Proposal of a Queueing Model for Simulation ofAdvanced Telecommunication Services over IMS

ArchitectureLubos Nagy, Jurgen Tombal, and Vit Novotny

Abstract—This article presents the implementation of a de-signed model for the simulation of three telecommunicationservices (File Transfer, Video on Demand and Voice over IP) usinga queueing theory. The main objective of this article is modellingand simulations of IMS (IP Multimedia Subsystem) networkbased on single servers (with a Poisson distribution of jobarrivals and an exponential job service time) with FIFO queuesof unlimited capacity in Matlab environment. Also, for IMSperformance improvement new algorithms for S-CSCF selectionwere designed and implemented in this mathematical model ofIMS subsystem. The results of designed algorithms obtainedby simulations are evaluated and compared with each other.It was shown that new algorithms improved IMS performancecompared with standardized solution.

Keywords—IP Multimedia Subsystem, Queueing Theory, FileTransfer, Video on Demand, Voice over IP.

I. INTRODUCTION

TODAY’S trends in telecommunication lead to the conver-gence of different network technologies and the integra-

tion of a large number of different services. The IP MultimediaSubsystem is a solution to this convergence of fixed andmobile technologies and concurrent services.

The IP Multimedia Subsystem (first time defined by 3rdGeneration Partnership Project in specification Release 5)represents a generic layered architecture that enables varioustypes of advanced telecommunication services to be combinedwith different access networks and different end-devices basedupon the use of Internet-based protocols (including SIP -Session Initiating Protocol) [1].

The wide variety of supported advanced services (IPTV,VoIP, PoC (Push-To-Talk over Cellular, sometimes called asPress-To-Transmit), Multimedia Messaging, conferencing andetc.) and also safe communication are the main benefits ofIMS for users [2]. The main benefits of IMS from an operator

Manuscript received February 21, 2013. This research is part of the projectreg. no. CZ.1.07/2.3.00/20.0094 and is co-financed by the European SocialFund and the state budget of the Czech Republic. Also, this work wassupported by Ministry of Education, Youth and Sports of Czech republicunder project SIX no. CZ.1.05/2.1.00/03.0072.

L. Nagy is a PhD student at the Department of Telecommunications at theFaculty of Electrical Engineering and Communication of Brno University ofTechnology in the Czech Republic. (E-mail: lubos.nagy@phd.feec.vutbr.cz).

J. Tombal is with the division Electonics-ICT and Energy Technologyat the Department of Industrial Sciences and Technology at the Lim-burg Catholic University College of Diepenbeek in Belgium (E-mail: jur-gen.tombal@khlim.be).

V. Novotny is with the Department of Telecommunications at the Faculty ofElectrical Engineering and Communication of Brno University of Technologyin the Czech Republic. (E-mail: novotnyv@feec.vutbr.cz).

point of view are the security (authentication and authorizationmechanisms), unified and improved charging policy (onlineand offline mechanisms), radio bearer with optimized QoSsupport, service control, etc.

The main motivation of this article is the design of aqueueing network model of a home IMS network in Matlabenvironment and proposal of new algorithms for S-CSCFassignment based on load balancing of S-CSCF defined in [3].Also, this article describes the proposal of a queueing networkmodel to simulate telecommunication services over the IMSnetwork.

II. OVERVIEW OF THE IMS ARCHITECTURE

The IMS is usually divided into three layers [1]: transport,control and application layer. Sometimes, the device layer,also known as the user plane, is added into the horizontalmodel of the IMS network. In this case, this layer representsthe different users equipment such as personal computers,mobiles, tablets, digital or traditional analog phones and othermultifunctional devices.

The transport layer represents the various types of trans-mission media such as WiFi, DSL, PON/GPON, GPRS,WCDMA, etc.

The control layer contains some of the most importantentities of the IMS architecture: the CSCF (Call SessionControl Function) servers and the HSS (Home SubscribeServer) databases. These elements together form the basis ofthe IMS core.

The first main elements of the control layer are the CSCFservers which are mainly responsible for the session androuting management. They can be further divided into four el-ements: Proxy-CSCF, Interrogating-CSCF, Serving-CSCF andEmergency-CSCF server [1]. The main functions of a P-CSCF server are SIP compression, IPsec security association,communication with the PCC (Policy and Charging Control)element and emergency call detection. This SIP server is alsoresponsible for discovering through DNS of the I-CSCF in thehome network [1]. The I-CSCFs are responsible for assigningthe S-CSCF address (based on communication with the HSS),routing requests to S-CSCF or application servers and hidingthe structure of the home network [1]. Also, the I-CSCFperforms the support of load balancing of S-CSCFs serversfor initial registration requests. The information needs forload balancing may be obtained via management, proprietaryinterfaces or via other mechanisms [3]. The most important

326978-1-4799-0404-4/$31.00 ©2013 European Union TSP 2013

element of the CSCF servers is the S-CSCF. This central entityof the CSCF servers is mainly responsible for communicationwith the application servers (through ISC interface), storingthe service profile and making routing decisions based on iFC(initial Filter Criteria) [1]. The selection of the S-CSCF nodeis performed in the I-CSCF using six types of following in-formation [3]: required capabilities for user services, operatorpreference on a per-user basic capabilities of individual S-CSCFs in the home network, topological information of wherea user is located, topological information of where the S-CSCF is located and availability of S-CSCFs. The S-CSCFis selected by I-CSCF in three main cases: during registration,during execution services for unregistered users or when S-CSCF is not responding (error or fault cases). All neededcapability information (mandatory and optional capabilities)is transferred using Cx interface (between HSS and I-CSCFservers) within grouped AVPs - Server-Capabilities AVP [4].The last element of CSCF is the E-CSCF server. This serveris used to handle the emergency request in the IMS networks[1].

The second main element of the control layer is the HSSdatabase. The HSS is used to store the main user data (thepublic and private identities, registration information, etc.) ofthe IMS network. This element of the IMS core is connectedto the S-CSCF and I-CSCF through the Cx interface and tothe application servers (AS) through the Sh interface. In bothinterfaces, the communication is based on the DIAMETERprotocol [4], [5]. The number of HSS databases in the IMScore depends on the number of stored users. If the IMS corecontains more than one HSS database, then it is necessary touse SLF (Subscription Locator Function). This element of thecontrol layer is responsible for finding the address of a HSSwhere a specific user is stored [1], [6].

The application layer (sometimes called service layer) isplaced on the top of the IMS architecture. This layer provideswith the help of the application servers the various typesof advanced services such as Presence, Instant Messaging,Push over Cellular, and others services. Some examples ofapplication servers are: SIP Application Servers, Open ServiceAccess-Service Capability Server (OSA-SCS), IP MultimediaService Switching Function (IM-SSF). This layer also providesthe interface for the communication with the control layer(CSCF) using the SIP protocol [1], [7].

In the next part of this article, the four-layer architecture ofthe IMS network will be used to describe our designed model.More information about the other important elements of theIMS architecture can be found in [1], [7], [8], etc.

III. IMPLEMENTATION OF THE IMS MODEL

The proposed model is based on the queueing theory.This theory is often used in mathematical studies of varioustelecommunication systems. In the case of [9], access nodedimensioning for IPTV traffic using effective bandwidth wascalculated using the queueing theory. In the cases of [12](using VNUML), [10], (using OPNET Modeler [11]), thesimple simulations of IMS networks are presented, but thesesimulations were not based on the queueing theory. In our

designed model of the IMS network, each entity is modelledby the M/M/1 queueing system (with a single server andFIFO queue with infinite capacity). The proposed model ofthe IMS network (see subsection III.C) consists of the IMScore, application and media servers and different end-devices.The designed model can be defined as a single class networkof Markovian queues with feedbacks [13]. The M/M/1 systemis briefly described in the next subsection.

A. The Queueing Theory

The queueing model can be defined using Kendalls notation(1) [13].

A/B/C/D (1)

where parameter A defines the arrival time distribution, param-eter B defines the job service time distribution, C is used todefine the number of servers and K determines the maximumnumber of jobs in the queueing system. In the case the systemcapacity is infinite; the queueing network is defined using onlyparameters A, B and C. The most common queueing systemsare M/M/1, M/G/1 or G/M/1.

In the case of an M/M/1 system, the arrival (λ [s−1])and service (µ [s−1]) rates are exponentially distributed. Theimportant parameters (mean response time T̄ , mean waitingtime W̄ and mean queue length Q̄) are shown in equations(2), (3) and (4) [13].

T̄ =

1µ

(1 − ρ)(2)

W̄ =

ρµ

(1 − ρ)(3)

Q̄ =ρ2

(1 − ρ)(4)

Where ρ is the utilization (defined as (λµ ) [13]).

B. Types of Simulated Services

Three of the most commonly used telecommunication ser-vices (File transfer as data service, Video on Demand andVoice over IP) are used to simulate IMS applications in thedesigned model. The architectures of these selected servicescan be divided into two categories:

• client-server (VoD service),• client-client (File transfer and VoIP services).In the proposed model, the primary difference between data

services and VoIP services is that data services are designedas a one-way application. A file (see figure 1) is alwaystransferred from one client (a sender entity) to another client(a receiver entity). In figure 1, the MSRP (Message SessionRelay Protocol) flow represents the file transfer.

In the case of a VoIP application (see figure 1), the voicestreaming (represented using RTP & RTCP flows Real-time Transport Protocol & RTP Control Protocol) is alwaystransferred between two clients (the callee and caller client)in both directions.

A VoD application is designed as a client-server architec-ture. Video streaming is always transferred from the VoD

327

Fig. 1. The simplified flows of three telecommunication services over a homeIMS network for only the SIP INVITE, RTP/RTCP, or MSRP messages.

Media Streaming Server to VoD Applications (see figure 1).All signalling flows of the simulated services are alwaystransferred through the transport layer. This layer is shownin figure 2.

Main signalling of simulated applications consists of SIP,RTSP, RTP and MSRP protocols. Also, the RTCP messages arealways used to simulate the video and voice streaming duringVoD and VoIP services. The main configuration parameters(speed, sending period, etc.) of all generated messages is basedon the analysis of all selected services in test-bed based onopen source tools. All flow sequences of the selected servicesis based on the analysis of these services and on document[14].

Also all simulations of tested services always include thephases of registration, re-registration and de-registration trans-actions (that means with support of the DIAMETER protocol).In the next subsection, the proposal of the IMS model isdescribed in more detail.

C. Proposal of the IMS Model

The model (see figure 2) for simulation of advanced IMSservices (described in the previous subsection) consists of:

• end-device layer (the UEs) with events generator,• transport layer it presents intermediate transport network

technologies and routers,• control layer (two PCSCFs, five S-CSCFs, one I-CSCF

and HSS),• application layer (the application and media streaming

servers AS and MSS used only to simulate the VoDservice).

All elements of the designed model consist of the M/M/1system (a single server and a FIFO queue with infinite ca-pacity), a control unit and a sink (see P-CSCF node in figure2). The main tasks of the control unit are usually used togenerate the response on received requests and the routingmanagement of these responses. For example, the control unitof the S-CSCF element is also responsible for making routingdecisions based on iFC or in the case of I-CSCF, the controlunit performs the selection of S-CSCF servers.

All initial events and whole signalling load (representedby signalling of VoD, VoIP and File Transfer services) aregenerated into the transport layer by the generator (see UEsentity in figure 1) with a Poisson distribution. This distributionis often used to simulation of signalling load for IMS services[15], [16], [17], etc. Also the service rates of all entities are

defined with the exponential distribution. All generated eventsare used to create the messages (SIP, RTSP, RTCP, MSRP, orRTP) in the user entities. These entities are used to simulateall applications (data, VoD and VoIP services). Both all IMSservice nodes and users (UEs VoD, UEs Callee, UEs Caller,UEs Data Sender and UEs Data Receiver) are located withinone IMS network.

The created messages are forwarded to the transport layer.This layer represents the transport layer of the IMS horizontalnetwork (briefly presented in the first part of this article).Also, the basic routing function is simulated in this node ofthe proposed model. The next elements are the CSCFs andHSS servers. These nodes are used to simulate the IMS core.The application layer consists of two servers; a VoD MediaStreaming Server and a VoD Application Server (see figure2). Both servers are used only to simulate video streaming.Both standardized [3] and new designed procedures related toS-CSCF assignment and load balancing algorithms performedby I-CSCF were implemented into the presented model. Thebasic scenario of the S-CSCF selection is shown in figure 3.All S-CSCF servers send the information about their serverutilization (as main performance parameter of single server)and the information about actual number of messages (indeedthese parameters are average measured values and their timeupdate is after message arrival and after message departure)in FIFO queue.

The I-CSCF performs the S-CSCF selection based on threealgorithms. The first algorithm is based only on the lowestactual number of messages in the S-CSCF queues; the secondone is based on selection of the server with the lowest serverutilization. Provided there are more than one server withlowest selection criteria (queue occupation, server utilization)the first one (with lowest ID) will be selected.

The third proposed method of S-CSCF selection is basedon a combination of these two algorithms. Firstly, the queueoccupation is considered and if there is only one server withlowest queue occupation then this server is selected. Providedthere are more servers with the same lowest level of queueoccupation then two of these servers with the lowest IDare chosen for the second round and the server with lowervalue of utilization is selected. This way of selection wasdesigned after evaluation of other methods based on averagelength of queue calculated from beginning of the simulationor various combinations of previous parameters (utilizations,actual number of messages, etc.).

Fig. 3. The scenario of S-CSCF assignment.

328

Fig. 2. The simplified scheme of IMS model (Queue = a FIFO Queue with an infinity capacity; Server = a single server with exponential service rate; CU= a control unit; and Sink used as the output of all dropped events) created in Matlab environment.

IV. SIMULATION RESULTS

In this part, simulation results are evaluated. All imple-mented services (see subsection III.B) are used to illustrate theperformance of the proposed algorithm (see subsection III.C).The most important obtained results of simulations are shownin 4–6 and in tab. I.

The following conditions apply to the presented IMS model:

• The length of simulations is set on 5000 s.• The service times of CSCFs, HSS, AS and MSS nodes are

set to 0.07 s. The service times of others nodes (transportplane, etc.) were set to 0.000001 s.

• The interarrival times are set to values of 0.1 − 0.14 s.• Only standardized signalling traffic (for VoD, File Trans-

fer and VoIP services) is generated by UEs modelled intonetwork.

• As we were concerned in IMS signalling performanceevaluation (SIP and DIAMETER protocol traffic) thesupport of RTP/RTCP and MSRP traffic through thetransport plane was disabled in all simulations describedand evaluated in this article.

• The registrar, re-registrar and de-registrar transactionsare included into each traffic of defined services. Thesetransactions are always initiated by users [3].

• All defined end-users are always situated only in a homeIMS network and they can be divided into two categories:originating (VoD, VoIP Caller and File Sender) andterminating users (VoIP Callee and File Receiver).

• Two P-CSCF servers are included in the IMS model, firstP-CSCF for originating end-users and second server forterminating end-users.

• All six required pieces of information for S-CSCF selec-tion performed by I-CSCF (see section II or [3]) are equalfor each of the simulated S-CSCF servers. All designedalgorithms can be defined as the best fit function basedon two parameters (actual number of messages in queueand server utilization).

• The failure of S-CSCF servers and cancellation of theS-CSCF assignment are not included into this model.

• Emergency service support is not included into this IMSmodel (the SIP CSCFs are designed without E-CSCFfunctionality).

• Only one HSS node is included into the model (the modelis without SLF functionality) and also the Sh interface is

not included into simulation model.• The performance parameters like the delays on the links

between analysed nodes are not included. The analysisof the influence of link parameters on the overall serviceperformance key parameters and possibility to neglect theinfluence of links is presented in [18].

• Neither online nor offline charging architecture is in-cluded into the signalling flow model.

• Also, the DNS and DHCP signalling are not supportedin the simulations.

In figure 4–6, the measured service latency of the wholenetwork is shown for various interarrival times of generatedsignalling load by UEs entity (the measured latency is influ-enced by signalling load of generator and feedbacks insideIMS core, see figure 1) and designed algorithms with andwithout load balancer. Also from obtained results, it can beseen that the minimum of improvement designed algorithmsto the method without load balancer is 7.75 % (see tab. I).

It can be seen that the best algorithm is the algorithm

Fig. 4. The service latency of whole network for designed algorithm basedon actual number of messages in queue.

TABLE ITHE MINIMUM OF PERCENT IMPROVEMENT FOR SERVICE LATENCY

Algorithm Minimal improvement tothe method without loadbalancer [%]

Algorithm based on actual numberof messages in queue

9.39

Algorithm based on actual serverutilization

8.01

Algorithm based on number ofmessages in queue and server uti-lization

7.75

329

Fig. 5. The service latency of whole network for designed algorithms basedon server utilizations.

Fig. 6. The service latency of whole network for designed algorithms basedon actual number of messages and server utilizations.

based on actual number of waiting messages in FIFO queuefor all simulated interarrival times (see figure 4, tab. I). Forshortest values of interarrival time, the best method of S-CSCF selection is algorithm based on combination of theactual number of messages in queue and server utilizations(see figure 6). In this case, the improvement is slightly over15%. The measured service latency of the whole networkwas unstable for shorter values of interarrival times than thesimulated maximum of interarrival time (0.1 s).

V. CONCLUSION

Simulations of three advanced telecommunication services(File transfer as data service, Video on Demand and Voice overIP) in the IMS model based on the queueing network modelwith standardized and new designed S-CSCF selection algo-rithms were presented. The M/M/1 model was used to simulateall entities. All services run within one IMS subsystem. Thismodel was created in a Matlab environment.

Three designed methods of S-CSCF assignment performedby I-CSCF were evaluated in this article. All methods arebased on evaluation of parameters such like the number ofmessages waiting in the server queue or the server utilization.

The analysis showed that the best load balancer method forall measured values of interarrival time is the algorithm basedon the actual number of messages in the FIFO queue (tab. I).However, the algorithm based on combination of algorithmswaiting messages in the queue and service utilization (figure6) was the best for shortest values of interarrival time, i.e. forthe highest system load.

Due the fact that used queueing systems - M/M/1 isonly very theoretical and using queueing network consists ofM/M/1 systems cannot simulate the real conditions in a IMS

network - our future work will be focusing on the modellingof S-CSCF assignment performed by I-CSCF server withM/G/1/K (see (1)) queueing systems. The service times foreach of SIP or DIAMETER signalling over IMS core (foreach IMS node) will be defined with the help of performancetest-beds of an IMS network. Thanks to M/G/1/K queueingsystems and performance test-beds, the designed model willmore correspond with the real IMS network and real networkconditions. Also, proposal of new selection algorithms basedon next important network parameters will be tested andevaluated in the designed IMS network based on M/G/1/Ksystems.

REFERENCES

[1] M. Poikselka, G. Mayer, The IMS: IP Multimedia Concepts and Ser-vices. 3rd ed., Wiley, 2009, pp. 560.

[2] S. Chakraborty, J. Peisa, T. Frankkila, P. Synnergren, IMS MultimediaTelephony over Cellular Systems: VoIP Evolution in a ConvergedTelecommunication World. Wiley, 2007, pp. 370.

[3] 3rd Generation Partnership Project, Technical Specification Group Ser-vices and System Aspects: IP Multimedia Subsystem (IMS) Stage 2.Release 11. 3GPP TS 23.228 (v11.7.0). December 2012.

[4] 3rd Generation Partnership Project, Technical Specification Group CoreNetwork and Terminals: IP Multimedia (IM) Subsystem Cx and Dxinterfaces, Signalling flows and message contents. Release 11. 3GPPTS 29.228 (v11.6.0). December 2012.

[5] 3rd Generation Partnership Project, Technical Specification Group CoreNetwork and Terminals: IP Multimedia (IM) Subsystem Sh interface:Signalling flows and message contents. Release 11. 3GPP TS 29.328(v11.6.0). December 2012.

[6] 3rd Generation Partnership Project, Technical Specification Group CoreNetwork and Terminals: Organization of subscriber data. Release 11.3GPP TS 23.008 (v11.6.0). December 2012.

[7] M. Wuthnow, M. Stafford, J. Shih, IMS: A New Model for BlendingApplications. CRC Press, 2010, pp. 360.

[8] 3rd Generation Partnership Project, Technical Specification Group Ser-vices and System Aspects: Network Architecture. Release 12. 3GPP TS23.002 (v12.1.0). December 2012.

[9] J. Smiesko, J. Uramova, “Access Node Dimensioning for IPTV Trafficusing Effective Bandwidth,” in Scientific Letters of the University ofZilina, Zilina, 2012, pp. 8–16.

[10] T. Macha, L. Nagy, Z. Martinasek, V. Novotny, “DiffServ and IntServMapping in IMS,” in 33nd International Conference on Telecommuni-cation and Signal Processing - TSP’ 2010, 2010, pp. 325–330.

[11] P. Vajsar, J. Hosek, K. Molnar, M. Bartl, “Advanced Trajectory Man-agement Techniques for Mobile Nodes in OPNET Modeler Environ-ment,” in 35th International Conference on Telecommunication andSignal Processing TSP 2012, 2012, pp. 348–353.

[12] F. Galan, E. Garcia, C. Chavarri, M. Gomez, , D. Fernandez, “Designand Implementation of an IP Multimedia Subsystem (IMS) Emulatorusing Virtualization Techniques,” in IEEE, 2006.

[13] G. Bloch, S. Greiner, H. De Meer, S. Trivedi,Queueing Networks andMarkov Chains: Modelling and Performance Evaluation with ComputerScience Applications. WILEY, 1998, pp. 745.

[14] 3rd Generation Partnership Project, Signalling flow for the IP Multime-dia call control based on Session Initiation Protocol (SIP) and SessionDescription Protocol (SDP); Stage 3 (Release 5). TS 24.228 (v5.15.0),September 2006.

[15] A. Munir, A. Gordon-Ross, “SIP-Based IMS Signalling Analysis forWiMax-3G Interworking Architectures,” in IEEE Transactions on Mo-bile Computing, 2010, Volume 9, Issue 5, pp. 733–750.

[16] A. M. Amooee, A. Falahati, “On Total Call Setup Waiting TimeProbability Distribution in IMS Singaling Network,” in 3rd InternationalConference on Next Generation Mobile Applications, Services andTechnologies NGMAST 09, 2009. pp. 33–38.

[17] N. Rajagopal, M. Devetsikiotis, “Modeling and optimization for thedesign of IMS networks,” in 39th Annual Simulation Symposium, 2006.pp. 33–38.

[18] J. Uramova, “Impact of Network State Information on QoS,” in ActaElectrotechnica at Informatica, Issue. 1, Volume 6, 2006, pp. 1–4.

330