Optimization of Multiple Access through ANDSF832450/FULLTEXT01.pdf · Optimization of Multiple Accesses through ANDSF Muhammad Sajid Iqbal . ... BBERF Bearer Binding and Event Reporting

Master Thesis Electrical Engineering June 2011

School of Computing Blekinge Institute of Technology 371 79 Karlskrona Sweden

Optimization of Multiple Accesses through ANDSF

Muhammad Sajid Iqbal

This thesis is submitted to the School of Computing at Blekinge Institute of Technology in partial fulfillment of the requirements for the degree of Master of Science in Software Engineering. The thesis is equivalent to twenty weeks of full time studies.

Contact Information: Author(s): Muhammad Sajid Iqbal Address: Ostergatan 10, LGH 1403, Sodertalje 15243, Stockholm E-mail: [email protected]

External advisor(s): Åke Arvidsson Prof., PhD. Technical Expert Data Traffic Theory Ericsson AB Address: Ericsson Research - KI/EAB/TPP, Färögatan 6, SE-164 80 Stockholm, Sweden Phone: +46 107151897

University advisor(s): Markus Fiedler Senior Lecturer / Associate Professor School of Computer Science and Communications (COM)

School of Computing Blekinge Institute of Technology 371 79 Karlskrona Sweden

Internet : www.bth.se Phone : +46 455 38 50 00 Fax : +46 455 38 50 57

THIS PAGE IS LEFT BLANK INTENTIONALLY

ABSTRACT 3GPP is in the process of enumerating functionality for Access Network Discovery

and Selection Function (ANDSF). The ANDSF includes data management and control functionality which are essential for providing network discovery and selection function to the User Equipment (UE, MS, mobile station) w.r.t. operators’ policy. A lack of quantitative measures of ANDSF benefits was identified so our task is to identify these benefits. The aim of the thesis is to present ideas for how to obtain such measures and we develop a tool which implements (some of) these ideas and finally we have examples of possible results which will support such a discussion with numbers.

This report also discusses different number of use case scenarios (such as ANDSF

and USER) which we implement in our simulation tool. In our simulation model we use to impose preferred strategy, reduced delays and losses, and system utilization efficiency. One more thing likes to clarify that the numbers which we use in our model are just examples. It can be any number but they will give us the same behavior of learning. Providing real gains is outside the scope of our study.

Keywords: 3GPP, ANDSF, UE, MS

ACKNOWLEDGEMENTS

First, of all I am grateful to almighty Allah the greatest of all. Then I would like to thank my supervisor at Ericsson, Åke Arvidsson for his guidance, encouragement, patience and support throughout this thesis work. Next, I would like to thank Patrick Sellstedt, Manager KI/EAB/TPP department, for providing me the opportunity to explore this endless voyage of knowledge.

Second, I would like to thank Sweden giving me an opportunity of studies which gives

me an International exposure and also thanks to Ericsson for giving me confidence to work with their Researchers and give me tremendous experience.

Special thanks to my supervisor at BTH, Dr. Markus Fiedler; who took a keen interest

in the research and shared his vast experiences making the whole work possible. Next, I thanks to all my friends who support me and help me during this process. Finally, I would like to thanks to my Family for always believing in me and support

me and especially my brother Muhammad Majid Iqbal.

Muhammad Sajid Iqbal Stockholm, 2010

CONTENTS Abstract 2 Acknowledgements 3 List of Figures 6 List of Tables 7 List of Abbreviations 8 Chapter 1 Introduction 1.1 General Overview of the Area 11 1.2 Problem Statement 11 1.3 Aims and objectives 12 1.4 Research questions 12 1.5 Research Methodology 13 1.6 Expected outcomes 13 1.7 Thesis outline 13 Chapter 2 Background 2.1 2G 15 2.2 3G 15 2.3 3GPP 16 2.4 Evolved Packet System Architecture 17 2.5 EPC components description 18 2.5.1 Serving Gateway (SGW) 19 2.5.2 Packet Data Network Gateway (PDN GW) 19 2.5.3 Mobility Management Entity (MME) 20 2.5.4 Policy and Charging Rules Function (PCRF) 21 2.6 Access Network Discovery & Selection Function (ANDSF) 22 Chapter 3 Method 3.1 Introduction 24 3.2 Model 24 3.2.1 Access Networks 24 3.2.2 Traffic 25 3.2.3 Access preferences 25 3.2.4 Quality preferences 26 3.2.5 Strategies 26 3.2.6 Scenarios 27 3.3 Customer Arrival Mechanism 27 3.4 Customer Departure Mechanism 28 3.5 ANDSF Scenario 28 3.6 USER Scenario 29 3.7 Arrival Intensities & Mean Holding Time 29 3.8 User case Scenarios 30 3.8.1 User case Scenario 1 31 3.8.2 User case Scenario 2 32

3.8.3 User case Scenario 3 33 3.9 Measurement Parameters 34 3.10 Results 34 Chapter 4 Empirical Study (Analysis) 4 ANALYSIS 35 4.1 Strategy Fulfillment 35 4.1.1 First strategy: Quality first (QoS aspect) 36 4.1.2 First strategy: Quality first (QoS aspect) 36 4.1.3 Comparison first strategy: ANDSF & USER scenario 37 4.1.4 Second strategy: Access first (Mobility/block aspect) 38 4.1.5 Second strategy: Access first (Mobility/block aspect) 38 4.1.6 Comparison second strategy: ANDSF & USER scenario 39 4.2 User Attempts 39 4.2.1 First strategy: QoS aspect 40 4.2.2 Second strategy: Mobility/block aspect 40 4.2.3 Comparison user attempts: ANDSF & USER scenario 41 4.3 Blocking Probabilities 42 4.3.1 First strategy 43 4.3.2 Second strategy 44 4.4 ADAPTIVE strategy 45 4.5 More Comparative Analysis: ANDSF & USER 46 4.5.1 First Strategy 47 4.5. 1.1 1st network acceptance probability 48 4.5. 1.2 2nd network acceptance probability 48 4.5. 1.3 3rd network acceptance probability 49 4.5. 1.4 High quality acceptance probability 49 4.5. 1.5 Low quality acceptance probability 50 4.5.2 Second strategy 51 4.5.2.1 1st network acceptance probability 52 4.5.2.2 2nd network acceptance probability 53 4.5.2.3 3rd network acceptance probability 54 4.5.2.4 High quality network acceptance probability 55 4.5.2.5 Low quality network acceptance probability 56 4.6 Other results 46 Chapter 5 Conclusion & Future Work 5.1 Conclusions & Future Work 57 Chapter 6 References 6.1 Reference 58 Chapter 7 Appendix A 7 RELATIVE HALF SIZE COMPARATIVE ANALYSIS: ANDSF &

USER 59

7.1 Strategy Fulfillment 59

7.1.1 1st Strategy 60

7.1.2 2nd Strategy 61

7.2 User Attempts 62

7.2.1 According to 1st Strategy 63

7.2.2 According to 2nd Strategy 64

7.3 Blocking Probabilities 65



7.4 More Comparative Results 68



LIST OF FIGURES Figure 1.1 General introduction of the problem Figure 2.1 Important targets in mobile network technology design which are

interrelated. Figure 2.2 Evolved Packet System (EPS) Architecture. Figure 2.3 Key PCRF interfaces. Figure 3.1 Quality first (QoS aspect). Figure 3.2 Access first (Mobility/block aspect). Figure 3.3 Customer arrival mechanism Figure 3.4 Customer departure mechanism Figure 3.5 ANDSF Scenario Mechanisms Figure 3.6 USER Scenario Mechanisms Figure 3.7 Accepted User Scenario for the first time Figure 3.8 Finally User request accepted Figure 3.9 User rejected scenario Figure 4.1 First strategy: QoS aspect w.r.t. ANDSF scenario. Figure 4.2 First strategy: QoS aspect w.r.t. USER scenario. Figure 4.3 Second strategy: Mobility/block aspect w.r.t. ANDSF scenario. Figure 4.4 Second strategy: Mobility/block aspect w.r.t. USER scenario. Figure 4.5 First strategy user attempts: QoS aspect w.r.t. USER scenario. Figure 4.6 Second strategy user attempts: Mobility/block aspect w.r.t. USER

scenario. Figure 4.7 1st strategy blocking comparison: ANDSF and USER. Figure 4.8 2nd strategy blocking comparison: ANDSF and USER. Figure 4.9 Static strategy. Figure 7.1 First strategy: 1st access network acceptance probabilities Figure 7.2 First strategy: 2nd access network acceptance probabilities Figure 7.2 First strategy: 3rd access network acceptance probabilities Figure 7.4 First strategy: High quality acceptance probabilities Figure 7.5 First strategy: Low quality acceptance probabilities Figure 7.6 Second strategy: 1st access network acceptance probabilities Figure 7.7 Second strategy: 2nd access network acceptance probabilities Figure 7.8 Second strategy: 3rd access network acceptance probabilities Figure 7.9 Second strategy: High quality acceptance probabilities Figure 7.10 Second strategy: Low quality acceptance probabilities

LIST OF TABLES Table 2.1 An example for ANDSF data (access network discovery information). Table 3.1 Access networks with respective bandwidths. Table 3.2 Access networks preferences. Table 3.3 Quality preferences with respective classes. Table 3.4 Arrival Intensities and Mean Holding Time w.r.t. Classes

LIST OF ABBREVIATIONS 3GPP 3rd Generation Partnership Project AF Application Function ANDSF Access Network Discovery and Selection Function BBERF Bearer Binding and Event Reporting Function EDGE Enhanced Data Rates for GSM Evolution eNB enhanced Node B EPC Evolved Packet Core ETSI European Telecommunications Standards Institute GGSN Gateway GPRS Service Node GPRS General Packet Radio Service HSDPA High-Speed Downlink Packet Access HSPA+ Evolved High Speed Packet Access HSPA High-Speed Packet Access HSS Home Subscriber Server HSUPA High-Speed Uplink Packet Access I-WLAN WLAN list LTE Long Term Evolution MCC Mobile Country Code MME Mobility Management Entity MNC Mobile Network Code NAP Network Access Provider NAS Network Access Server NSP Network Service Provider PCC Policy and Charging Control PCEF Policy and Charging Enforcement Function PCRF Policy Control and Resource Function P-CSCF Proxy Call Session Control Function PDN GW Packet Data Network Gateway QCI QoS Class Identifier QoS Quality of Service RAN Radio Access Network SAE System Architecture Evolution SDFs Service Data Flows SDOs Standards Developing Organizations SGSN Serving GPRS Service Node SGW Serving Gateway UE User Equipment UMTS Universal Mobile Telecommunications System

Chapter 1: Introduction

1.1 General Overview of the Area The main difference in accessing a network today and in few years time is,

availability of different access networks (e.g. WiFi networks as well as LTE networks), which can be accessed at the same time, while all these different access networks will controlled by a 3GPP compliant core network. The operators of several networks will be able to roam traffic between various 3GPP-based different access networks (e.g. GSM, UMTS and LTE) and also among non-3GPP different access networks (e.g. CDMA, WiFi and WiMax). It will also help operators in load balancing of traffic among these different access networks and to meet the requirements of mobile users for increase in bandwidth for their mobile applications.

In order to understand the general overview of the area, we will discuss figure 1.1.

Figure 1.1 General introduction of the problem

Figure 1.1 describes how different access networks working as well as WLAN connectivity at Core network. At User equipment side there are generally two functions ANDSF and PCRF which help users for selection of different access networks on the basis of availability.

In the near future, a significant growth is expected in these different wireless

access networks. 3GPP will facilitate mobile devices to connect and to exchange data through multiple different access networks. In order to meet the demand of the operators w.r.t. these different access networks, Evolved Packet Core (EPC) is a multi-access core network based on IP and standardized by 3GPP, it is also use to accommodate both 3GPP (LTE,..) as well as non-3GPP (Wi-Fi,..) access networks.

EPC architecture also provides mobility of users that is based on the coordination

among network and application layer. Generally, information regarding handover is separate from existing mechanism from network state as well as service requirements. Mobile devices use to control handover mechanism (which ensures service continuity over the physical, data link and network layer).

The PCRF is a control plane node, having rules from a database. PCRF is a very

intelligent node because it takes decision for a user with respect to IP traffic. PCRF can also guide the PCEF in the user plane regarding rules. The PCEF is located and controlled by the home network. The PCRF sends message to the PCEF in order to provision PCC rules (including QoS rules). The PCEF answers with a message indicating success with the installation of the PCC rules. ANDSF having data for non-3GPP access networks discovery and policy data for non-3GPP access (regarding inter-system mobility). According to classical configuration, both PCRF and ANDSF are separate nodes having their data locally; with the exception PCRF that uses the Sp interface in order to get data from its database.

1.2 Problem Statement There are two main aspects w.r.t. technical features that need to be addressed when

a multimode UE connects to the core network through multiple different access networks.

1. A UE uses to discover different available access networks in an efficient

way; and it is very true, due to continuous search for different access networks usually devices has battery draining problems. Therefore due to the fact a UE must know about different access networks according to its location.

2. In order to provide high quality service, there should be an appropriate

access network to be selected. It is also desired that the selection for access network should happen in a simple way without involvement of the end user; therefore there should be an automatic method for access network selection.

In release 8 of 3GPP, Access Network Discovery and Selection Function

(ANDSF) is an optional network selection function; usually it is used to support non-3GPP access networks. The selection procedure of the 3GPP access network depends on the connectivity state of the UE [2]. The aim of the thesis is to identify quantitative measures of ANDSF benefits. The report also presents ideas for how to obtain such measures and we develop a tool which implements (some of) these ideas and finally

we have examples of possible results which will support such a discussion with numbers (simulation tool output).

The main objective of the thesis is to develop a simulation tool that is based on

mathematical and statistical models. It will simulate the different loads in a network. The work will comprise of developing the mathematical / statistical models, implementing them in a simulation tool and running simulations in order to develop scientific conclusions.

1.3 Aims and objectives Developing simulation tool based on mathematical/statistical model and run different simulation scenarios in order to develop conclusions. In order to complete objective I have sub-goals which already Ericsson mentioned:

We model the problem as a population of users and a network state matrix. The user population can be divided into a distinct number of classes where each class is characterized by a flow arrival rate, a flow holding time, a set of codec rates, a set of network accesses and a search order which specifies the order in which various accesses and codecs are tried until a request is accepted or abandoned. The network state can be described by a matrix with accesses as rows and codecs as columns and where each element is a set (c,C) where c is the number of flows in progress and C is the permissible number of flows.

The model can be studied by simulation models and, to some extent, by analytical models.

The simulation model can, at least in the initial study, be implemented as a (fast) Markov simulation with essentially three events; arrival, departure and sample. For arrivals, a class is drawn at random after which a class specific search order for free bandwidth is executed according to the specified search order. The number of searches and the final outcome are recorded for each arrival. For departures, a flow is picked at random. Successful arrivals and departures are followed by updates of the number of flows in progress as well as the total disconnection rate. For samples, the utilization of the different networks is recorded.

We consider a scenario where different classes of users can choose between different QOS classes (corresponding to different codecs and thus different bandwidths) and different access. We would like the system as a whole to admit as many service requests as possible with as high QOS as possible, after as few attempts as possible. A fundamental observation is the fact that the bandwidth of each access can be characterised as a maximum number of flows of each QOS class.

1.4 Research questions RQ1: What are the main challenges that can affect in order to develop simulation tool? RQ2: How analytical teletraffic model will be used to check the relevance of a proposed scenario before it is simulated? RQ3: What are the scenarios which will help us to develop scientific conclusions regarding simulation?

1.5 Expected outcomes Once the models are developed and tested, they should be used to produce estimates of the possible gains obtained from various forms of "smart searches" where, e.g., heavily used

accesses are avoided.

1.6 Research Methodology The main goal to adopt research methodology is to produce new knowledge, and there are three main forms of research methods:

• Exploratory research, It identifies problems in the system. To better understand what

implications different "join/duration/leave" distributions will have on the load and performance of these networks we need to simulate different such scenarios.

• Constructive research, It develops solutions to a problem. Here we are using two models

simulation model as well as analytical model in order to develop solution to a problem. The simulation model can, at least in the initial study, be implemented as a (fast) Markov simulation. The analytical model may be based on classical.

• Empirical research, By using empirical evidence we will test feasibility of a solution. When we will

develop simulation model then it is used to produce estimates of the possible gains obtained from various forms of "smart searches".

1.7 Chapter Organization Chapter 1, Introduction: a general introduction of the area, problem statement

describes actual aim of the thesis, discusses problem solving approach, and at last describes chapter organization throughout the report.

Chapter 2, Background: a brief section that gives the necessary background

information about our research area especially what have been done before? Chapter 3, Method: This section provides the detailed experimental and research

work, simulation design, and how we are implementing the ideas and approaches. Chapter 4, Empirical Study (Analysis): This section provides the detailed analysis

and evaluation of simulation results. Chapter 5, Conclusion and Future work: provides what we have learned, did we

meet our goals, what are the suggestions about the research area, what we have untouched in the research area? Which will be the future work?

http://en.wikipedia.org/wiki/Exploratory_research

http://en.wikipedia.org/wiki/Constructive_research

http://en.wikipedia.org/wiki/Empirical_research

Chapter2: Background

2 BACKGROUND

2.1 2G

1. GSM:

The story of Global System for Mobile Communications (GSM) is exceptional and distinguished by individual experience to practically 100% of the inhabitants in industrialized countries, and an escalating portion of that in emerging countries. GSM (see e.g. [10] for a detailed overview) provides narrowband, real-time as well as circuit-switched network connectivity in order to provide speech communication in wide areas; it is also used to provide users mobility from fixed to fast-moving as well as worldwide roaming. In 2009, high numbers of GSM networks were in function and GSM networks made lots of extensions in order to enable data communication, but the success was inadequate due to limited services.

2. GPRS:

General packet radio service (GPRS) use to provide connectivity to packed data networks for mobile users and even IP networks (e.g. Internet) too. The data rate is up to 172 Kbps in theory, but with respect to operators point of view 8 logical channels hardly ever got allocated to one user. One of the major jamming points was lofty charges, which are still disproportionate in roaming since today.

GPRS is a way to 3G networks and according to operators point of view it also

gives an idea to implement core architecture that should be IP-based for data applications which can be used to elaborate 3G services for data as well as integrated voice applications. There are many features in GPRS that can be used to describe wireless packet data:

• It is an upgrade to existing systems. • It is also an integral part of a future 3G system. • It also gives online feature that one can be connected on a permanent

basis. • It has an open architecture, integrated internet and telephony

infrastructure. • It is also a first step towards an end to end wireless architecture.

GPRS can be seen in the region of 2.5G. For a detailed description of the GPRS

technology, see e.g. [11]. GPRS offers user-friendly billing mechanism as compare to circuit switched

services. According to circuit switched services, billing depends on the duration of the connection which is not suitable as this way; a user has to pay for whole airtime, even for idle periods. According to packet switched services, billing is only based on the transmitted data.

Incremental optimizations were made for both GSM (based on circuit switched

network) and GPRS (based on packet switched network), even EDGE provides higher modulation efficiency, but there is no major changes essentially made by these technologies.

2.2 3G UMTS: Universal Mobile Telecommunications System (UMTS) is the 3rd generations

(3G) technology for mobile networks (for detailed description see [12]), based on a new radio technology (which is called Wideband CDMA) it also has many features and some of them are given below:

• It provides maximum bandwidth for the operator and also has high data

rates for the end user due to its new radio spectrum. • It also provides a maximum data rate up to 2 Mbps under best

circumstances. • Its network architecture also provides integration among Circuit Switched

network and Packet Switched network with respect to data transmission. • Its complete service control layer was created in IP Multimedia Subsystem

(IMS). UMTS services are based on user and radio environments; in UMTS the network

user will experience a consistent set of services during roaming. UMTS is appreciated as a global system which contains both components of terrestrial and satellite. The radio interface UTRA of UMTS provides high spectral efficiency and service quality. UMTS is used to ensure an efficient and effective roaming and handover services between terrestrial networks and satellite.

HSPA: High Speed Packet Access (HSPA) provide higher data rates, HSDPA is for

downlink, HSUPA is for uplink and HSPA+ based on even more refined radio schemes. HSPA+ was standardized with 3GPP Rel. 7, HSUPA in Rel. 6 and HSDPA in Rel. 5. 3GPP Rel. 9 is also used to complement the LTE/SAE work.

The acceptance of 3GPP networks is due to the fact of high security as well as

distinctive subscriber identification. However, it is true that the security in 2G as well as in 3G has a wide variation in strength. For the development of a new system only the top level of security is allowed. In case of comparative study of any system, one should always keep the same level of functionality. Therefore when the 3GPP access networks with the non-3GPP access networks the additional functionalities or nodes for integration must be considered in order to evaluate both systems.

In the following, we describe some of the key accepted requirements for 3G

networks; it provide an efficient and exiled services anywhere at any time depending on the requirements. It also provides wide provision of services from low to high bit-rates which definitely cannot be fulfilled by first as well as second generation systems. It is true at some point that evolved 2G systems (like GSM with an enhanced version with GPRS, HSCSD and EDGE) will meet these requirements efficiently; however, multimedia services which usually require high as well as variable bit-rate will remain challenging.

3G was initially believed to become a single worldwide standard, but this

visualization has not fully materialized. We are now basically dealing with two standards; 3GPP and 3GPP2 3GPP provides a route for GSM networks to UMTS networks, and 3GPP2 is leading from cdmaOne to cdma2000. In theory over the air interface, 3G systems can sustain high bit-rates relatively too wideband carriers.

However, in practice 3G spectrum supports up to 2 Mbps only if the targeted user close to micro cell base stations or served by Pico-cells provided to stationary positions.

2.3 3GPP The 3GPP created in December 1998 which is one of the global standardization

initiatives. It’s essential task was to develop a complete technical specifications for 3G mobile networks, based on the evolved GSM core network and UTRA which is an innovative radio interface. The main aim of the project was to develop a better relation as well as co-operation among regional standard organizations and other industry groupings. 3GPP also collaborate with different activities between recognized SDOs, with the encouragement of industry groups as well as other individual members.

In November 2004 in Toronto: where network operators, manufacturers and

research institutes started with a workshop for 3GPP’s RAN (Radio Access Network), and the first set of requirements were compiled. It was decided that there is a demand for the evolution of the mobile core network. Before starting the actual proposal of the evolved system, 3GPP performed studies for the packet core network and the evolution of UTRA/UTRAN. In June 2006 and December 2006, these studies were concluded and documented in 3GPP TS 23.882 [4] and 3GPP TS 25.913 [5] respectively.

There are subsequent pertinent factors for competitiveness was seen in more than a

decade [3]:

• It improved system coverage as well as capacity. • It reduced latency for both user’s plane and control plane. • It provides more flexibility in radio spectrum. • It also provides high user data rates. • It has reasonable power consumption and terminal complexity. • It also reduced cost for the operator.

The three most important targets in mobile network technology design are: to

provide security, mobility and Quality of Service (QoS). These targets are fully interlinked with each other, as it is shown in figure 2.1.

Figure 2.1: Important targets in mobile network technology design which are

interrelated [3].

2.4 Evolved Packet System Architecture The main objective of the system architecture in 3GPP is not just to describe an

efficient packet core network as well as RAN architecture for LTE in order to meet the requirements described in [13]; but it is also use to develop a frame of reference for an enlargement and shift of current systems up to following features:

• It is use to develop a packet-optimized system in order to provide low

latency. • It also provides high data rate that use to supports mobility. • It also uses to provide service continuity over heterogeneous access

networks. • It is also envisioned that various access technologies would be use to

provide IP-based services. There are two basic nodes in the user plane in the EPS architecture: eNB and EPS

gateway; eNB contain all radio access functions, and EPS gateway contains the complete bearer plane (i.e., user plane) in the core network. The MME node is logically separated from the user plane and EPS gateway with an open interface between them in the control plane.

Figure 2.2 Evolved Packet System (EPS) Architecture [6].

There is a more detailed view of the EPS architecture in figure 2.2, with the

interfaces that are used to support flexibility between 3GPP and non-3GPP networks. The EPS gateway may be divided into two separate logical nodes: the serving gateway (GW), and the packet data network (PDN) gateway; and there is also optional S5 interface which is use between these logical nodes. There is a core interface towards 3GPP which is terminated by serving gateway and its is also use to serve as a point of local mobility anchor for inter-eNB handover within the EPS, and it is also use to provide mobility anchoring for inter-3GPP. There is a direct control plane interface S3 and user plane interface S4 between the SGSN (which is use to serve GPRS support node) and the EPS network (which is use to server UMTS/GSM networks); these kind of interfaces are use to allow for a packet session to be maintained. In case of a user of a multimode terminal that usually migrates across GSM/EDGE, UMTS/HSPA, and LTE coverage areas. The PDN gateway uses to provide an access to the packet data network and also uses to allocate an IP addresses: it also use to serve as an anchor between 3GPP and non-3GPP access systems for mobility, which is called SAE anchor function.

2.5 EPC components description There are four components of EPC which are given below:

1. Serving Gateway (SGW) 2. Packet Data Network Gateway (PDN GW) 3. Mobility Management Entity (MME) 4. Policy and Charging Rules Function (PCRF)

SGW, PDNGW and MME are described in 3GPP Release 8 while PCRF was

described in 3GPP Release 7. The architectures using PCRF not widely adopted up to now may be in the future. The role of PCRF with the EPC components like SGW and MME is compulsory in Release 8 and essential for the operation of the LTE.

2.5.1 Serving Gateway (SGW) The Serving GW (Gateway) uses to implement the following functions with

respect to QoS and policy-related terms for e.g. QCI, SDF etc. • SGW use to provide intra-LTE mobility anchor as well as inter-3GPP

mobility anchor. • It provides packet routing and forwarding operations. • It offer lawful intercept and also provides a roaming interface. • It provides LTE idle mode with DL buffering mechanism and also provide

charging per UE, PDN and QCI. • It also has a local non-3GPP anchor and in case of PCEF it uses to provide

bearer mapping as defined for PCC.

2.5.2 Packet Data Network Gateway (PDN GW) The PDN GW is the node which is used to enable interconnection towards PDNs;

there are following functions which are common for both variants of EPC protocols. • PDN GW has an external IP point of interconnect and also IP address

allocation. • It provides a mobility anchor from 3GPP to non 3GPP. • It also provides packet routing, forwarding, lawful interception and a

roaming interface. • It use to enforce policies with respect to following ways:

1. Per user packet filtering (DPI) 2. Service level Charging 3. Service level gating control 4. Service level rate enforcement 5. Bearer binding towards 3GPP access as defined by PCC

2.5.3 Mobility Management Entity (MME) The MME (Mobility Management Entity) realizes these functions:

• MME provide authentication, NAS signaling as well as gateway selection. • It also provides roaming from S6a (“This reference point is for

information exchange related to UE’s subscription (download and purge) [3]”) to home HSS.

• It also uses to do bearer management and also perform idle mode tracking function.

• It also performs paging function and provides IRAT mobility as well as inter-MME.

• It also has a security responsibility that’s why it uses to provide NAS ciphering and also performs integrity protection.

2.5.4 Policy and Charging Rules Function (PCRF) According to release 7 of 3GPP, it introduces converged architecture in a new way

which allows interactions between the rules and policy functions. For the First time, Policy and Charging Rules Function (PCRF) were introduced in release 7 of 3GPP; this is a combination of Policy Decision Function (PDF) and Charging Rules Function (CRF).

In release 8 of 3GPP, PCRF functionalities are improved by increasing the functionalities of the Policy and Charging Control (PCC) in order to facilitate non-3GPP different access networks.

There are some key responsibilities of PCRF given below:

• It is used to define charging for each Service Data Flow (SDF), as well as it also sets QoS for each SDF.

• It is used to enables bearer QoS control. • It is also used to create interaction between bearer charging and

application; and it also provides announcement of bearer events with respect to application function.

• Application Function (AF) in figure 2.3 uses to represent network elements that support applications for charging control as well as for dynamic policy.

• AF is an implementation of P-CSCF. Figure 2.3 shows PCRF interfaces with other EPC elements.

Figure 2.3 Key PCRF interfaces.

The main elements in the above architecture are:

• Application Function in the service control layer, • PCRF in the resource control layer, and • PCEF in the transport layer.

There is an extended interface between the PCRF and PCEF [15] as well as between the PCRF and the serving gateway [14] which is based on the Diameter protocol. There are two mode operations; Push and Pull, both mode operations are supported, but there is no mechanism for inter-domain resource reservation. The architecture is mainly for UMTS network and elementary steps have been made in order to consolidate Packet Cable as well as WLAN accesses [16]. The PCRF use to provide signaling connection between services domain and EPC.

The PCRF mention less congested and back up access networks in order to

provide flow establishment. The access network selection was made by the PCRF, and it’s undefined that “how the selection of these alternative access networks were made? [19]” This dilemma highlights another problem as well: during request for an IP flow process, “how can the PCRF trust that the UE is behaving according to the policy rules that the UE received from the ANDSF, especially since the PCRF is not aware of the ANDSF rules? [19]”

Evolved 3GPP system architecture has two main functionalities which are given

below: • There is a choice option for a UE to access different networks regarding

services. • A UE efficiently discover different access networks and select the best

suited one. PCRF only use to provide all these functionalities for the 3GPP access networks.

There is a new Access Network Discovery and Selection Function (ANDSF) has been introduced in order to support non-3GPP access networks, which is an optional function in release 8 of 3GPP.

2.6 Access Network Discovery & Selection Function (ANDSF) ANDSF is also another network function that use to support a UE for finding

different access networks allowed by network operators for best connectivity. There are two categories of data in ANDSF (defined in OMA DM scheme [18]):

1. Inter-system mobility policies: Inter-system mobility policies having

rules regarding the UE by the operator in order to select as access: rules having priorities and only one rule can be active at a time. These rules may include location/area data as well as time windows for their validity. The evaluation of rules results in preferred and restricted access technologies.

2. Access network discovery information:

Access network discovery information use to support UE in order to find the most appropriate and suitable access network for service. It contains information of the access networks which is based on area/location data as well as per potential access technology: the specific items to look for on the radio interface (e.g. SSID is used in case of WLAN, Network Access provider ID is used in case of WIMAX, In case of 3GPP access PLMN/Tracking Area/cell identities are used).

Moreover, the information regarding UE location is contained in the data structure, and it is defined between ANDSF and UE, only ANDSF can get this information. There are several general observations made on ANDSF [3]:

• I-WLAN (for e.g. preferred WLAN list) contains existing lists for user and

operator preferences with respect to different access networks which can be seen as a "dynamization".

• It is use to concern the type of UE that control by the network or, it can be

seen from UE autonomy, and it also gives possibility to have a full range - from fully network centric to fully UE centric.

• Actually the agreement in 3GPP was not to authorize a tight coupling of

the communication between UE and ANDSF w.r.t. handover events. It cannot be eliminate from such kind of communication that usually occurs near to a handover.

• It was defined that the selection for different access networks of non-3GPP

should not interfere with 3GPP's access networks, which are well defined PLMN selection procedures.

The communication from UE to ANDSF can be in push and pull mode; push mode

is ANDSF initiated and pull mode is UE initiated. There is one conceivable problem, if policies are push down to UE and it has not yet been discovered, or it has not yet been IP connectivity and tries to contact ANDSF for pull mode operation. In this type of problem an SMS will be used like a triggering event.

There are three ways to discover ANDSF by UE is either by static configuration,

DNS query or by dynamic configuration DHCP query. In case of DNS query, a specific FQDN was use to defined by 3GPP, which is given below:

"andsf.mmc<MNC>.mcc<MCC>.pub.3gppnetwork.org" [3]. Where MNC stand by Mobile Network Code and MCC stand by Mobile Country

Code of the UE's HPLMN. If case of DHCP query which is used for ANDSF discovery, either through an IP

address or a domain name is given back. In this case another resolution step by a DNS query is necessary.

The security of communication between UE and ANDSF can be guaranteed either

by using the 3GPP defined Generic Bootstrapping Architecture (see 3GPP TS 33.402 [8] and TS 33.222 [9]), or by the OMA DM bootstrap and secure http solution.

UE’s Location Access Type=WiMAX Access Type= WLAN Cell 1 NSP-id 1: NAP-id 1, NAP-id 2

NSP-id 2: NAP-id 2, NAP-id 3 SSID=wlan1,BSSID=bs1 SSID=wlan2,BSSID=bs2

Cell 2 NSP-id 2: NAP-id 3 Not available Cell 3 Not available SSID=wlan1,BSSID=bs3

SSID=wlan4,BSSID=bs4 ……… …………….. …………….. Cell n NSP-id: NAP-id SSID=wlan7,BSSID=bs5 Table 2.1 An example for ANDSF data (access network discovery information)

[3].

How ANDSF data (access network discovery information) could be provided to a UE is given in Table 2.1. We use the WIMAX related abbreviations: NSP and NAP, and WLAN related abbreviations SSID and BSSID. It is left on the reader to sketch the corresponding coverage of accesses.

Chapter 3: Method

3 METHOD

3.1 Introduction The aim of this report is to identify quantitative measures of ANDSF benefits. We

contributed in three ways in order to identify quantitative measure of ANDSF benefits.

1. We develop ideas for how to obtain such measures. 2. We develop a simulation tool which implements some of these ideas. 3. Finally we got examples of possible results.

We derive use case scenarios in order to analyze the impacts from policy nodes (especially PCRF) may have on the ANDSF, when static policies in the ANDSF are taken into account for network selection, in particular in access network reallocation scenarios without UE involvement. We worked on how we can get better gains from ANDSF as compare to USER scenarios. There are three main aspects on which we expect better gains from ANDSF.

1. Impose preferred strategy. 2. Reduced delays and losses. 3. System utilization efficiency.

This report also discusses a number of use case scenarios of ANDSF and USER

where one or more user request flows are not admitted at a given access network. Instead of dropping the flow establishment of user’s requests, the availability of additional access network that may supply to the required resources, and they instruct UE to use such access network instead. Additionally, instead to the failure of the flow establishment the report presents scenarios where the network proactively instructs the UE to transfer to another access network.

In our simulation model we use these aspects and it will be discussed in detailed in

the sequel. One more thing to clarify that the numbers which we use in our model are just examples. It can be any number (output results) but they will give us the same behavior of learning. Providing real gains is outside the scope of our study.

3.2 Model

In order to develop simulation tool our model contains following parameters which are given below:

1. Access networks 2. Traffic 3. Access preferences 4. Quality preferences 5. Strategies 6. Scenarios

3.2.1 Access Networks We use three different access networks w.r.t. bandwidths.

S.No Access Network (s) Bandwidth (s) 1 3G 42 Mbps 2 4G 160 Mbps 3 WLAN 54 Mbps

Table 3.1 Access networks with respective bandwidths.

3.2.2 Traffic There are two traffic terminal types in our model.

1. HandHeld (HH) 2. PC

These two traffic terminals are sub divided into two traffic classes.

1. Web 2. Video

Due to the divisions, we are at four different traffic classes.

1. Handheld web 2. Handheld video 3. PC web 4. PC video

3.2.3 Access preferences According to traffic terminal types access networks are placed into preferences.

Table 3.2 shows access preferences w.r.t. traffic terminal types.

S.No Traffic terminal types

1st Preference 2nd Preference 3rd Preference

1 HH 3G 4G WLAN 2 PC WLAN 4G 3G

Table 3.2 Access networks preferences.

3.2.4 Quality preferences According to quality preferences, traffic classes are sub divided into two

categories high quality and low quality. High quality provides QoS aspect where as low quality work on the Mobility/block aspect. Table 7.3 shows requested bandwidths w.r.t. each traffic class which are given below once again numbers which we use in our model are just examples, it can be any number. S.No Quality Preferences Traffic Classes Bandwidths 1 High HH web 100 kbps

HH video 200 kbps PC web 1000 kbps PC video 2000 kbps

2 Low HH web 25 kbps HH video 50 kbps PC web 250 kbps PC video 500 kbps

Table 3.3 Quality preferences with respective classes.

3.2.5 Strategies There are two strategies defined in the model.

1. Quality first (QoS aspect) 2. Access first (Mobility/block aspect)

In the first strategy, QoS aspect will be considered, as we discuss above in table

3.1 access network preferences like HH (3G, 4G, WLAN) and PC (WLAN, 4G, 3G) where in case of QOS aspect, each access network considered first with high quality and then considered with the low quality. This will shows that in QoS aspect most of users are accommodated with high quality and rest of users provide service with low quality, when there is a chance of blocking occurs.

Figure 3.1 Quality first (QoS aspect).

In the second strategy, Mobility/blocking aspect will be considered where mobility

increases and blocking decreases. In this strategy each access network provided with the high and low quality service and then move on to the next access network and it will also follow the same access network preference which we discussed in table 3.2.

Figure 3.2 Access first (Mobility/block aspect).

3.2.6 Scenarios There are two network scenarios.

1. ANDSF scenario 2. User scenario

According to ANDSF scenario, access network’s selections are in a specified

order. Due to network in specified order, we impose the preferred strategy in order to avoid blocking.

According to user scenario, access network’s selections are in random order. The reason for two network scenarios is to study the quantitative measures of ANDSF benefits. We also perform a comparative study among the two network scenarios so that we can get the reasons for the maximum gain from ANDSF.

3.3 Customer Arrival Mechanism Whenever user arrive and requested for service then there are some steps which

should be fulfilled:

• First it determines an event for example it’s an arrival or departure. • After finding it’s an arrival then user determine class then regarding class

type of preferences will be applied. • Preference list has two major attributes access network and bandwidth. • Each access network has controlled bandwidth which will be provided

w.r.t. user requirement. • Whenever a user request comes and there is not enough bandwidth for the

requested access network then, it will proceed to the next preference and there are maximum six preferences; or if it is the last preference then user request will be rejected.

Figure 3.3 Customer arrival mechanism

3.4 Customer Departure Mechanism Whenever a user arrives for departure then there are also some steps which should

be fulfilled:

• First it determines an event for example it’s an arrival or departure. • After finding it’s a departure then determines class then type of preference

will be selected. • Preference list has two major attributes access network and bandwidth. • When we come to know class and preference number then re-allocation of

the requested bandwidth would be very easy. We already mentioned that each access network has controlled bandwidth and it is deliver w.r.t. user requirement. Whenever user go for departure then requested bandwidth should be re-allocated so that whenever next user will come it will served accordingly.

Figure 3.4 Customer departure mechanisms

3.5 ANDSF Scenario According to ANDSF scenario, there are four different classes respectively (HH

web class, PC web class, PC video class and HH video class). Whenever a user request for arrival comes, it determine user class and with respect to its class access network selection defined.

Figure 3.5 ANDSF Scenario Mechanisms

3.6 USER Scenario According to USER scenario, there are also four different classes as mentioned

above in section 3.6. Each class has six sub classes in order to study the actual behavior with respect to random network selection mechanism. Why we need six sub classes in USER scenario? We already know that in USER scenario network selection is random so in order to implement random behavior for users; we maximize the classes then go for random selection for access network.

Figure 3.6 USER Scenario Mechanisms

3.7 Arrival Intensities & Mean Holding Time In table 3.4 we mention arrival intensities as well as mean holding time with

respect to each class. Each class has arrival intensities (lambda) which will multiply by capital lambda (˄). We can evaluate blocking with respect to each class. We developed a function which will generate exact value for capital lambda that satisfies blocking probabilities with respect to each class. We came to know that classes web HH and video HH has less than equal to 1% blocking and where as in case of classes web PC and video PC has greater than equal to 1% blocking. According to below arrival intensities values with respect to each class, we have capital lambda equal to ˄41. On the other hand mean holding time with respect to all user classes is the same. We choose values λi/µi and scale the values by ˄ so therefore we reach a certain performance level.

User Class

User Class Disc Arrival Rate Mean Holding Time

1 HH web 20*41=820 1

2 PC web 2*41=82 1

3 PC video 1*41=41 1

4 HH video 10*41=410 1

Table 3.4 Arrival Intensities and Mean Holding Time w.r.t. Classes

3.8 User case Scenarios There are some of the user case scenarios which we will discuss in the below

section. The actual idea behind these user case scenarios is to discuss user’s requests, that how system reacts with respect to different user’s requests.

3.8.1 User case Scenario 1 In the user case scenario 1 as shown in figure 3.7, we discussed accepted user’s

request for the first time. Whenever an arrival for user request comes, first its user class identified then it move on to the requested bandwidth. Any user request accepted or rejected on the basis of availability of bandwidth. In the figure 3.7 where user request for a bandwidth and its request accepted for the first time which is definite a best scenario.

Figure 3.7 Accepted User Scenario for the first time

3.8.2 User case Scenario 2 In the user case scenario 2 as shown in figure 3.8, we discussed user request

accepted at last preference. As we discussed above that user request only rejected due to lack of bandwidth. In case of first two preferences there is no availability of bandwidth that’s why it move on to third preference where it finds requested bandwidth. In this scenario user request also avails two level of blocking which is definitely not a good choice. This can be even a bad use case scenario where user at last avails requested service. There is a possibility to avoid blocking almost completely by providing low service (low bandwidth allocation) to customers but this is not our aim. We try to provide quality service at best level of the system utilization. The aim of these scenarios is to provide information to user experience to the system whenever they will request for service.

Figure 3.8 Finally User request accepted

3.8.3 User case Scenario 3 In the last user scenario as shown in figure 3.9, we discussed user’s request

rejected. Here user rejected due to unavailability of bandwidth of the requested access network with respect to each preference. This one is the worse scenario where it shows blocking probability of user’s request.

Figure 3.9 User rejected scenario

3.9 Measurement Parameters These following measurement parameters will be considered:

• Access network utilization. • Number of retrials regarding user request. • Each Preference probability. • Total number of user’s acceptance percentage. • Number of Rejected users.

3.10 Results We will discuss our results w.r.t. these aspects which are given below:

• How well are the strategies fulfilled? • How many attempts are required for users? • Blocking probabilities are compared.

The strategies (QoS and Mobility/blocking aspect) concerns how well users are

accepted for the first time (references).

4: Empirical Study (Analysis)

4 ANALYSIS

4.1 Strategy Fulfillment There are two strategies defined in the model; Quality first (QoS aspect) and

access first (Mobility/block aspect). When we talk about strategy fulfillment w.r.t. QoS aspect then it means that we are preferring users with high quality. If there is blocking in the system then it moves on to the low quality. Mean while we are also comparing results between ANDSF and USER scenarios, that which one providing high quality service w.r.t. acceptance probability.

4.1.1 First strategy: Quality first (QoS aspect)ANDSF scenario Figure 4.1 shows acceptance probability of users according to first strategy w.r.t.

ANDSF scenario. In the horizontal line digits(1, 2, 3) shows sequence of access network preferences with high and low quality likewise we have three different access networks for e.g. 4G, 3G and WLan, ANDSF has static network selection w.r.t. each traffic class in order to avoid blocking. Each bar in the graph represents class of users for e.g. the first bar with color lavender is HH web class and so on. Once user not accepted by first preference access network then it got blocking and it moves to the next access network preference. If we look at the overall graph we come to know that most of users got high quality service. It means that ANDSF fulfill first strategy very well because almost most of users got high quality service which is main objective of the first strategy.

ANDSF

0102030405060708090

1/high 2/high 3/high 1/low 2/low 3/low

1st Strategy

Acce

ptan

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roba

bilit

y HH webPC webPC videoHH video

Figure 4.1 First strategy: QoS aspect w.r.t. ANDSF scenario.

4.1.2 First strategy: Quality first (QoS aspect)User scenario Figure 4.2 shows acceptance probability of users according to first strategy w.r.t.

USER scenario. In USER scenario network selection is random.

As shown in figure 4.2, we know that 1, 2 and 3 use to represent different access networks (4G, 3G and WLan) and that can be any due to its random behavior; there may be possibility a user request’s service that is not fulfill by access network at first order. If we look at the graph below a large number of user’s request accommodated in the second network choice and even more number of user’s requests are accommodated in third network choice as compare to first. The question is why most of user’s served in second and third network choice why not first. The answer is well known to us due to its random network selection; but in case of ANDSF scenario there is no users served by third access network because most of user served with first two network choices. Here we also see a concentration to network 2 and this deviation from the randomness outcome is because some users (in particular high bandwidth PC users) are rejected from 1 and 3 (which have lower bandwidth) but accepted with higher bandwidth. That’s shows a clear difference that ANDSF network selection mechanism is a better way to accommodate user’s request.

User

0102030405060708090

1/high 2/high 3/high 1/low 2/low 3/low

1st Strategy

Acce

ptan

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roba

bilit

y

HH webPC webPC videoHH video

Figure 4.2 First strategy: QoS aspect w.r.t. USER scenario.

4.1.3 Comparison first strategy: ANDSF & USER scenario The first strategy concerns with QoS aspect, here aim is to identify which scenario

fulfils requirements very well. We know in ANDSF scenario network selection is static in order to avoid blocking, as a result in figure 8.1 shows that first two options w.r.t. access networks are enough to accommodate maximum users. ANDSF also has the knowledge of free bandwidth regarding access network, whenever a user request comes, ANDSF come up with the best option w.r.t. user’s requirement. This kind of behavior avoids blocking and fulfill user requirement very well.

On the other hand, USER scenario has no information about free bandwidth in the

network so i.e. USER scenario is like a hit and trial method for e.g. a user come up with the service request, there may be possibility of getting service for the first time or may be pass through all option until successful or get blocked after tried all options (w.r.t. access network). In USER scenario preferences are in any order. In the figure 8.2, USER scenario shows random behavior of acceptance probability and even not fulfill requirement very well because user getting blocked number of time until they successful. It is also true that hit and trial methodology will not yield desired results.

In conclusion, ANDSF shows better performance as compare to USER scenario.

4.1.4 Second strategy: Access first (Mobility/block aspect)ANDSF In the second strategy, Mobility/blocking aspect will be considered where mobility

increases and blocking decreases. Each access network provided with the high and low quality service and then move on to the next access network. Figure 4.3 shows acceptance probability of users according to second strategy w.r.t. ANDSF scenario. Most of users are accepted w.r.t. first access network with high and low quality. After blocking it moved to other access network. The aim of the second strategy is to obtain access first w.r.t. different access networks. If we look at the figure 4.3 then we will come to know that most of users accepted from the first access network and even more then 60% users got high quality too.

Figure 4.3 Second strategy: Mobility/block aspect w.r.t. ANDSF scenario.

4.1.5 Second strategy: Access first (Mobility/block aspect)USER Figure 4.4 shows acceptance probability of users according to second strategy

w.r.t. USER scenario. Actual theme of the second strategy is access first; maximum number of user’s request accepted from first access network either with high or low quality and so on. If we look at the graph below, high number of user’s requests fulfill in third network choice as compare to first access network. In section 4.1.2 we already discussed that why USER scenario shows an ambiguous result and even theme of second strategy is not fulfill well enough.

Figure 4.4 Second strategy: Mobility/block aspect w.r.t. USER scenario.

4.1.6 Comparison second strategy: ANDSF & USER scenario In the second strategy ANDSF fulfill requirements very well. In ANDSF scenario

some of the users got service after blocked by first choice of network or sometime blocked by second choice of network but most of users served from the 1st access network and also it shows no rejection. In case of USER scenario, most of users experienced blocking from start and almost less than 15% users accepted from first access network and more than 60% users served by the second access network and so on. Why USER scenario has variation in the result? Because in USER scenario network selection is random for e.g. if a user request for a service which require 21 Mbps bandwidth and only 4G and WLAN can accommodate service then it means 3G is useless for this kind of service, but due to random selection it selects 3G also which become the cause of blocking. In case of ANDSF scenario there is no such problem because Network selection is static w.r.t. user requirement.

4.2 User Attempts There are six preferences in the simulation tool, which are used to accommodate

user’s request, if any of the six preferences will not fulfill user requirement then it will reject user request. We know ANDSF try network in specified order so i.e. it means that there is no need to discuss user attempts. In other words ANDSF try user attempts in specified order in order to avoid blocking and increase acceptance probability w.r.t. first preferences.

According to USER scenario network selection is random so i.e. it needs to discuss

user attempts. In the below section 4.2.1 and 4.2.2 we will discuss user attempts according to first strategy that is Quality first (QoS aspect) and second strategy that is access first (Mobility/block aspect).

4.2.1 First strategy: QoS aspect Figure 4.5 shows acceptance probability of user’s w.r.t. preferences. As we discuss

in the previous section that every user whenever come into the system, a user has six attempts to get the service if user is not enough lucky to get serviced then a user request will be rejected. In figure 4.5 on the horizontal line there is one to six digit

representation of user attempts and each attempts represent bar graph that shows how many users got service (or got requested bandwidth) for the first time and so on. It means that how many users acceptance for the first time (like first preference) and how many for the second (like second preference) and so on. We already know that first strategy deal with QoS aspect; therefore its goal of the strategy, that most of user should serve by high quality.

We know most of user’s request accommodated for the first time and so on in the

figure below. In case of third attempts; about 10% of the PC users in the QoS strategy have thus been blocked twice and it gets even worse in the other strategy. Same like in case of second attempts; about 30% of the PC users have been blocked once. Why PC users got blocking because they request for the high bandwidth; due to random network selection they got blocking.

Figure 4.5 First strategy user attempts: QoS aspect w.r.t. USER scenario.

4.2.2 Second strategy: Mobility/block aspect According to second strategy figure 4.6 shows acceptance probability of user’s

w.r.t. preferences. Access first means that maximum user’s request accepted from first access network either with high or low quality, like most of users accepts from first preference in the figure below.

In PC class more than 30% of the users got blocking w.r.t. first access network;

even they got maximum blocking.

Figure 4.6 Second strategy user attempts: Mobility/block aspect w.r.t. USER

scenario.

4.2.3 Comparison user attempts: ANDSF & USER scenario We believe that there is no comparison in case of user attempts between ANDSF

and USER scenario. ANDSF try user attempts in specified order in order to avoid blocking, on the other side USER try network selection in random order which may become the cause of blocking as well rejection. In case of strategy fulfillment comparison we already come to know that ANDSF behave well w.r.t. USER approach. Here in case of user attempts where ANDSF always work on positive side as compare to USER.

4.3 Blocking Probabilities Finally we will discuss blocking probabilities and compare blocking w.r.t. ANDSF

and USER scenario. In our simulation tool, we have six different options to accommodate user request.

4.3.1 First strategy Figure 4.7 shows blocking probability w.r.t. ANDSF and USER scenario.

Horizontal line shows classes and vertical line shows blocking percentage. HH traffic class has minimum blocking as compare to PC traffic class. According to table 3.3 which describes that HH classes request for minimum bandwidth where as PC classes request for maximum bandwidth which become cause of blocking.

If we compare blocking between ANDSF and USER scenario w.r.t. classes then

each class of ANDSF has low blocking as compare to USER.

Figure 4.7 1st strategy blocking comparison: ANDSF and USER.

4.3.2 Second strategy Second strategy also shows high blocking in USER scenario as compare to

ANDSF scenario. In this case both ANDSF and USER have high blocking as compare to first strategy.

Figure 4.8 2nd strategy blocking comparison: ANDSF and USER.

4.4 ADAPTIVE strategy There is also another type of strategy which is mainly concern with the ANDSF

scenario. ANDSF could adapt high/low preferences to current load. Due to this way it will avoid blocking at a maximum level (or may be completely) but this remains just an idea because we have not tried it. This kind of strategy can be implemented by setting conditions typically depends on high/low load.

In figure 4.9 we come up with the static strategy and there is no blocking in the system. The main aim of the static strategy is use to minimize blocking and it is also possible to reach at zero blocking. It is mainly use when current load on the system is not high.

The goal of an adaptive strategy is to minimize blocking and on the other hand

maximize utilization.

Figure 4.9 Static strategy.

4.5 More Comparative Analysis: ANDSF & USER In this section we will perform some more comparative study among ANDSF and

USER scenario. We will study acceptance probability among different access networks w.r.t. both strategies and acceptance probability of high and low quality service in different strategies.

4.5.1 First Strategy According to first strategy we will discuss acceptance probability among different

access networks w.r.t. both strategies and acceptance probability of high and low quality service.

4.5.1.1 1st network acceptance probability We know ANDSF network selection is in specified order and USER scenario try

network in random order. Due to this behavior ANDSF accommodate maximum acceptance at first access network but USER scenario results having low acceptance probabilities w.r.t. different classes.

Figure 7.1 shows acceptance probability of first access network. ANDSF

acceptance probability is higher then USER scenario.

Figure 7.1 First strategy: 1st access network acceptance probabilities

4.5.1.2 2nd network acceptance probability In case of second access network acceptance probability, USER scenario shows

higher acceptance as compare to ANDSF even the difference is not so high.

2nd Network Acceptance Probability (1st strategy)

52,9444,36

66,6377,86

38,25

71,94

87,8

43,74

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100

HH web PC web PC video HH video

Classes

Accep

tan

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tag

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ANDSFUser

Figure 7.2 First strategy: 2nd access network acceptance probabilities

4.5.1.3 3rd network acceptance probability There is at least 1% acceptance probability in ANDSF scenario w.r.t. 3rd access

network because most of users fulfill their requests from first two access networks. In USER scenario high number of users got acceptance in 3rd access network (as compare to first access network) due to inappropriate choice of network selection (b/c of its random choice of network selection); even the users third network choice face 2nd level of blocking (in case of network selection).

3rd Network Acceptance Probability (1st strategy)

0,24 0,04 0 0,41

31,7

18,42

8,47

30,52

0

5

10

15

20

25

30

35


Classes

Acc

epta

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Per

cen

tag

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ANDSFUser

Figure 7.2 First strategy: 3rd access network acceptance probabilities

4.5.1.4 High quality acceptance probability Figure 7.4 shows high quality acceptance probability w.r.t. both ANDSF and

USER scenario. The acceptance percentage of ANDSF is bit high then USER scenario. The aim of the first strategy is to provide high quality service so i.e. ANDSF fulfill requirement very well.

High quality Acceptance Probability (1st strategy)

99,998,12

95,09

99,6599,85

96,5

92,86

99,53

88

90

92

94

96

98

100

102


Classes

Accep

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ANDSFUser

Figure 7.4 First strategy: High quality acceptance probabilities

4.5.1.5 Low quality acceptance probability Figure 7.5 shows low quality acceptance probability w.r.t. both ANDSF and

USER scenario. The acceptance percentage of USER is bit high then ANDSF scenario. Here also ANDSF shows better results as compare to USER.

Low quality Acceptance Probability (1st strategy)

0,1

1,88

4,91

0,350,15

3,5

7,14

0,47

012345678


Classes

Accep

tan

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erc

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tag

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ANDSFUser

Figure 7.5 First strategy: Low quality acceptance probabilities

4.5.2 Second strategy According to second strategy we will discuss acceptance probability among

different access networks w.r.t. both strategies and acceptance probability of high and low quality service.

4.5.2.1 1st network acceptance probability Figure 7.6 shows acceptance probability of first access network. ANDSF

acceptance probability is much higher then USER scenario because of its network selection in specified order. Why again and again we talk about ANDSF network selection mechanism because this is one of the key factor which help users towards service. In real environment the ANDSF becomes aware of less congested access networks in the area the UE is located, and provides instructions to the UE to move the existing IP flows to the less congested access network.

1st Network Acceptance Probability (2nd strategy)

60,266,36

51,63

42,52

29,27

16,758,14

27,39

0

10

20

30

40

50

60

70


Classes

Acc

epta

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Per

cen

tag

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ANDSFUser

Figure 7.6 Second strategy: 1st access network acceptance probabilities

4.5.2.2 2nd network acceptance probability In case of second access network acceptance probability, USER scenario shows

higher acceptance as compare to ANDSF.

2nd Network Acceptance Probability (2nd strategy)

39,7233,64

48,3757,37

38,74

59,82

76,63

41,59

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Classes

Acc

epta

nce

Per

cen

tag

e

ANDSFUser

Figure 7.7 Second strategy: 2nd access network acceptance probabilities

4.5.2.3 3rd network acceptance probability According to second strategy where we mainly focus on access first; that

maximum user’s request accepted from first access network either with high or low quality. If we compare results among ANDSF and USER scenario then we come to know that ANDSF has less then 1% acceptance probability w.r.t. third access network, but on other side USER has almost 25% of acceptance probability. In USER scenario most of users got acceptance in 3rd access network due to inappropriate choice of network selection; and face 2nd level of blocking (regarding network selection).

3rd Network Acceptance Probability (2nd strategy)

0,07 0 0 0,11

31,99

23,43

15,23

31,02

0

5

10

15

20

25

30

35


Classes

Accep

tan

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ANDSFUser

Figure 7.8 Second strategy: 3rd access network acceptance probabilities

4.5.2.4 High quality network acceptance probability Figure 7.9 shows high quality acceptance probability w.r.t. both ANDSF and

USER scenario. The acceptance percentage of ANDSF is bit high then USER scenario. The aim of the first strategy is to provide high quality service so i.e. ANDSF fulfill requirement very well.

Figure 7.9 Second strategy: High quality acceptance probabilities

4.5.2.5 Low quality network acceptance probability Figure 7.10 shows low quality acceptance probability w.r.t. both ANDSF and

USER scenario. The acceptance percentage of USER is bit high then ANDSF scenario. Here also ANDSF shows better results as compare to USER.

Figure 7.10 Second strategy: Low quality acceptance probabilities

4.6 Other results In appendix A section we also discuss some other results according to both

strategies (first and second). We discuss acceptance probability w.r.t. each access networks, high and low quality acceptance probability w.r.t. both strategies. In that section we conclude Confidence Interval w.r.t. each scenario and then we come up with the relative half size. At last we evaluate these values into graphs.

5: Conclusion & Future Work

5 CONCLUSION & FUTURE WORK

The aim of the thesis is to identify quantitative measures of ANDSF benefits. Our contribution is to develop ideas for how to obtain such measures in order to identify ANDSF benefits. We developed a simulation tool which implements some of these ideas. In simulation tool we impose preferred strategies, reduced delays and losses and work on system utilization efficiency in order to identify ANDSF benefits. In our simulation model we use different implementation terminologies like network traffic, access networks, and preferences w.r.t. quality as well as w.r.t. strategies. We have two main scenarios ANDSF and USER; we also perform extensive comparative study in order to evaluate analysis of gains from ANDSF. We have examples of possible results and our numbers are just examples because providing real gains is outside our study. We evaluate our scenarios w.r.t. three main aspects; how well the strategies are fulfilled? How many attempts are required for users? and compare blocking probabilities.

The overall conclusion of the thesis is to find out the reasons that why ANDSF is a

better choice for network selection as compare to users themselves. Our results shows that ANDSF is a better option for network selection because it helps users towards use their service efficiently as well as avoid blocking; even in real environment the ANDSF becomes aware of less congested access networks in the area the UE is located, and provides instructions to the UE to move the existing IP flows to the less congested access network.

Now ANDSF in its initial stage of standardization and there is only the minimal

interface defined for the mobile device. Due to its initialization only limited definition as well as description found regarding ANDSF internal working structure there is no connection to the other terminals only depends on its information for run time decisions. ANDSF also has limited dynamic operations. But, In case of future work is concerned regarding ANDSF there is number of Extensions proposed and some of them are given below:

• It can be used in the future as a subscription based ANDSF. • Dynamic ANDSF discovery Information. • It also works as a Location Enabler in the future. • ANDSF for Femtocells Discovery and Selection

6: References

6 REFERENCE:

[1]. Marius Corici, Alberto Diez, Dragos Vingarzan, Thomas Magedanz (Fraunhofer Fokus Institute Berlin, Germany) and Cornel Pampu, Zhou Qing (Huawei Technologies Berlin, Germany), “Enhanced Access Network Discovery and Selection in 3GPP Evolved Packet Core”. 3rd IEEE LCN Workshop on User MObility and VEhicular Networks, Zürich, Switzerland; 20-23 October 2009 [2]. Sachs, J. and Olsson, M. (2010), “Access network discovery and selection in the evolved 3GPP multi-access system architecture”. European Transactions on Telecommunications, 21: 544–557. doi: 10.1002/ett.1410 [3]. Gottfried Punz, “Evolution of 3G Networks, The Concept, Architecture and Realization of Mobile Networks Beyond UMTS” 1st Edition., 2010, X, 306 p. 50 illus., Hardcover ISBN: 978-3-211-09439-6 [4]. 3GPP TS 23.882: “3GPP System Architecture Evolution: Report on Technical Options and Conclusions”. [5]. 3GPP TR 25.913: “Feasibility Study of Evolved UTRA and UTRAN”. [6]. Rao, A. M., Weber, A., Gollamudi, S. and Soni, R. (2009), LTE and HSPA+: Revolutionary and evolutionary solutions for global mobile broadband. Bell Labs Technical Journal, 13: 7–34. doi: 10.1002/bltj.20334 [7]. Rosenbrock, K. H. and Andersen, N. P. S. (2002) The Third Generation Partnership Project (3GPP), in GSM and UMTS: The Creation of Global Mobile Communication (ed F. Hillebrand), John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/0470845546.ch9 [8]. 3GPP TS 33.402: "3GPP System Architecture Evolution (SAE): Security aspects of non-3GPP accesses" [9]. 3GPP TS 33.222: “Generic Authentication Architecture (GAA); Access to network application functions using Hypertext Transfer Protocol over Transport Layer Security (HTTPS)” [10]. J. Eberspacher, HJ. Vogel: "GSM- Architecture, Protocols and Services", John Wiley & Sons (2009) [11]. A. Kavanagh, J. Bechmeyer: "GPRS Networks", Osborne Publishing (August 2002) [12]. H. Kaaranen, A. Ahtiainen, L. Laitinen, S. Naghian and V. Niemi: "UMTS Networks (Architecture, Mobility and Services)", John Wiley & Sons (2005) [13]. 3rd Generation Partnership Project, “Requirements for Evolved UTRA (E-UTRA) and Evolved UTRAN (E-UTRAN) (Release 7),” 3GPP TR 25.913, v7.3.0, Mar. 2006, <http://www.3gpp. org/ftp/Specs/html-info/25913.htm> [14]. 3GPP, TS 29.214 Policy and Charging Control over Rx Reference Point V.8.3.0. 2008. [15]. 3GPP, TS 29.212 Policy and Charging Control over Gx Reference Point V8.2.0. 2008.

[16]. 3GPP, TS 23.234 3GPP System to Wireless Local Area Network Interworking V8.0.0. 2008. [17]. Good, R., de Gouveia, F. C., Ventura, N. and Magedanz, T. (2010), Session-based end-to-end policy control in 3GPP evolved packet system. International Journal of Communication Systems, 23: 861–883. doi: 10.1002/dac.1096 [18]. OMA-ERELD-DM-V1_2: "Enabler Release Definition for OMA Device Management"

[19]. Pablo Martinez, Miguel A. Garcia “PCRF - ANDSF interactions in constrained resource scenarios” Ericsson technical report 2010-06-11

7: Appendix A

7 RELATIVE HALF SIZE COMPARATIVE ANALYSIS: ANDSF & USER In this section we will perform some more comparative study among ANDSF and

USER scenario according to relative half size. We will study acceptance probability among different access networks w.r.t. both strategies and acceptance probability of high and low quality service in different strategies.

7.1 Strategy Fulfillment 7.1.1 1st Strategy

Classes Parameters 1/high 1/low 2/high 2/low 3/high 3/low 1 Mean 0.26233 0.33126 0.40347 0.00148 0.00114 0.00030

Conf95 0.00446 0.00553 0.00522 0.00063 0.00055 0.00021 RelHalfSize 1.70150 1.67040 1.29570 42.6620 48.1350 70.1950

2 Mean 0.34606 0.31059 0.32781 0.01531 3.8e-008 0.00024 Conf95 0.01538 0.01599 0.01353 0.00571 4.3e-006 0.00034 RelHalfSize 4.44530 5.13840 4.12730 37.3110 58.8970 143.350

3 Mean 0.14652 0.35628 0.46468 0.03252 0 3.13e-00 Conf95 0.01434 0.01937 0.01582 0.01162 0 0.00017 RelHalfSize 9.78930 5.43780 3.40510 35.7240 0 562.330

4 Mean 0.08971 0.32712 0.57666 0.00430 0.00153 0.00066 Conf95 0.00356 0.00627 0.00611 0.00166 0.00073 0.00040 RelHalfSize 3.97310 1.91810 1.06010 38.5930 47.7520 61.0380

Classes Parameters 1/high 1/low 2/high 2/low 3/high 3/low 1 Mean 0.19730 0.08593 0.38559 0.02120 0.23865 0.07133





7.1.2 2nd Strategy

Classes Parameters 1/high 2/high 3/high 1/low 2/low 3/low 1 Mean 0.37135 0.57590 0.03138 0.00856 0.00879 0.00401


2 Mean 0.37346 0.33272 8.6e-00 0.16134 0.12884 0.00390 Conf95 0.01756 0.01329 6.8e-00 0.01345 0.01023 0.00146 RelHalfSize 4.70270 3.99510 96.0100 8.33830 7.94280 37.5140

3 Mean 0.16482 0.31224 0 0.29444 0.22838 0.00079 Conf95 0.01718 0.02185 0 0.02272 0.01877 0.00100 RelHalfSize 10.4280 6.99840 0 7.71720 8.22130 125.820


Classes Parameters 1/high 2/high 3/high 1/low 2/low 3/low 1 Mean 0.16896 0.43884 0.37303 0.00500 0.00733 0.00684





7.2 User Attempts 7.2.1 According to 1st Strategy

Classes Parameters 1 2 3 4 5 6 1 Mean 0.68598 0.14878 0.10399 0.02316 0.02184 0.00442





7.2.2 According to 2nd Strategy

Classes Parameters 1 2 3 4 5 6 1 Mean 0.74178 0.01075 0.19265 0.00535 0.03861 0.00292





7.3 Blocking Probabilities 7.3.1 According to 1st Strategy

Classes Parameters ANDSF USER 1 Mean 95.65 1199.0

Conf95 48.97 264.58 RelHalfSize 51.20 22.070

2 Mean 78.94 1361.5 Conf95 37.16 284.37 RelHalfSize 47.07 20.890




’






7.4 More Comparative Results 7.4.1 According to 1st Strategy
























3 Mean 3.13e-5 0.0540 Conf95 0.0001 0.0084 RelHalfSize 562.33 15.657




























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