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Analysis and Optimizations of Presence Generated Traffic for Cellular Networks

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Analysis and Optimizations of Presence Generated Traffic for Cellular Networks 2005:021 CIV MASTER'S THESIS Analysis and Optimizations of Presence Generated Traffic for Cellular Networks David Henriksson Luleå University of Technology MSc Programme in Engineering Department of Computer Science and Electrical Engineering Division of Computer Communication 2005:021 CIV - ISSN: 1402-1617 - ISRN: LTU-EX--05/021--SE Master’s Thesis Analysis and Optimizations of Presence Generated Traffic for Cellular Networks David Henriksson Luleå University of Technology January 28, 2005 Supervisor: Jan Christoffersson, Ericsson Research, Luleå Examiner: Pierre Fransson, Luleå University of Technology Department of Computer Science and Electrical Engineering Division of Computer Science and Networking Abstract Presence services have grown increasingly popular during the last decade and today there exist several implementations designed for the Internet. When de- signing a presence service for cellular networks, new aspects regarding limited network resources and compatibility have to be considered. In this master’s thesis, presence traffic generated according to the Push-to-Talk over Cellular presence specification is analyzed. Different presence updating models are com- pared through simulations and optimizations in the form of limiting unnecessary messages are suggested. The presence impact on WCDMA capacity has also been investigated by comparing the resources needed for presence and Voice over IP generated traffic. The results show that mechanisms for limiting the number of presence messages are needed, either by throttling the number of presence messages sent or by letting the users perform pulls in order to download the information. Without any kind of message limitation mechanism, presence messages could halve the number of Voice over IP users supported within one radio cell. Depending on the intensities of presence signaling, the decrease in the number of supported users can be limited to between 12 and 30 percent by using throttling and 10 to 17 percent using pull. Acknowledgements I would like to thank the following people for their support and ideas during the work of this thesis: – Pierre Fransson, examiner at Luleå University of Technology for his thor- ough review and suggested improvements regarding this report. – my supervisor Jan Christoffersson at Ericsson Research for his advice and help during the thesis work. – all employees at Ericsson Research Luleå. – family and friends. Luleå, January 2005 David Henriksson i Contents Contents iii List of Tables v List of Figures vi 1 Introduction 1 1.1 Background.............................. 1 1.2 Objectives............................... 1 1.3 DocumentOutline .......................... 2 2 Background 3 2.1 Presence................................ 3 2.2 PresenceInformation. .. .. .. .. .. .. .. .. .. .. 3 2.3 Standards............................... 4 2.4 PresenceApplicationsandProtocols . 5 2.4.1 Jabber............................. 5 2.4.2 OSCAR............................ 5 2.4.3 WirelessVillage ....................... 6 2.4.4 WindowsMessengerandMSNMessenger . 6 2.4.5 SIPTheSessionInitiationProtocol . 6 2.4.6 Signaling Compression (SigComp) . 8 3 Presence Generated Traffic and Presence Models 9 3.1 Pull-BasedPresenceServices . 9 3.2 Push-BasedPresenceServices . 10 3.2.1 Push-Throttle. .. .. .. .. .. .. .. .. .. .. 10 4 PoC Presence Specification 11 4.1 MessageExchangeinPush-basedModels . 11 4.1.1 Registration ......................... 12 4.1.2 PresenceEvents ....................... 13 4.1.3 Re-Registration. 13 4.1.4 De-Registration. 14 4.2 MessageExchangeinPull-basedModel . 15 iii 4.2.1 Pull .............................. 16 5 Optimizations and Improvements 17 5.1 Re-Registrationsin Push-basedSystems . 17 5.2 Re-Registrations in Throttled and Pull-based Systems . ..... 17 5.3 De-registrations............................ 18 5.4 PullPartialNotifyUpdates . 18 6 SIP Presence Simulator 19 6.1 SimulationInputs .......................... 19 6.2 SimulationOutputs.. .. .. .. .. .. .. .. .. .. .. 19 6.3 ProgrammingLanguageEvaluation. 21 6.4 Principles of Operation and Design of the Simulator . ... 22 6.4.1 SystemOverview. .. .. .. .. .. .. .. .. .. 22 6.4.2 Operation........................... 24 6.4.3 SimulationEvents . 24 6.5 VerificationofSimulatorCorrectness . 25 7 Estimating Presence Traffic 27 7.1 TrafficGeneratedinPush . 27 7.2 TrafficGeneratedinPush-Throttle . 28 7.3 ComparisonofPushandPull . 31 8 Capacity Comparison of Presence and VoIP 35 8.1 BriefIntroductiontoWCDMA . 35 8.2 TheErlangUnit ........................... 36 8.3 Calculations of Presence and VoIP Comparison . 37 8.4 ResultsofPresenceVoIPComparison . 39 9 Discussion 43 9.1 FutureWork ............................. 44 Bibliography 47 A Calculations of Presence Event Intensity 49 B Verification of Simulation Results 51 C Presence Erlang Capacity Calculations 53 C.1 FormulasforCapacityCalculations . 53 C.2 Erlang Results for High Intensity Calculations. .... 56 iv List of Tables 6.1 Overview of the SIP Presence Simulator parameters. ... 20 7.1 The benefits gained at different throttling intervals at a group size of 20 users, measured in number of messages per hour and user................................... 30 7.2 The benefits gained at different throttling intervals at a group size of 20 users, measured in kilobytes per hour and user. 30 7.3 The characteristics of the four compared pull models. P.S is short forPartial(Single)Notify. 31 8.1 The number of Erlangs generated per presence enabled user dur- ing registration for downlink channel at group sizes of 5, 10 and 15users................................. 39 8.2 Erlangs generated at different traffic generating phases for group sizesat5,10and15users. 40 8.3 Theoretical number of concurrent low intensity presence and pres- ence + VoIP users. Values in percentage represents the decrease of users relative to if no presence service was used. 40 8.4 Theoretical number of concurrent high intensity presence and presence + VoIP users. Values in percentage represents the de- crease of users relative to if no presence service was used. ... 41 A.1 Presence event intensities for state transitions. ...... 49 B.1 Theoretical and simulated results compared. .. 51 C.1 Erlangs generated at different traffic generating phases for group sizesat5,10and15users. 56 v List of Figures 2.1 APresenceSIPSession ....................... 7 4.1 Traffic generating phases in a push presence model with two states. 12 4.2 Messages exchanged during the registration phase. .... 12 4.3 Messages exchanged when a presence event occurs, i.e., a presen- tity updates its presence information. 13 4.4 Messages exchanged during re-registration. ... 14 4.5 Messages exchanged during de-registration. ... 14 4.6 Traffic generating phases in a pull presence model with two states. 15 4.7 a) Messages exchanged during subscription-less pull. The server interprets this as an un-subscription. b) Messages exchanged during subscription-based pull. The server interprets this as a pre-longingofthesubscription. 16 6.1 The data structure where simulation data is stored. The number of messages and message sizes for each type and user is stored in a time slot corresponding to the time of the event. 21 6.2 The figure illustrates how a user moves between the predefined states. The time spent within each state is exponentially dis- tributed with the mean value specified by the simulation inputs. 22 6.3 System Overview of the Presence SIP Simulator. 23 7.1 Traffic generated in a push-only system. a) Average number of messages per user and hour. b) Average number of kilobytes per userandhour. ............................ 28 7.2 Traffic generated in a throttled push system at the throttling in- tervals 1, 5, 15 and 30 minutes. The upper most line in each graph is the un-throttled traffic. The left column show the aver- age number of messages per user and hour and the right column showtheaveragenumberofkilobytes. 29 7.3 The graphs illustrate the intersection value of how often a user can pull the server until the traffic generated exceeds the traffic inthecomparedpushmodel. 32 vi 7.4 The intersection values for low and medium intensity levels. a) Subscription-based PoC model, b) The optimized subscription- basedOpt.I.model. ......................... 33 8.1 Arriving process and service process used for calculating the num- berofErlangs. ............................ 37 8.2 Messages propagated in uplink and downlink channel during reg- istration. The “200OK” messages are marked with a P, S or N, describing an acknowledgement for a Publish, Subscribe or Notify message................................. 38 C.1 Reservation of uplink and downlink channel when receiving push notification. .............................. 53 C.2 Reservation of uplink and downlink channel when receiving throt- tlednotifications.. .. .. .. .. .. .. .. .. .. .. .. 54 C.3 Reservation of uplink and downlink channel when receiving pull notifications. ............................. 55 vii Chapter 1 Introduction 1.1 Background Presence is a service where users can subscribe to presence information and receive updates of other users’ current state. The state of the user can, depend- ing on the implementation, hold information on whether the user is online or not, current mood or geographical location. Today there exist several presence implementations designed for the Internet but unfortunately, the majority of them are incompatible with each other. When designing a presence service for cellular networks, new aspects regarding limited network resources and compat- ibility have to be considered. Presence
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