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Policy based Admission Control across heterogeneous wireless networks Ken Murray and Dirk Pesch Adaptive Wireless Systems Group Department of Electronic Engineering Cork Institute of Technology, Cork, Ireland E-Mail: {kmurray, dpesch}@cit.ie

1

Introduction

Future 3G and 4G mobile networks will consist of wireless access technologies such as WCDMA, EDGE and 802.11a/b WLAN coexisting in a heterogeneous access network environment. Each network access technology provides different levels of coverage and QoS as well as cost to the end user. The range of anticipated services for future wireless networks will introduce high variability in the required QoS and therefore, the most optimal access network can dynamically change. It is envisaged in such wireless networks that multi-modal mobile terminals will seamlessly and dynamically roam between different access networks to support the varying QoS and network connectivity constraints. Supporting this dynamic mobility is seen as one of the key issues in resource management for heterogeneous wireless networks [1]. With inter-system mobility, users will benefit from the different coverage and capacity characteristics of each network throughout the interconnected heterogeneous environment and can strive to be connected to the best available network at all times. A pivotal element in the mobility management architecture of a heterogeneous access network is admission management or control. Fundamentally, admission control is responsible for making access decisions in response to a user’s access request based on a range of criteria including required QoS level, bandwidth requirement, coverage, cost, etc. From a network perspective, admission control facilitates high capacity and spectrum efficient network usage. This can be achieved through load balancing between available access networks, enforcing handover to a different access network to meet changing QoS constraints, and also to admit a user to multiple networks simultaneously using multiple connections in order to achieve the best fit QoS for multiple, parallel application traffic streams. Sophisticated admission control schemes are required to maintain QoS contracts and continuous connectivity in an environment where users are dynamically roaming between different access technologies [2]. From a user perspective, roaming requires selection between different access network operators and service providers. Service provider selection could be motivated by cost, discount or reward point schemes, or even previous positive or negative service experience. Using Policy to initiate handovers across heterogeneous wireless networks has been previously proposed [3], however, such proposals only consider the users perspective. Giving total control to the user can result in network instability as users compete for network resources regardless of network conditions, while a network controlled system will ignore user preferences and QoS requirements. The most optimal mobility management and admission control scheme should encompass both user and network aspects. In this paper we examine the implications of using policy-based management techniques in making admission management decisions from both the network operator perspective and also the user perspective.

2

Seamless Intersystem Mobility

It is envisaged that future wireless networks will be IP based, with a common core backbone network integrating the different wireless access technologies [4]. Mobile IP and Cellular IP have been widely accepted in solving the seamless mobility problem across such IP based networks [5,6]. Variations of Mobile IP using multicasting and packet buffering have also been proposed to further reduce the handoff latency encountered when a mobile host changes its point of attachment [7,8]. Although Mobile IP and similar proposals address seamless intersystem mobility across multiple IP based networks, it does not address admission control and network selection from both the user and network perspective. There is a need for a dual adaptive decision making algorithm to make admission control and network selection decisions in an environment where multiple networks are available, each of which offer different coverage and QoS characteristics. To this end, we propose a Policy Based Management system to make admission control and network selection decisions for both network and user.

3

Policy Based Network Management

Fundamentally, a policy is a set of rules and instructions that determine a network operation. The evaluation of a policy rule is triggered by an event which results in a policy decision been enforced on a specific network device. As policies are declarative, they can be adapted at run-time to flexibly control system behaviour and are therefore becoming increasingly popular in adaptive, run-time configurable networks and information systems. 3.1 Access Control using Policy – the Network Perspective A variety of access control schemes have been proposed for call admission control in wireless networks that exhibit soft capacity such as those based on CDMA technology [9,10,11,12,13]. All of the proposed schemes are based on a homogeneous network environment and do not consider the possibility of initiating a handover for session transfer to another available access network. Admission control across heterogeneous networks based on parameters such as radio channel characteristics, resource availability, QoS constraints and user preferences remains an open issue. In this paper, we propose an admission control scheme for heterogeneous wireless networks based on a policy-controlled technique. A policy based management system is governed by a set of rules that determine the action to be taken based on a set of input parameters [14]. In the context of admission control, the resulting action will be the admittance of users into the requested network(s) or the forced handover of a current user to another network(s). The parameter values that the policy rules process include for example received signal strength at the requested base station, average bit error rate, current QoS level and the required QoS, access network coverage, cost of both current and requested networks, battery power of mobile terminal, user preferences made available to the provider etc. Policy parameters are discussed further in section 3.3. 3.2 Network Selection using Policy – the User Perspective As policy based mechanisms may assist service providers in balancing user admission with network conditions, so they may also assist the user in flexibly controlling their choices in requesting wireless network admission and accepting any conditions associated with admission. This requires users to express their preference not as simply a set of parameters and values but as a set of rules that express the conditions under which to request and accept wireless network access. This enables automatic negotiation of network access for the user based on adaptive user preferences that combine user preference for cost, reliability, application latency and security with the static capabilities of currently available networks and their dynamic state, e.g. predicted load over a period, signal interference etc. For instance a user’s policy may state: IF applicationThroughputRequirement > 128k bps THEN select(WLAN) ELSE select(GPRS). 3.3 Policy Parameters A policy rule is specified in terms of a number of network and user parameters. These parameters are continuously updated and stored in a policy repository in both the network side and mobile terminal. The architecture of the policy based management system is further discussed in section 3.4. Policy parameters include, network conditions, handover latency, power consumption, network coverage, cost, mobile speed and user priority. We explain each in turn. Network Condition: Network condition can be described in terms of the average SIR and BER measurements at both base station and mobile terminal. The current performance of reachable networks is an important factor in determining the best network from those available. A low SIR and high BER will result in increased retransmissions, thereby reducing the throughput. When a high bandwidth network (WLAN) is heavily loaded or congested the policy system may instruct the mobile terminal to switch to a lower bandwidth connection (EGPRS). Handover Latency: The time to implement a handover to another access network may be quite large when compared to the connection time. If the connection duration will be short, it may be worthwhile to remain with the current network if possible. Also for real-time, time sensitive applications, high handover latency may be unacceptable from a QoS point of view.

Power Consumption: Power consumption is another dynamic factor influencing the choice of available networks. Different networks will demand different power from a mobile terminals battery. If current battery status is low, then the policy system should choose a network with the lowest power requirements. Network Coverage: Network coverage can be used in deciding which network to use from a candidate list. If a network offers a low coverage area such as that from a small number of WLAN access points, then a decision should be made not to attempt accessing the WLAN if the mobile terminal is moving quickly through this coverage area. Mobile Speed: The speed of a mobile terminal will indicate the length of time the current connection can be maintained due to lack of coverage. A WLAN would not be considered the best network if a mobile is moving at a high velocity as this would cause excessive handovers between access points within the WLAN network, which could lead to a loss of data. User Priority: Each mobile terminal will have a priority according to the users role in the network. High priority users will have precedence over lower priority users when attempting to access a network. If a high priority user requires a high bandwidth connection, other lower priority users can be forced to handover to a lower bandwidth network by the policy system.

4

Policy Architecture

We propose a policy system architecture for making policy-based access control decisions and network selection decisions in the network and at the user terminal respectively. Policy system architectures tend to focus on the relationship between the point where the outcome of a policy is enforced, e.g. the point in a network where admission control is enacted, and the point where the decision on whether a policy conditions are satisfied is taken, i.e. the Policy Decision Point (PDP). The PDP for network access control is implemented on a server within the network and uses an open communication protocol with enforcement points [14]. This approach allows implementing the PDP at a location where network information such as data rate, coverage area, mobility support and current load are available, e.g. a base station, switch or a network router. Data required by the admission controller policy engine is maintained in a policy repository. The policy repository contains the policy parameters which are used in the decision making process. This architectural approach also facilitates the updating of policy rules through the network. For the user the enforcement point is their mobile terminal, which is typically powerful enough to run a PDP. Condition state of user policies are however restricted to measurements that can be made by the terminal or are available to the user, such as packet round trip time, cost of usage, perceived subjective quality of service, etc. since open access to the providers’ network measurements is unlikely. The policy rules within the PDPs are adaptive in nature so as to achieve load balancing across the heterogeneous networks operated by a provider. Adaptive policy rules enable each network to carry the maximum traffic load for the available spectrum as network load levels vary. The design of policy rules that achieve business goals has to be done carefully and with a good understanding of the networks operation. Conflicting policies can cause unexpected behaviour in the network and mechanisms are available for detecting certain conflicts before deployment [14].

Base Station Base Station Policy Engine PEP

Policy DataBase PDP Avg. SIR BER Coverage Other Networks

Enforce PDP Decision

Policy Rules Evaluated IF ……. THEN

Access request from user Network Status/Congestion

Policy Decision Exchange/Arbitration

Mobile Station

Mobile Station Policy Engine PEP

Policy DataBase PDP User Preference: Cost, QoS Network Measurements

Enforce PDP Decision

Measurements Reports from Network

Policy Rules Evaluated IF ……. THEN

Reduced QoS Network Unavailable

Figure 1

5

Policy System Architecture

Simulation Model

In order to evaluate the proposed policy-based access management approach we are implementing a computer simulation model of a heterogeneous access network with access technologies (E)GPRS, WCDMA, and IEEE802.11 WLAN. Continuous coverage for both UMTS and GPRS are provided throughout the network with each cell containing UMTS and GSM/GPRS transceivers. A cluster of WLAN access points is positioned within a small number of cells giving partial cell coverage. Multimodal terminals are positioned non-uniformly throughout the network. We consider three types of user traffic- voice, www browsing, and multimedia streaming, which are expected to be among the most commonly used types of services in future mobile networks. The multimedia streaming class considers H263 video streaming with 64kbps target bit rate. The interarrival time between user service requests is

exponentially distributed with a mean of 20 minutes. The average call holding time for voice and streaming sessions are exponentially distributed with means of 3 and 10 minutes respectively. The number of web pages per web session is uniformly distributed between 5 and 15, while, the number of packets per web page range from 15 to 30. These figures are simulation parameters and will be varied in the evaluation period. Users roam between the three access networks based on decisions made by the policy based management system. Downlink UMTS traffic can be carried with data rates of 60, 120, 240, 480 and 960 kbps, depending on the signal quality, which is determined via periodic SIR measurements at both the base station and mobile terminal. Traffic carried over the EGPRS network is allocated a 22.4kbps timeslot on the uplink and up to four 22.4kbps timeslots on the downlink, resulting in a maximum data rate of 89.6kbps. The MC-5 coding scheme is used in EGPRS. The maximum data rate is determined by resource availability at the associated base station. The WLAN access network considers the IEEE 802.11b, giving data rates of up to 11Mbits/s, depending on signal quality and number of users accessing the WLAN. The performance of the proposed policy-based access management approach will be assessed based on network utilisation and individual user perceived QoS. A secondary assessment will be the cost of network access to the provider and the user. The higher the cost the less optimal the decisions made by the policy controller.

Conclusion This paper examines the use of policy based management techniques for admission management by service providers offering multiple wireless network types and for selection between network types and providers by users. An adaptive policy based admission control scheme for seamless mobility between heterogeneous networks is proposed. Policy rules are evaluated using network characteristics, application and user parameters. Policy rules are adapted so as to continuously achieve optimal load balancing between the available networks and fulfil user requirements.

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