One document matched: draft-dong-qms-fag-00.xml
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<rfc category="info" docName="draft-dong-qms-fag-00" ipr="trust200902">
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<!-- ***** FRONT MATTER ***** -->
<front>
<!-- The abbreviated title is used in the page header - it is only necessary if the
full title is longer than 39 characters -->
<title abbrev="QMS based on Flow Aggregation">A Dynamic Service Class Mapping Scheme
for Different QoS Domains Using Flow Aggregation</title>
<!-- add 'role="editor"' below for the editors if appropriate -->
<!-- Another author who claims to be an editor -->
<author fullname="Yu-ning Dong" initials="Y.N." role="editor"
surname="Dong">
<organization>Nanjing Univ. of Posts and Telecom.</organization>
<address>
<postal>
<street>66 New Mo-fan-ma-lu Road</street>
<!-- Reorder these if your country does things differently -->
<city>Nanjing</city>
<region>Gulou</region>
<code>210003</code>
<country>China</country>
</postal>
<phone>+86 15077858011</phone>
<email>dongyn@njupt.edu.cn</email>
<!-- uri and facsimile elements may also be added -->
</address>
</author>
<author fullname="Chun Liu" initials="C." role="editor"
surname="Liu">
<organization>Nanjing Univ. of Posts and Telecom.</organization>
<address>
<postal>
<street>66 New Mo-fan-ma-lu Road</street>
<!-- Reorder these if your country does things differently -->
<city>Nanjing</city>
<region>Gulou</region>
<code>210003</code>
<country>China</country>
</postal>
<phone>+86 18362930657</phone>
<email>132189@163.com</email>
<!-- uri and facsimile elements may also be added -->
</address>
</author>
<date month="February" year="2016" />
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<area>General</area>
<workgroup>Datagram Congestion Control Protocol</workgroup>
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<abstract>
<t>This document addresses the issue of provisioning end-to-end Quality of Service (QoS)
for multimedia services over heterogeneous networks and introduces a parametric model
by using network calculus theory for QoS class mapping between different QoS domains.
Then a QoS Mapping Scheme based on Flow Aggregation (QMS-FAG) is proposed in this
document to mitigate the information loss problem due to mapping between QoS domains with
different granularity of QoS class and to provide efficient network resources
utilization by considering user's Quality of Experience (QoE). In QMS-FAG, the QoS
requirements of service flows are indicated by a unique FAG identifier which is described
in a service flow map of QoS parameters. With FAG identifier and mapping executors sitting
at the border of different QoS domains, QMS-FAG allows smooth QoS class mapping between
networks with different granularity of QoS class. Both numerical analysis and simulation
studies are given to demonstrate the efficiency of the proposed method.</t>
</abstract>
</front>
<middle>
<section title="Introduction">
<t>This document proposes a unified QoS Mapping Scheme based on Flow AGgregation (QMS-FAG) to
provide better end-to-end QoS over heterogeneous networks. Different from previous
efforts, the aim of the proposed method is to provide better flow services over
heterogeneous networks. We aim to contribute to the ongoing research by proposing a QoS
mapping scheme, based on network QoS requirements and users' QoE. The proposed method has
several advantages: (1) it considers the asymmetrical problem between fine and coarse
grained QoS domains (Normally the fine grained QoS domain has more/finer QoS classes
than the coarse grained QoS domain); (2) it considers QoE and can improve users'
experience by maximizing the utilization of network resources with flexible QoS
class mapping; (3) it does not need a mapping table.</t>
<section title="Requirements Language">
<t>The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in <xref
target="RFC2119">RFC 2119</xref>.</t>
</section>
</section>
<section anchor="qms_flag_development" title="QMS-FAG Development">
<t>Previous studies on QoS class mapping between different networking technologies can
be roughly classified into two categories: the function based methods [2][3] and
mapping-table based ones [4][5]. The first category that translates between the
QoS parameters of heterogeneous networks is complex, in which the effective design
of functions can highly affect the end-to-end QoS. The second category that
established mapping tables consisting of many QoS class pairs can cause the i
nformation loss due to mapping between QoS domains with different granularity of
QoS class. One shortcoming of current approaches is incapable of utilizing network
resources efficiently because of not considering users' QoE in the QoS mapping process.</t>
<t>For ease of analysis, let us define the following variables:</t>
<t><list style="symbols">
<t>RN = N-dimensional real number Euclidian space;</t>
<t>Pvi = overall N QoS requirements of i-th service;</t>
<t>pvin = value of N QoS requirement for i-th service;</t>
<t>PWhl = lower boundary of QoS class h in network W;</t>
<t>PWhu = upper boundary of QoS class h in network W;</t>
<t>HW = number of QoS classes in network W;</t>
<t>P = a conjunction of a set of F QoS parameters;</t>
<t>pf = the f-th element of P;</t>
<t>Sk = the k-th Mapping Evaluator(ME);</t>
<t>X = set of FAG;</t>
<t>FWm = QoS description of xm in network W.</t>
</list></t>
<section title="QoS and QoS Class Models">
<t>Based on [6] and our finding, each of QoS parameters can be parameterized
by a real number (Please see Appendix A for details). Assuming that the
QoS value is ranked in order of importance in this paper, the most important
one has the minimal value and the least important has the maximal value.
Each of QoS requirements can then be represented by a real number and the
overall QoS requirements can be represented by a vector consisting of
corresponding QoS parameters. Formally, we specify the overall N QoS
requirements of i-th service by vector Pvi, as follows:</t>
<t><list style="symbols">
<t>Pvi = [pvi1, pvi2, pvi3,..., pviN], i=1,2,3,... (1)</t>
</list>where i is an integer that represents index of service,pvi is in
RN represents the value of n-th QoS requirement located in
RN space for i-th service. RN denotes an N-dimensional
real number Euclidian space which is consisted of QoS parameters.</t>
<t>Because each QoS class has a sub-space in N-dimensional space, we use a pair
value (PWhu,PWhl) specification in our paper, which will allow us to define
range representation with acceptable QoS regions (PWhl≤Pvi≤PWhu) and unacceptable
QoS regions (Pvi<PWhl) of QoS class h in network W with proper normalization of
QoS parameters (see Appendix A for details).Pvi<PWhl indicates the level of QoS
is below the acceptable lower boundary, with which the traffic should be
arranged for the lower class level or refused to transmit. For the case of Pvi>PWhu,
it indicates that the traffic with Pvi should be arranged for a higher class
level.PWhl and PWhu are the lower and upper boundaries of QoS class sub-space
in N-dimensional space, respectively, whose definitions are similar to Pvi,
where h=1,...,HW;HW is the number of QoS classes in network W.</t>
<t>QoS influences user's QoE, which is vital for the success of multimedia services. Furthermore,
QoE is also influenced by the human factors that often are independent of the service type [7].
As a result, different users of the multimedia service have different tolerance for adjusting
QoS level. For some users, when enjoying a live TV program via web (such as a football match),
they probably prefer to degrade their QoS level rather than to be denied access directly.
Therefore, users' QoE should be considered in QoS class mapping schemes to increase the
number of satisfied users in heavy traffic load. </t>
<t>Depending on the individual human perception, it is somewhat difficult to give a precise
objective metric and objective estimation method for QoE [8]. This paper will not
concentrate on how to estimate QoE or map between QoE and QoS, which has been a hot
research topic of many other works [8][9].</t>
<t>We use the QoE model proposed in [9] to obtain a mean opinion score (MOS) to rate QoE
level and modify the model by substituting sender bitrate (SBR) with bandwidth and
block error rate (BLER) with packet loss rate caused by delay and link errors.
In the modified model mean burst length (MBL) and content type (CT) have constant
values of 2.5 and 0.1, respectively, which are typical values in [9] (For details
see Appendix B). The values of the coefficients of the modified model are the
same as the values of the model proposed in [9]. In this paper, by dynamically
adjusting the QoS parameter values within threshold, we present an empirical QoS
class mapping method with QoE to demonstrate the feasibility of the proposed method.</t>
</section>
<section title="Flow Aggregation Concept">
<t>A flow aggregation (FAG) is defined in this work as a set of flows with similar QoS
requirements represented by a conjunction of a set of F QoS parameters P=[p1,p2,...,pF],
each associated with a QoS constraint, that can be specified by a range representation
with acceptable and unacceptable QoS regions. We assume that the QoS requirements of
a service flow can be expressed by a vector in a multi-dimensional space of relevant
QoS parameters, and then define this multidimensional space as a service flow map.
Each FAG has a unique identifier that can be described by the QoS information on
a service flow map.</t>
<t>The FAG is different from QoS class defined by global standardization organizations
in the following aspects: 1) its granularity can be established on the fly according
to QoS requirements of services and reflects natural muster in QoS characteristic space,
and is not connected with any of the predefined QoS classes; 2) it provides a bridge
with a flexible granularity for consistent mapping between fine and coarse grained QoS
classes in order to mitigate the information loss problem, whose efficacy will be
demonstrated by numerical analysis in Section V.</t>
</section>
<section title="An Overlay Network Paradigm">
<t>In this section, we describe an overlay network paradigm based on the scenario
illustrated in Fig. 1. From the viewpoint of providing end-to-end QoS guarantees,
the process of QoS mapping can be imagined as a virtual plane of QoS mapping above
the traditional layers. This plane of QoS mapping is a collection of virtual nodes
connected together by a set of virtual links to form a large virtual domain, which
is essentially a subset of the underlying network topology. Each virtual node is
a logical abstraction of a particular physical node that processes QoS mapping.
A virtual link spans over a path in the physical network and includes a portion
of the networking resources. By allowing multiple networks to have different QoS
domains to map QoS in the plane of QoS mapping, users in two ends construct a
virtual end-to-end path and are provided end-to-end QoS guarantees across different
QoS domains, as illustrated in Fig. 1.</t>
<t>In Fig. 1, the proposed Mapping Evaluator (ME) entity sits on a gateway/router
at the edge of two different QoS domains, aiming to classify each service according
to QoS requirements. Whenever ME receives a service, it generates a corresponding
FAG with P according to QoS requirements of the service by a clustering algorithm,
such as evolutionary algorithm, and labels the FAG with a unique FAG identifier.
Then ME puts the FAG into the corresponding queue with the same priority value.
According to available network resources, ME determines appropriate QoS class
mapping between current and new networks for the FAG by the proposed QMS-FAG.</t>
</section>
<section title="A Typical Scenario of QoS Class Mapping over Heterogeneous Networks">
<t>In this section, we depict a typical scenario of QoS class mapping over
heterogeneous networks.</t>
<figure anchor="figureTypicalScenario">
<preamble>A typical scenario of QoS class mapping over
heterogeneous networks is shown below.</preamble>
<artwork><![CDATA[
Nwk A -----R1----- Nwk B -----R2----- Nwk C
]]></artwork>
</figure>
<t>As illustrated in figure above, we consider a scenario of three interconnected networks
(Nwk A, Nwk B and Nwk C) connected by two gateways/routers (R1 and R2). Assume
Nwk A and Nwk C are 3G UMTS networks and Nwk B is a wireline IP-based Diffserv
network. Since audio conferencing is a typical multimedia service requiring
strict QoS requirements to set priorities at flow\packet level, here we assume
that the audio conferencing service is implemented between user X and user Y.
In source network (Nwk A), an appropriate QoS class queue is assigned to audio
according to QoS requirements. For traditional QoS mapping, the QoS class
mapping table is preset in the gateway/router that sits at the boundary of two
different QoS domains and the audio conferencing service belongs to a certain QoS
class of current QoS domain. Whenever the gateway/router receives an audio
conferencing service, it determines an appropriate QoS class mapping between
current and new network according to the mapping table for this audio conferencing
service. </t>
</section>
<section title="MOS Value for Video Service">
<t>The MOS value for video service is computed as follows [10]:</t>
<t><list style="symbols">
<t>MOS = (a1+a2*ln(SBR)+CT*(a3+a4*ln(SBR)))/(1+(a5*BLER+a6**BLER*BLER)*MBL) (2)</t>
</list>where, SBR is sender bitrate, BLER is block error rate in 3G/UMTS networks,
MBL is mean burst length, CT is content type of the video service.</t>
<texttable anchor="table">
<preamble>Coefficients in (2) are:</preamble>
<ttcol align="center">a1</ttcol>
<ttcol align="center">a2</ttcol>
<ttcol align="center">a3</ttcol>
<ttcol align="center">a4</ttcol>
<ttcol align="center">a5</ttcol>
<ttcol align="center">a6</ttcol>
<ttcol align="center">CT</ttcol>
<ttcol align="center">MBL</ttcol>
<c>3.9560</c>
<c>0.0919</c>
<c>-5.8497</c>
<c>0.9844</c>
<c>0.1028</c>
<c>-0.236</c>
<c>0.1</c>
<c>0.25</c>
</texttable>
</section>
</section>
<section anchor="qms_fag_description" title="QMS-FAG Description">
<section anchor="parametric_model" title="Parametric Model">
<t>The proposed scheme can automatically map the FAG to the appropriate class that
has QoS resource by adjusting QoS requirements. An attractive feature of the
dynamic QoS class mapping is that the method considers the QoE of end users
by which the ME adjusts the QoS requirements of FAG under the condition of
available QoS resources.</t>
<t>Consider a network session being set up over the heterogeneous networks
consists of MEs S1,S2,...,Sk, the set of FAGs that will be transmitted into the
next network can be described as </t>
<t><list style="symbols">
<t>X = {x1,...,xm,...,xM}, m=1,2,...,M (3)</t>
</list>where xm represents the m-th FAGs, M is the number of FAG in an ME.</t>
<t>By a similar description to QoS class, xm can be described as </t>
<t><list style="symbols">
<t>FWm = [Pm1,...PmN], m=1,2,...,M (4)</t>
</list>where FWm denotes QoS description of xm in network W,
Pmn(n=1,2,...,N) represents the n-th QoS requirement of xm.</t>
<t>In mapping process, the ME will map xm to class y described as
below by the function Phi(for RN->F, then x->Phi(x)).
This function can be derived as [2]</t>
<t><list style="symbols">
<t>ch=W*(||FWm-PWh||), for all h=1,2,...,HW (5)</t>
</list>where ch is the order of QoS class mapped according to PWm,
W=[w1,w2,...,wHW] is a weighting array which is used to describe the
characteristics of multimedia service, satisfied with w1+w2+...+wHW=1
and often gained based on the experience. But the computation
is different in the two following cases: lower and higher
traffic load cases.</t>
</section>
<section title="Procedure of QMS-FAG">
<t>Computation is different in the two following cases: lower and higher
traffic load cases.At lower traffic load, QoS class y can be derived as
</t>
<t><list style="symbols">
<t>y = {k|ck=minh{ch}}, for all h=1,2,...,HW (6)</t>
</list>where k is the order of QoS class and ck is the minimum value among all
QoS classes ch, y is the order of QoS class adjusted according to available network
resources. Here, if one QoS class has a smaller order value, the class's FAG
has a better chance to transmit earlier.</t>
<t>At higher traffic load, the process is as follows:</t>
<figure>
<preamble> The QMS-FAG scheme at higher traffic load is described in Algorithm 1.</preamble>
<artwork><![CDATA[
/*Algorithm 1: The QMS-FAG scheme */
-------------------------------------------------------------------
1. The QoS class level is decreased by one
2. y is recomputed according to equations (6) based on the QoS requirements adjusted
3. If network resources for the decreased QoS class are still not enough to transmit
this FAG, go back to step 1)
4. If the MOS value is still OK (above a preset threshold MOSth) for end users,
based on Equ. (2), then, this FAG is transmitted; otherwise,
the FAG is rejected.
6. The process is stopped.
-------------------------------------------------------------------
]]></artwork>
</figure>
<t>On the whole, the algorithmic steps of QoS class mapping are as follows:</t>
<t>1)If the network resource allows, ck is mapped to QoS class y based on equations (2)</t>
<t>2)If the network resource is not allowed, with the process in the case of
higher traffic load, the ME gradually reduces the order of QoS class for xm
until xm is transmitted with a lower order of QoS class, or is rejected if
no appropriate mapping is available (assuming the lower the order of QoS
class, the lower its priority). </t>
</section>
</section>
<section anchor="Acknowledgements" title="Acknowledgements">
<t>The authors would like to acknowledge feedback and discussions on
service class mapping scheme for QoS with a wide range of people,
including members of the Wireless Communication Research Group and
the End-to-End Research Group. Thanks are given to the National
Natural Science Foundation of China (No.61271233, No.60972038), the
Ministry of Education (China) Ph.D. Programs Foundation (No.20103223110001),
the Research Culture Funds of Anhui Normal University (No.2013xmpy10) and
Jiangsu Province Postgraduate Innovative Research Plan (No.CXZZ11_0396)
for their financial support.</t>
</section>
<!-- Possibly a 'Contributors' section ... -->
<section anchor="IANA" title="IANA Considerations">
<t>There are no IANA actions required for this document.</t>
</section>
<section anchor="Security" title="Security Considerations">
<t>All drafts are required to have a security considerations section.</t>
</section>
</middle>
<!-- *****BACK MATTER ***** -->
<back>
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&RFC2119;
</references>
<references title="Informative References">
<!-- A reference written by by an organization not a person. -->
<reference anchor="B"
target="Proc. NEW2AN">
<front>
<title>Systematic QoS Class Mapping Framework over Multiple Heterogeneous Networks</title>
<author initials="" surname="Misun Ryu, Youngmin Kim, Hongshik Park">
<organization></organization>
</author>
<date year="September 2008" />
</front>
</reference>
<reference anchor="C"
target="Proc. IEEE IC-BNMT">
<front>
<title>IPv6 end-to-end QoS provision for heterogeneous networks using flow label</title>
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</author>
<date year="2010" />
</front>
</reference>
<reference anchor="D"
target="Proc. WiCOM">
<front>
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<author initials="" surname="Lin Fu, Fei Pei, Zhang Dengyi, Li Wenhai">
<organization></organization>
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<date year="2011" />
</front>
</reference>
<reference anchor="E"
target="Proc. IEEE Symposium on Computers and Informatics">
<front>
<title>Cooperative architecture for QoS management in wireless 4G networks</title>
<author initials="" surname="Ben Hamza Nejd, Rekhis Slim, Boudriga Noureddine">
<organization></organization>
</author>
<date year="2011" />
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<reference anchor="F"
target="IEEE Multimedia">
<front>
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<date year="1995" />
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<front>
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<date year="October 2009" />
</front>
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<reference anchor="H"
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<front>
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<front>
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</author>
<date year="2012" />
</front>
</reference>
<reference anchor="j"
target="Hydrological Processes">
<front>
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<author initials="" surname="Cibin R, Sudheer K P, Chaubey I">
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