Analyzing Gateways’ Impact on Caching for Micro CDNs based on CCN

esar Bernardini

and Bruno Crispo

2,3

DPS, University of Innsbruck, A6020, Innsbruck, Austria

DISI, University of Trento, 38123, Povo, Italy

DistriNet, KU Leuven, 3001, Leuven, Belgium

Keywords:

ICN, CCN, Content, Centric, Information, Caching, Cache, Gateways, Single Gateways, Multiple Gateways,

CDN, Catalog.

Abstract:

Content Centric Networking (CCN) is a new architecture for a future Internet. CCN is a clean-state architecture

that targets the distribution of content. As such, content is located at the heart of the architecture and CCN

includes two main features: communication led by names and caches everywhere. Nevertheless, CCN has

been criticized due to the economical cost of replacing every IP router with a CCN router. As such, we assume

that CCN will be used for small content delivery networks –Micro CDNs– located in the ISP facilities: it

has already been shown that with only 100MB of caches in the ISP facilities, the ISP trafﬁc to the Internet

can be reduced by 25%. As a matter of fact, if CCN is deployed as a Micro CDN, gateways must exist to

interconnect the CDN network with the Internet. In this paper, we study the advantages of using multiple

gateways against a single gateway and its impact on the caching features. Our results show that multiple

gateways are beneﬁcial not only because they improve the performance of caches but also because the load of

the network get distributed across several nodes.

1 INTRODUCTION

Today, users largely consume videos over the Inter-

net. Indeed, the overall consumption of video stream-

ing media accounts for 66% of all the Internet traf-

ﬁc (Cisco, 2013). New devices are already pushing

these numbers forward. Smartphones, tablets, game

consoles and Smart TV are all used for streaming

video and by 2017 the number of smart devices will

double. In particular, web-enabled TV will have a

fourfold increase. Mobile video will increase 14-fold

between 2013 and 2018 (Cisco, 2013). Therefore, the

consumption of video streaming is expected to keep

growing.

The trafﬁc is already affecting the ISP capabilities.

In fact, it has a twofold impact on the ISP: economical

and networking aspects. With regards to economical

aspects, today, many content providers provide ser-

vices and access to content that depends on someone

else infrastructure. Clearly, video on demand services

such as YouTube or Vimeo could not be used without

ISP infrastructures. ISPs expect that somebody pays

for the extra trafﬁc generated by these services. In

the one hand, these content providers are not prone to

pay for the dedicated infrastructures that they require.

A clear example is the dispute between Verizon &

AT&T in the USA or the French Free ISP and Google

(http://blog.netﬂix.com/ 2014 / 04 / the - case - against

-isp-tolls.html; http://www.cnet.com/news/france-

orders-internet-provider-to-stop-blocking-google-

ads/). In the other hand, end users are not likely

to pay more to solve this dispute. With regards to

networking technology, Content Delivery Networks

(CDNs) are used today to cope with large bulks

of data being transmitted. CDNs are large storage

network distributed across multiple datacenters,

some of them located at the ISP facilities. Their

goal is to serve content, applications, live-streaming

media from nearby locations. The video on demand

services has skyrocketed and the use of CDN has

become a requirement for correct functioning of

the services. However, every CDN company has

implemented their own architectures and protocols.

As a consequence, content delivery services require

to hire multiple CDNs services which are incom-

patible between them. Furthermore, ISPs can not

link together two similar contents being distributed

through different CDNs. Thus, the construction of

a new architecture targeting the content delivery is

required to alleviate the charge of similar content

being requested to the ISP.

Bernardini, C. and Crispo, B.

Analyzing Gateways’ Impact on Caching for Micro CDNs based on CCN.

DOI: 10.5220/0005946400190026

In Proceedings of the 13th International Joint Conference on e-Business and Telecommunications (ICETE 2016) - Volume 1: DCNET, pages 19-26

ISBN: 978-989-758-196-0

Content Centric Networking has appeared as an

emerging architecture for content delivery. Its com-

munication paradigm based on names seems to ﬁt bet-

ter the current Internet needs: users are interested in

content rather than its location, as IP does. The main

features of CCN are communication based on names

and in-network caching features everywhere. Espe-

cially, the in-network caching features appear as the

masterpiece to solve the current problem of ISPs. It

has been proven that with only 100MB of memory

allocated into the ISP facilities, the trafﬁc from the

ISP to the Internet can be reduced by 25%. Adding

100GB of memory can reduce the load further by

35% (Imbrenda et al., ). This extra memory can be

organized in particular locations of the ISP, organized

as Micro CDNs using the CCN technology. As such,

these Micro CDNs can help to achieve three goals: re-

move redundant trafﬁc, increase the performance for

end users and reduce the trafﬁc generated towards the

Internet.

Micro CDNs are expected to bridge CCN net-

works to the Internet. As such, many entry and exit

points must exist between these two networks. We re-

fer to entry and exit points as Gateways. These Gate-

ways are used to transform packets from one architec-

ture (CCN) to another (TCP/IP). However, the trans-

formation of packets from one network to another is

not the only problem that the gateways cause. The de-

sign of Single or Multiple Gateways may have a major

impact on the performance of the caches of the Micro

CDN network. In this paper, we study the difference

between implementing Single or Multiple Gateways

and the impact on the caching features. With exten-

sive simulations, we show that Multiple Gateways are

a better design choice because they not only provide

a better caching performance for the overall network,

but also they distribute uniformly the load across the

network.

The rest of the paper is organized as follows. In

the Section 2, we describe the CCN architecture and

present a use case for the architecture: Micro CDNs.

The section 3 give an insight into Single and Multi-

ple Gateways and details the hypothesis treated in this

paper. Then, the simulation environment and the re-

sults are presented in Sections 4 and 5. Subsequently,

the related work on the area is presented in Section 6.

Section 7 summarizes the contributions of this work

and deﬁnes future work.

2 CCN OVERVIEW

2.1 Details of the Architecture

CCN is a clean-slate approach for the future Internet.

The communication paradigm is led by names, known

as (Content Names), which are contained in the Inter-

est and Data messages. Communication is based on

these two primitives: Interest and Data. The Interest

expresses the will of a user for a content, while a Data

message contains the answer for that content.

To address Content Names, every CCN node holds

three tables:

• Content Store (CS) is a caching structure that

stores content temporarily.

• Pending Interest Table (PIT) keeps track of the

currently non-satisﬁed interests. Basically, it

serves as a trace for the reverse path once the re-

quested content is found.

• Forwarding Interest Base (FIB) is a routing table

used to determine the interface to transmit con-

tent.

When an Interest arrives, the node extracts the

Interest name and looks up into its CS for content

stored that matches the full name. If the content is

found, it is automatically sent back through the inter-

face over which the Interest arrived and the Interest

is discarded. Otherwise, we lookup the PIT to decide

whether the CCN node is already waiting for the re-

quested content. If an entry is found, the Interest is

discarded. Otherwise, the FIB table is checked to de-

cide the interface to redirect the Interest to. In the

FIB table, a longest preﬁx matching operation is per-

formed and the Interest is forwarded to another CCN

node where same procedure is repeated until the re-

quested content is eventually found.

There exists a reluctancy from the major network

equipment companies such as Cisco or Huawei to im-

plement the CCN technology at large scale. Imple-

menting CCN at Internet scale will mean replacing

every IP router by a CCN router, which indeed will

have a major economic cost. As such, we argue that

CCN will be implemented in smaller networks where

there exists a clear economical beneﬁt. For instance,

ISPs can proﬁt of this technology with content deliv-

ery by answering trafﬁc locally instead of redirecting

it through the Internet. In the following section, we

revisit a use case for CCN into the ISP infrastructures

that target content delivery: Micro CDNs.

DCNET 2016 - International Conference on Data Communication Networking

2.2 Micro CDN: A Use Case for CCN

Micro CDN is a content delivery system. It is a net-

work of caches that serve content to the clients of the

network. Micro CDN offers two main distinctive fea-

tures. First, in-network high-speed caching features.

Second, a content based routing protocol based on

names. Its features are achieved by implementing a

CCN network.

Using CCN as the underlying architecture for Mi-

cro CDNs presents the following advantages:

• Caches for Every Protocol/Application. Cur-

rently, different CDN architectures target differ-

ent applications or protocols. For instance, a CDN

may offer services for live streaming of content or

static content delivery. With the use of CCN, dif-

ferent protocols and applications share the same

information at the networking layer. At network-

ing layer, a Content Name speciﬁes the content

being transmitted instead of the protocol or any

IP address of the server destination. It means that

every caching protocol and application can beneﬁt

of the in-network caching features of CCN.

• Fine-Granularity of Cached Content. Content

Names are hierarchically structured and made up

of components. Among the components, CCN

stores segmentation and version of the packet. It

means that CCN handles packets at a chunk level.

This can be beneﬁcial for particular cases of con-

tent delivery. Such is the case for video on de-

mand services, where ﬁrst chunks must be re-

trieved faster to start playback than the rest of the

chunks that can be incrementally downloaded.

• No More HTTP. Nowadays, most of the content

is transmitted through HTTP pages. Although the

HTTP protocol was not implemented for transmit-

ting content. For example, video streaming ser-

vices such as YouTube serve of HTTP and RTSP,

another protocol derived from HTTP, to deliver

the content. CCN permits to deliver content at the

network layer and completely suppress the over-

head caused by HTTP.

CCN based Micro CDNs may provide interesting

features for ISPs and networks in general. However,

there are still many parameters and studies to be car-

ried out. In this paper, we focus one speciﬁc param-

eter of Micro CDNs: the Gateways and its impact on

the caching features.

3 SINGLE GATEWAY OR

MULTIPLE GATEWAYS

A Gateway is a network node interfaced to connect

to other networks that use different communication

protocols.

In our case, the Gateways connect the Micro CDN

with the Internet. As Internet uses the TCP/IP com-

munication model and the Micro CDN uses CCN,

both networks are interfaced with Gateways. In a Mi-

cro CDN based on CCN, the content is not expected

to be produced in the CCN network. The CCN net-

work retrieves the information from the Internet. As

such, every time a content cannot be found in a cache,

it is demanded through a Gateway and subsequently

retrieved from the Internet.

Interfacing two networks through Gateways is a

challenging problem. In particular, mapping a CCN

name into an IP packet is a complicated task and it

depends on naming conventions (Shang et al., 2013).

However, this is not the only interesting point. As

CCN is a network of caches, different manners of im-

plementing Gateways will affect drastically the per-

formance of the Micro CDN. As a consequence, it is

essential to determine the effects produced by using

alternative Gateway designs to interconnect the CCN

and Internet networks.

In the Figure 1, we have explicitly said similar re-

quests are always retrieved from the same gateway.

We assume that the CCN network has a routing proto-

col associated. In this case, it is Open Short Path First

for Named data (OSPFN) (L. Wang, A. M. Hoque,

C. Yi, A. Alyyan, and B. Zhang, 2012; Moy, 1998)

OSPF is the default routing protocol for CCN. OSPF

ﬁnds the shortest path towards the requested node. As

such, similar requests are always to follow the same

routing protocol and will be guided through the same

nodes.

There exists an alternative manner to explain this

problem: using catalogs instead of gateways. A cat-

alog is a storage entity where all the demanded con-

tent is previously saved. Then, if we consider an au-

tonomous CCN network without connection with ex-

ternal networks, the catalogs can be interpreted as the

Gateways of the network. Single or Multiple Gate-

ways can be translated into Single or Multiple cata-

logs. Thus, every request is answered with one of the

catalogs. The problem becomes into assessing if hav-

ing one single catalog or multiple catalogs distributed

across the network are better choices.

For the analysis on the impact of Gateways into

caching features, we consider two types of Gateway

designs that are presented in the Figure 1: Single and

Multiple Gateways. The Single Gateways are repre-

Analyzing Gateways’ Impact on Caching for Micro CDNs based on CCN

Figure 1: Micro CDN connected to the Internet using Single and Multiple Gateways.

sented on the left side of the Figure while the Multiple

Gateways are on the right side. In both cases, a Mi-

cro CDN network using CCN is connected to some

external network, the Internet. In the case of Single

Gateways, the Micro CDN has an internal topology

composed of many CCN nodes. However, only one of

these nodes is a Gateway and is connected to the ex-

ternal network. This node is responsible for retrieving

content from the Internet, when the content can not

be found in the CCN network. In the case of Multiple

Gateways, the Micro CDN has multiple CCN nodes

that have access to the external nodes. As in the pre-

vious case, these nodes are responsible for retrieving

content from the external network.

In the rest of the paper, we validate the following

hypothesis:

1. Multiple Gateways achieve better caching perfor-

mance than a Single Gateway.

2. Multiple Gateways distribute the load better

across the network than Single Gateways.

4 SIMULATION ENVIRONMENT

In order to assess the hypothesis under a re-

alistic and comprehensive simulation environ-

ment, we used SocialCCNSim, a discrete-event

simulation tool written in Python, available

at (https://github.com/mesarpe/socialccnsim, ).

This simulation tool supports all the parameters and

scenarios we have presented throughout the paper.

Regarding the topology, we consider Micro CDNs

as being part of the ISP infrastructure. The topologi-

cal structure of the Internet is not expected to change

and will be just like today’s Internet. As a conse-

quence, ISP topologies are the best candidates for

evaluating our strategies. We choose four ISP level

topologies and one tree topology: Abilene, Dtelecom,

GEANT and Tiger (Rossi and Rossini, 2011), and a

binary tree of 4-levels. We can see the topologies in

the Figure 2.

In our scenario, requests are issued from 8 nodes

in the network. These nodes are selected randomly

from the network. Every node follows the Poisson

process law with a frequency of 5Hz.

The content popularity model is a function that

establishes the popularity of every piece of content,

i.e., how often every single piece of content is re-

quested. The content popularity is commonly mod-

eled with a probability distribution function such as

Zipf or MZipf (Rossi and Rossini, 2011). In the liter-

ature, the (M)Zipf α parameter ranges from 0.6 to 2.5.

For instance, the catalog of the PirateBay is modeled

with α = 0.75, DailyMotion with α = 0.88, while the

VoD popularity in China exhibits a α parameter rang-

ing from 0.65 to 1.0 (Fricker et al., 2012). In our case,

we consider a broad range of α values from 0.65 to

2.0. Sometimes we refer to as popularity model with

α = 1.1

With regards to the conﬁguration of the caches,

we have selected Leave Copy Everywhere (LCE) as

the caching strategy to organize the data stored in the

network. Every time a Data message is transmitted

in a CCN network, LCE leaves a copy in the cache

of the CCN node. Least Recently Used was used as

replacement policy, to determine what elements must

be evicted from the caches.

The performance of caches is analyzed using the

Cache Hit metric. When we analyze an individual

cache, we report a Hit operation if an element is found

in a cache otherwise a Miss operation. In a network

of caches as CCN, we measure efﬁciency of caches

DCNET 2016 - International Conference on Data Communication Networking

(a) Abilene. (b) DTelecom. (c) Geant.

(d) Tiger. (e) Tree.

Figure 2: Topologies used across the simulations: 4 ISP-level topologies and a 4-level binary tree.

with Cache Hit shown in Equation 1: hits

refers to the

number of Interest messages answered by the cache of

node i, while miss

the number of unanswered Interest

messages. |N| refers to the number of nodes in the

topology.

CacheHit =

∑

|N|

i=1

hits

(

∑

|N|

i=1

hits

) + (

∑

|N|

i=1

miss

)

(1)

Table 1: Simulation environment.

Parameters

Number of requested 10

content

Cache size Ratio {10

−6

;10

−5

;

−4

;10

−3

}

Popularity Model MZipf(

α = {0.65; 1.1; 1.5;

2.0}, β = 0)

Topologies Abilene, Tree, Geant

Tiger, DTelecom

Caching Strategy LCE

Replacement Policy LRU

Request Model Poisson Process

Request Placement Uniform Probability

Law

Gateways conﬁgurations Single (random),

Multiple Disjoint

Repetitions 3

Simulated Time 86,400 seconds

Routing Algorithm Open Shortest

Path First

5 RESULTS

Hypothesis #1: Multiple Gateways achieve better

caching performance than Single Gateways

Our intuition is that Multiple Gateways can

achieve better performance in terms of Cache Hit than

Single Gateways. To assess this hypothesis, we resort

to compare performance of Cache Hit in several sce-

narios. We vary topologies, popularity scenarios and

cache sizes. We expect to ﬁnd that caching perfor-

mance of the overall network is always better with

Multiple Gateways than with Single Gateways.

In the Figure 3, we present the results of our com-

parison of Multiple Gateways and Single Gateways

after 480 experiments. In the x-axis, we show the

Cache Size Ratio while the y-axis shows the Cache

Hit results. The blue line represents the Disjoint Mul-

tiple Gateways while the red line refers to the Sin-

gle Gateway. Every line of charts corresponds to

one topology while every row corresponds a different

popularity model.

With a ﬁrst look on the charts, we can see that the

blue line always surpasses the red line: it means that

the Cache Hit Ratio for Multiple Gateways is always

better than the ratio for Single Gateways. It does not

matter which topology we consider or what popular-

ity scenario we evaluate, the condition always stand.

With 480 experiments, we can conclude that Multiple

Gateways have always better Cache Hit performance

than single gateways.

There exist certain cases where the difference of

performance between Single and Multiple gateways

increase. This is the case for a popularity model with

(α = 1.5) and for the DTelecom topology also stands

when α = 1.1. Our intuition is that the connection de-

Analyzing Gateways’ Impact on Caching for Micro CDNs based on CCN

0.0

0.2

0.4

0.6

0.8

1.0

-6

-5

-4

-3

Abilene

Popularity model (α = 0.65)

Multiple Gateways

Single Gateways

-6

-5

-4

-3

Popularity model (α = 1.1)

-6

-5

-4

-3

Popularity model (α = 1.5)

-6

-5

-4

-3

0.0

0.2

0.4

0.6

0.8

1.0

Cache Hit

Popularity model (α = 2.0)

0.0

0.2

0.4

0.6

0.8

1.0

-6

-5

-4

-3

Tree

-6

-5

-4

-3

-6

-5

-4

-3

-6

-5

-4

-3

0.0

0.2

0.4

0.6

0.8

1.0

Cache Hit

0.0

0.2

0.4

0.6

0.8

1.0

-6

-5

-4

-3

Tiger

-6

-5

-4

-3

-6

-5

-4

-3

-6

-5

-4

-3

0.0

0.2

0.4

0.6

0.8

1.0

Cache Hit

0.0

0.2

0.4

0.6

0.8

1.0

-6

-5

-4

-3

Geant

-6

-5

-4

-3

-6

-5

-4

-3

-6

-5

-4

-3

0.0

0.2

0.4

0.6

0.8

1.0

Cache Hit

0.0

0.2

0.4

0.6

0.8

1.0

-6

-5

-4

-3

Dtelecom

Cache Size Ratio

-6

-5

-4

-3

Cache Size Ratio

-6

-5

-4

-3

Cache Size Ratio

-6

-5

-4

-3

0.0

0.2

0.4

0.6

0.8

1.0

Cache Hit

Cache Size Ratio

Figure 3: Single vs Multiple Gateways.

gree of the topology has an inﬂuence on the caching

performance. The connection degree stands for the

average number of edges connected to every node

in the topology. For instance, Abilene and the Tree

topology shares a connection degree of 2.54; Tiger

and Geant hold a connection degree between 3 and 4

while Telecom is bigger than 10. If we consider the

topologies shown, the gap between Single and Multi-

ple Gateways is not important. Once the connection

degree of the topology increases, the gap of perfor-

mance increases. As we can see analyzing the ﬁgure

with a top-bottom approach, the gap performances get

increased as we switch from less connected topolo-

gies towards more connected topologies. The reason

for this behavior can be found on the number of paths

towards the different gateways: as more alternatives

of connections appear, alternative paths can be cre-

ated to reach different gateways. Thus, gateways be-

come less active and their caches are crossed by less

requests.

Hypothesis #2: Multiple Gateways distribute

the load better across the network than Single

Gateways

To prove that, we collect all the paths generated

during the experiences. From these paths, we count

all the processed Interest messages by the nodes and

average them over the total number of processed In-

terest messages. For example, let us imagine that we

have two requests that cross through nodes 1,2,3,4 and

4,1,5. As we can see there are 2 requests for content

1 and 4, one request for content 2, 3 and 5. In total,

there are 7 requests. For instance,

of the requests are

for content 1. The aim of this experiment is to show

that Multiple Gateways generate a more uniform dis-

tribution of the requests than a Single Gateway.

In the Figure 4, we show the results of our ex-

periment. The Figure presents two pie charts: one

describes the percentage of processed Interest mes-

sages with Single Gateways while the second Mul-

tiple Gateways. Every pie chart is divided into 11

pieces. Every slice of the pie represents the processed

Interest messages by every node. After, the slices that

surpassed the sum of the average of processed mes-

sages plus its standard deviation were separated a bit

from the core of the pie, to highlight heavier load.

From the pie charts, we can observe that with Sin-

gle Gateways, most of the Interest messages are man-

aged by only a few nodes. With more precise number,

50% of the Interest messages are processed by two

nodes of the network. With Multiple Gateways, the

processing of Interest messages is distributed across

all the nodes of the network. It means that even when

some nodes are heavy loaded than others, there exists

a fair distribution of the charge of the network. Thus,

we can conclude that Multiple Gateways are useful to

balance the load of processed Interest messages.

DCNET 2016 - International Conference on Data Communication Networking

(a) Single Gateways. (b) Multiple Gateways.

Figure 4: Processed Interests per node with Single vs. Multiple Gateways. The pie chart represents the percentage of

processed messages by every node. Colors are used to simplify the reading.

6 RELATED WORK

CCN has attracted considerable attention for their

caching features. The data structure used for replac-

ing content in the CS is called Replacement Policy

(RP). These RPs are largely used in operating sys-

tems such as Least Recently Used (LRU), Most Fre-

quently Used (MFU) or First-In First-Out (FIFO).

Rosensweig et al. (Rosensweig et al., 2013) have

shown that, in the long term, the replacement poli-

cies can be grouped into equivalence classes. This

means that their results are prone to be similar. Then,

the coordination of multiple CS has been studied with

the use of caching strategies: Leave Copy Every-

where, ProbCache, Leave Copy Down, MPC (Bernar-

dini et al., b), SACS (Bernardini et al., 2014) or

Cache “Less for More”. These caching strategies

have shown interesting results and are summarized

and compared in (Bernardini et al., a).

Rossi et al. (Rossi and Rossini, 2012) study per-

formance of heterogeneous and homogeneous cache

sizes. Although heterogeneous caches achieve better

results than homogeneous caches, the gain is modest

and it incorporates high complexity for managing and

maintaining heterogeneous cache sizes.

Another hot topic is where to deploy the caches.

In case every Internet router adds caching capabilities,

enormous cache sizes (100 Petabytes) will be needed

to achieve acceptable rates of performance (Fricker

et al., 2012). Due to prohibitive cost of adding

caches everywhere and of the required sizes, re-

searchers started discussing about locating caches at

edge network (or ISP facilities). Fayazbakhsh et

al. (Fayazbakhsh et al., 2013) afﬁrm that placing the

caches at edge network is a best choice because of

two reasons: the same caching results can be achieved

and it is easier to manage only caches at the edges of

the network than at global scale. In this sense, Im-

brenda et al. (Imbrenda et al., ) analyzed trafﬁc on a

real ISP infrastructure and concluded that with a neg-

ligible amount of memory of 100MB, the load in the

access network can be reduced by 25%. As a conse-

quence, the research on the ﬁeld points out that CCN

must be implemented at the edges of the network and

this is the reason to implement CCN into Micro CDNs

networks.

7 CONCLUSION

ISPs are facing certain difﬁculties with the video on

demand services. CCN networks appear as an emerg-

ing technology to address these issues. Results on the

state of the art highlight that caching infrastructures

may be helpful to reduce the trafﬁc of the ISP net-

work. Indeed, we have revisited the notion of Micro

CDNs deploying the CCN technology. it is essential

to study interconnection of these Micro CDNs with

the Internet. In this paper, we study the impact on the

caching of this interconnection. Caching features will

play a major role in the implementation of CCN net-

works. We have evaluated two alternatives of build-

ing gateways: Single Gateways and Multiple Gate-

ways. The multiple disjoint gateways have shown to

improve the performance of the network in terms of

caching performance, but also in balancing the load

of the network. we can obtain a gain of up to 10% in

the efﬁciency of the caches by just doing a small adap-

tation in the conﬁguration of the network and also dis-

tributing better the charge across the network. When

a 1 or 10% of gain in terms of cache efﬁciency may

translate into saved money for the exchanged trafﬁc

between networks.

The impact on caching of interconnection of CCN

Analyzing Gateways’ Impact on Caching for Micro CDNs based on CCN

networks with the Internet is an important subject that

aboards many other subjects. We are interested in

revisiting this subjects in the early future. For in-

stance, it is essential to determine the impact of differ-

ent caching strategies and different routing algorithms

on the construction of Gateways. It is important to

create models to calculate the potential gains by us-

ing Single and Multiple Gateways. Sometimes, the

implementation of Single or Multiple Gateways may

not be oriented by performance matters but for costs.

If this is the case, we expect that models are devel-

oped to measure the trade-off of performance against

costs.

ACKNOWLEDGMENTS

This work has been partially funded by the Austrian

Research Promotion Agency (FFG) and the ENIAC

Joint Undertaking, grant 843738 eRamp.

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