Jianping
Wang (City University of Hong Kong).
Section 2.10: Luigi Alfredo Grieco (Politecnico di Bari).
7 Informative References
[RFC4838] Cerf, V., Burleigh, S., Hooke, A., Torgerson, L., Durst,
R., Scott, K., Fall, K., and H. Weiss, "Delay-Tolerant
Networking Architecture", RFC 4838, April 2007.
[NetInf] Ahlgren, B. et al., "Design considerations for a network
of information", Proc. CoNEXT Re-Arch Workshop. ACM,
2008.
[CCN] Jacobson, V. et al., "Networking Named Content", Proc.
CoNEXT. ACM, 2009.
[PSI] Trossen, D. and G. Parisis, "Designing and realizing an
information-centric internet", IEEE Commun. Mag., vol. 50,
no. 7, July 2012.
[DONA] Koponen, T. et al., "A Data-Oriented (and Beyond) Network
Architecture", Proc. SIGCOMM. ACM, 2007.
[SoA] Ahlgren, B. et al., "A survey of information-centric
networking", IEEE Commun. Mag., vol. 50, no. 7, July 2012.
[ICN-SN] Mathieu, B. et al., "Information-centric networking: a
natural design for social network applications", IEEE
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Authors' Addresses
Kostas Pentikousis (editor)
Huawei Technologies
Carnotstrasse 4
10587 Berlin
Germany
Email: k.pentikousis@huawei.com
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Borje Ohlman
Ericsson Research
S-16480 Stockholm
Sweden
Email: Borje.Ohlman@ericsson.com
Daniel Corujo
Instituto de Telecomunicacoes
Campus Universitario de Santiago
P-3810-193 Aveiro
Portugal
Email: dcorujo@av.it.pt
Gennaro Boggia
Dep. of Electrical and Information Engineering
Politecnico di Bari
Via Orabona 4
70125 Bari
Italy
Email: g.boggia@poliba.it
Gareth Tyson
School and Electronic Engineering and Computer Science
Queen Mary, University of London
United Kingdom
Email: gareth.tyson@eecs.qmul.ac.uk
Elwyn Davies
Trinity College Dublin/Folly Consulting Ltd
Dublin, 2
Ireland
Email: davieseb@scss.tcd.ie
Dorothy Gellert
InterDigital Communications, LLC
781 Third Avenue
King Of Prussia, PA 19406-1409
USA
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Email: dorothy.gellert@interdigital.com
Priya Mahadevan
Palo Alto Research Center
3333 Coyote Hill Rd
Palo Alto, CA 94304
USA
Email: Priya.Mahadevan@parc.com
Pentikousis & Ohlman Expires September 12, 2013 [Page 34]