QoS Management Scheme Based on OAM
Performance Management
Zhao Yang and Wang GuangXing
Northeastern University, Shenyang, China (postal box 427#)
Postal code: 110006, E-mail: zhaoyang@mail.neu.edu.cn
Abstract
Monitoring the change of network performance parameters is a key to realize the QoS management in ATM networks.
The OAM performance management function defined by ITU-T, however, simply monitors network performance and
reports sratus information. It can not give QoS management an enough support. In terms of the relationship between QoS
and network performance parameter, an ATM layered QoS management model is proposed and defined. In this model, an
improvement in OAM performance management functions is also made. Some new functions, which are necessary to
QoS management, are defined in reserved field of activation/deactivation OAM cell and forward monitoring/backward
reporting OAM cell.
Keywords
QoS Management,
OAM(Operations, Administration, and Maintenance),
Network Performance
Parameters
1. Introduction
ATM network guarantees many kinds of user’s QoS requirement. When a connection is set up, the QoS parameters of
user’s application are mapped or translated into each layer’s QoS parameters of protocol stacks. Meanwhile, they are
translated into network performance (NP) parameters through call admission control (CAC) in switching system. These
NP parameters include cell loss rate, cell delay, and cell delay variation, etc. Cell delay is induced by propagation delay,
switching delay, and queuing delay; whereas, cell loss is caused by transmission error, lack of buffer space, and cell delay
violation. The changes of the parameters reflect whether the ATM network fulfills its service contract for a given
connection. Therefore, how to monitor and report NP parameters effectively is a key in ATM QoS management.
Recently, many works about QoS management [1,2,3,4] have been studied. The QoS framework, in which the QoS
manager interacts with the network management framework and applications, has been proposed [1]. A similar research
has been addressed as the QoS Broker [2]. The core function of the QoS Broker is QoS negotiation and translation. QoS-A
as a structure that supports QoS management mechanism systematically is proposed in [4], and QoS management
scenario in ATM layer is suggested in [3].
The OAM performance management function specified in ITU-T I.610, [5] periodically monitors the network
performance along routing path in the boundary of end-to-end or segment. In addition, the OAM function could extract
some control information according to the QoS parameters negotiated between users and networks at the connection
establishment phase and then apply it to traffic control functions in user and control plane in order to prevent congestion
within the networks. The OAM performance management function, however, simply monitors network performance and
reports them by performance management OAM cell. So, the functions executing the OAM performance management
function in the layer management of ATM protocol reference model should be extended for the purpose of supporting the
requirements for QoS management.
Therefore, a new QoS management framework based on the extended OAM performance management function is
proposed. We also integrate OAM functions with other QoS issues such as call admission control (CAC), usage parameter
control (UPC), resource control, and congestion control to implement QoS management. In the extended OAM
performance management, we defined some new fields to realize the scheme in the reserved field of OAM cells.
In section 2, we discuss the QoS layered structure model admitted widely. The concepts of QoS and network performance
parameters are also defined. On the basis of these discussions, we propose the QoS management model for ATM layer.
Section 3 gives the extended method for OAM performance management. At last, the conclusion is made.
2. QoS management framework
2.1 QoS layered structure model
From the ITU-T recommendations, it is generally admitted that the QoS is the user’s view of a service as opposed to the
network provider’s view [6]. In order to plan, design and operate the network and its services such as voice, data, and
video, future standards should refine the concept of QoS and propose an appropriate QoS framework. The framework
must satisfy user’s QoS requirements that not only change over time, but also depend on each application and user [7]. At
present, a generally accepted concept of QoS architecture is layered QoS structure, in which each layer guarantees the
requested QoS to its next-higher layer and demands a (possibly different) QoS from its next-lower layer [7,8,9]. The QoS
layered structure we use is modeled after the concept and is illustrated in Fig. 1. The architecture consists of four
horizontal protocol layers and three vertical control planes. The bottom three protocol layers are physical layer, ATM
layer and adaptation (AAL) layer. The functions and features of these protocol layers are well defined in ATM UNI
Specification. Application layer of QoS is defined for end-system.
The selection of QoS parameters in each layer depends on the requirements of its higher layer. Because each layer
receives the SDUs(Service Data Units) from a higher layer and uses the corresponding PDUs(Protocol Data Units) to
communicate with its peer layers. The QoS parameters are based on the SDU, and they can be accessed by SAP(Service
Access Point) between the higher and lower layer. For example, from the SAP of AAL, we can obtain the AAL QoS
parameter which is related to five kinds of traffic [10]; whereas, from the SAP of ATM layer, we get the ATM QoS which
reflect the end-to-end network feature, that is, namely network performance (NP). The network cannot understand the
meaning of higher layer’s QoS parameters. For instance, the definition of an image is described by the quantity of
pels/frame, which is no sense for network. Only when it is translated into such as bandwidth parameter, can it be
understood by network. Thus, it is necessary that application layer’s QoS should be translated into ATM layer’s QoS, and
the QoS translation finally results in the NP parameters. The translation goes beyond this paper.
2.2 ATM layer’s QoS parameter and NP
The QoS requirement is specified in terms of bounds on QoS parameter. These bounds can be either deterministic or
statistical [7].

Deterministic bound
QoS_Parameter <= Upper_bound
QoS_Parameter >= Lower_bound

Statistical bound
Prob(QoS_Parameter <= Upper_bound) >= Prob_bound
Prob(QoS_Parameter >= Lower_bound) <= Prob_bound
For the sake of simplicity, we consider only deterministic bounds in this paper. For example, the ATM layer’s QoS
parameter and its bound are described as follow.

Cell Loss Ratio(CLR) bound: CLRmax . It is an ATM specific parameter that results mainly from the buffer overflow
in ATM switches due to congestion.

Throughput bound: Wmin . The throughput requirements at the ATM layer are given in terms of W min parameter. In
the ATM layer, throughput bound describes the minimum bandwidth requested within a connection. This may
correspond to the cell rate in traffic parameter when there is no use of the fast resource management in Available Bit
Rate(ABR) and ATM Block Transfer(ABT) capabilities.

Cell Delay and Cell Jitter bound: Dmax and Jmax . The delay bound(Dmax), and jitter bound(Jmax) in ATM the layer have
the same definition as in the AAL with the understanding that these bounds are now concerned with ATM cells, not
frames.

Cell Misinsertion Rate(CMR) bound. The CMR is due to errors in ATM cell header. In our study we choose to
neglect the CMR since the ATM switches detect and discard cells having an errored header, and the AAL function
efficiently detects misinserted cells and therefore the CMR is negligible compared to the CLR.
The NP parameters are visible only to the network. They are under study in ITU-T [11] and are currently defined as
follows:

Bit Error Ratio(BER)

Cell Error Ratio(CER)

Cell Loss Ratio(CLR)

Cell Misinsertion Rate(CMR)

Cell Transfer Delay(CTD)

Cell Delay Variation(CDV) or Jitter

Severely Errored Cell Block Ratio(SECBR)
2.3 QoS management model for ATM layer
As being described above, the key QoS management depends on ATM layer’s QoS management. QoS translation
finally results in the NP parameters. These parameters determine whether the ATM network fulfills its service contract for
a given connection. Thus, we emphasize the QoS management on OAM performance management. We consider the
following two principles to define the QoS management model for ATM layer.
1. Protocol machines in user and control planes execute their own functions intelligently with autonomy [12].
2. The functions of upper planes should do more abstracts and integrated functions that lower planes can not control.
The function of upper plane reacts to solve a request, when the function of lower plane issues it as an event.
This model is shown as Fig.2. Protocol plane consists of user and control planes, which include QoS translation
function, QoS negotiation and maintain mechanism, call admission control (CAC), usage parameter control (UPC),
congestion control, and resource control etc.
In layer management, there are extended OAM management function unit, performance OAM function unit, and fault
OAM function unit, where, the functions of fault OAM function unit and performance OAM function unit are restricted to
the functions specified in ITU-T recommendation I.610. The continuity check and loopback test functions also specified
in the standard are executed as subfunction of fault and performance OAM functions. The extended OAM function unit
has a role as an upper plane function of the protocol plane, therefore, monitors the status and the performance of protocol
machines in the protocol plane, and operates on them properly. The protocol machines adjust their action according to the
monitoring results to guarantee the QoS for the existent connections. Meanwhile, the extended OAM function unit
notifies the plane management the monitoring results. The OAM interface is defined between plane management and
layer management. The management interface is also necessary between layer management and protocol plane.
Plane management consists of agent function unit, MIB unit and element system management unit. The element system
management unit is responsible for the control in the level of whole switching system. MIB is a unit to store the managed
objects, which are the abstraction of logical or physical resource. Agent function unit handles network management
messages, it realizes the access to managed objects defined in MIB.
So, the process of QoS management can be concluded as following:
(1) QoS translation and classification. Translate users’ QoS parameters to each layer’s QoS parameters until NP
parameters in ATM layer.
(2) QoS negotiation and setup. QoS consult and maintain mechanism demand the resource control through CAC. If
there is enough resource, the connection meet the QoS requirement is set up, and then, the service begin with the actions
of UPC and congestion control.
(3) NP parameters monitoring, reporting, and storage. Once the connection is set up, the OAM functions, periodically
or depending on requirement, monitor and report NP parameter, reflect these parameters to plane management, and store
it to MIB.
(4) QoS notification. Plane management should notify the degraded QoS information to network manager.
3. The extended scheme for OAM performance management
In general, a connection has the route via several networks, which have heterogeneous configurations, topologies and
protocol functions. But in ITU-T I.610, however, the method to select segment boundary is not defined. So, in this paper,
we simply adopt the method that each ingress switching system node can be chosen as segment endpoints according to the
purpose of performance management. As show in Fig.3, segment endpoints can be 1, 4, and 8. We hypothesize that the
route of the VCC connection is (S, 1, 3, 4, 5, 7, 8, 10, D), then the definition of the end-to-end and segment of F5 and F4
flow is shown as Fig.3.
3.1 The extended mechanism
The extended scheme is to monitor more detail information about network performance, to provide it to traffic control
functions, and to support QoS management mechanism. The scheme has two principles described as following.
1. Depending on the purpose of management function, monitoring boundary is switched between end-to-end range and
segment range. End-to-end monitoring is used in the general management mode, while, segment monitoring is used to
find out the switching system at which performance is degraded seriously, after detecting a degradation of performance in
the general management mode.
2. Functions are discriminated between F4 and F5 flow, the functions for F4 flow support network operation
mechanism in view of network provider, meanwhile, the functions of F5 flow should be capable of guaranteeing QoS
required by users at the connection set up phase.
In the case of end-to-end performance management, forward monitoring OAM cells are inserted at the source endpoint,
monitored at the destination endpoint and reported the monitored information to the source endpoint. Intermediate nodes
are each ingress switching systems, and can be set to monitor forward monitoring OAM cells, apply some monitored
results to traffic control functions, and check the status and performance of services in analyzing backward reporting
OAM cells sent by the destination endpoint.
In the case of segment monitoring, the source endpoint selects some intermediate nodes and inform them of using a
field in forward monitoring OAM cell and these selected nodes should sent a backward reporting OAM cell to the source
endpoint immediately. The source endpoint receives backward reporting OAM cells from the selected nodes, extracts
information about traffic congestion and the degree of QoS, and determines whether each switching systems have been
degraded or not.
3.2 Activation
In the unused field of performance management activate/deactivation OAM cell, we define two fields, NC (Node
Counter) and NTB (Node Tag Bit), as showing in Fig.4
NC field is used to count the number of nodes between the source and destination endpoints. The intermediate nodes
and the destination endpoint increase this field by 1 and sent this information to the source endpoint by performance
activation/deactivation confirm OAM cell. This field is finally applied to TNC (Total Node Counter) field of forward
monitoring OAM cell. NTB field is used to distinguish the sequence of nodes by bit position. This field is applied to the
NTB field of forward monitoring OAM cell to determine the boundary of segment in the case of segment monitoring
mode.
3.3 Monitoring/Reporting function
Monitoring and reporting functions are defined differently according to monitoring range, end-to-end or segment
mentioned in section 3.1. There, we define new fields in forward monitoring OAM cell and backward reporting OAM cell.
Fig.5 shows these new fields.
RF is a range field and it means whether monitoring scope is end-to-end or nor. SCT (Service Class Type) is to classify
the service types. That is, this field allows a service provider to provide users with more flexible service. This field
determines a set of monitoring and reporting parameters with relation to the next field, POBF (Parameter Optional Bit
Field). Some bits set in POBF field means parameters monitored and reported by the destination endpoint. For an example,
using SCT and POBF fields, the class may make use of parameters, minimum cell interval, cell error number, cell loss
number etc.
As being described above, TNC (Total Node Counter) and NTB (Node Tag Bit) fields is obtained from the performance
management activation confirm OAM cell that the destination endpoint sends in the phase of performance management
activation. The source endpoint sets some bits in NTB field of the forward monitoring OAM cell to select nodes as
segment boundary nodes in the case of segment performance management mode.
DS (Delay Stamp) field means the total delay time when the forward monitoring OAM cell pass through switching
systems. Each switching system records the time of ingressive and egressive forward monitoring OAM cell, so the
balance of the two data is the time which forward monitoring OAM cell pass through the switching system. This time
include switching delay and queuing delay, whereas, the propagation delay is easy to get. Therefore, we can get the exact
CTD, and then get CDV [13].
n
CTD   Ti  Cell Propagate Delay
i 1
CNN (Current Node Number) field is used to notify which node sends backward reporting OAM cells. So, the value of
this field is the same as the sequence number that each intermediate nodes and the destination endpoint has incremented
by 1 in the phase of performance management activation. PMR (Parameter Monitoring Result) field is only used in
backward reporting OAM cell and contains monitoring results.
We consider some scenarios applying new fields as followed. In the case of end-to-end performance management mode,
the value of RF field is zero, where NTB field is ignored and monitoring and reporting functions are only performed in the
destination endpoint. The destination endpoint processes monitoring and reporting functions based on the parameters set
in POBF field. The information obtained by monitoring function is encoded to PMF field and sent to the source endpoint.
The source endpoint and intermediate nodes can copy this backward reporting OAM cell to check the degree and the
status of QoS parameters negotiated by connection admission control. In addition, they make use of the information to
support traffic control functions. Of course, reporting information should be translated into analyzed information through
a simple analyzing function defined in section 3.4.
In the case of segment performance management mode, RF bit is set to 1. The source endpoint makes use of NTB field
to notify segment endpoint to intermediate nodes which are chosen as segment endpoint execute monitoring function and
immediately send a backward reporting OAM cell to the source endpoint.
3.4 Analyzing reporting information
The source endpoint having received these backward reporting OAM cells analyzes reporting information and obtains
useful information for QoS management. Through analyzing functions, switching system could extract information such
as CLR (Cell Loss Ratio), CER (Cell Error Ratio), CTD (Cell Transfer Delay), ACR (Average Cell Rate), CDV (Cell
Delay Variation) and so on. They are calculated by the following simple formula.
CLR 
Cell Loss Number
Total User cell
(1)
CER 
Cell Error Number
Total User cell
(2)
CMR 
Cell Misin sertion Number
Total User cell
(3)
n
CTD   Ti  Cell Propa gate Delay
(4)
i 1
ACR 
Total User cell
CTD
4. Conclusions
(5)
Based on the discussion of relationship between QoS and networks performance parameter, an ATM layered QoS
management scheme is proposed. The model’s protocol machine, which supports intelligent and autonomic mechanism
[12], is composed of user plane and control plane. With the machine’s support, the QoS management is divided into layer
management and plane management two levels. It also provides the interfaces among these layers and network
management system. To realize the model, we extend the OAM functions defined in ITU-T I.610. According to this
method, we can extract more detail information of the network performance information and the status of the given
connection. This model emphasizes on the feedback mechanism of ATM network performance monitoring. Some new
added fields defined in reserved field separate the boundaries of end-to-end monitoring and segment-to-segment
monitoring in whole switch system. According to the difference of management goal, the former is called general
management mode, and the latter is used for concrete segment problem monitoring when problem is detected in general
management mode. Our study shows that the improvement is feasible and efficient in QoS management mechanism.
This scheme, however, might increase processing load of switching systems and let switching systems more complex.
Therefore, studies about optimized architecture linking this scheme with related QoS management should be done
continuously, and then encoding method of monitoring/reporting parameters will be required in the future.
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Acknowledgements:
This paper was aided by national “95” key project (No. 97-769).
Vitae:
Zhao Yang was born in Jinan, P.R.China, on May 8, 1969. He received his B.S. degree in computer science from
Shandong University, Jinan, China, in 1991, his M.S. degree in computer science from Shenyang Institute of Technology,
Shenyang, China, in 1997. He is currently completing his studies towards the Ph.D. degree in computer science at the
Northeastern University, China. His research interests include broadband networks and services, distributed systems and
network management.
Wang Guangxing was born in Liaoning, P.R.China, on April 2, 1937. He graduated from Northeastern University,
Shenyang, P.R.China, in 1958, majoring in electrical engineering. Since 1958 he has been with the Northeastern
University where he is currently a professor and the Director of the Key Lab. of Networks and Communication. From
1980 to 1982 he was a visiting scholar in the Department of Electrical Engineering and Computer Science at the RPI, Troy,
USA. He is a member of the IEEE Communication Society. His research work is in the area of digital information
transmission and communication networks.
Contact Information:
Name: Zhao Yang
Title: Mr.
Address: Northeastern University, Shenyang, China, 427#
Postal code: 110006
Telephone: +86 024 23893000 7779 or +86 024 23955416
E-mail address: zhaoyang@ramm.neu.edu.cn or dr.zhao@263.net