Sub-drenes.

3.5

Dynamic roaming

In this section the network composition mechanisms used for dynamic roaming will be explained. General benefits will be outlined together with examples of improved service availability.

Network Composition

Dynamic Roaming is based on the Network Composition concept developed in the Ambient Networks project36_{. Composition provides a unified framework to support}

dynamic establishment of cooperation between networks, providers and end-user equipments [129] [130].

This cooperation includes both business and technical aspects. Each relation is described by a Composition Agreement (CA) between the networks or business en- tities. The composition framework target to support different types of co-operation between networks and/or devices. Examples are network attachment of user de- vices and joint resource control of operator networks. The composition framework includes a set of well defined procedures:

• Media Sense The medium over which cooperation is established is sensed

• Advertisement and Discovery Offers and requests are exchanged during this phase including resources and services. The received offers are evaluated and network candidates forwarded to the continued composition process.

• Basic Connectivity and Security AssociationWhen an entity is found a basic connectivity and security association is established to ensure a secure connec- tion over which further message exchange can be carried out.

• Negotiation of Composition Agreement (CA) includes the policies for a new composition and e.g. how resources are shared between the composing enti- ties.

• Composition Agreement Realization When a CA has been negotiated and agreed, the involved entities should configure their networks or devices to reflect the CA. Communication sessions can now start.

An example of sequence of actions when a user terminal is connected to one of several Ambient Networks (AN1, AN2, AN3) is shown in Figure 3.8. The user terminal listens and receives a number of access offers from different networks (and providers). These offers are evaluated and one network (in this case AN1) is se- lected. A basic connectivity link is established in order to negotiate a CA. When a CA is agreed and in place the application session can start.

36_{The Ambient Networks official web site (www.ambient-networks.org) is no longer available.}

Here all project deliverables from the project were available for download. Hence, references in this section are made to journal and conference publications and to 3GPP documents

Figure 3.8: Example of sequence of actions for Network composition

One potential problem with composition is the added signalling in the network. An analysis made by Akhtar and Queseth shows that the relative signalling load is 0.1 - 1.0 % of the transferred user data [17] [18] [19]. The signalling load for multiple attachment and negotiation procedures was assessed by modeling signalling sequences for a WLAN system enabled with AN technology. The load was computed for varying numbers of users and for users with different levels of willingness to evaluate and negotiate offers. The most important parameter is the number of attachment attempts per time unit, which indicates the user activity level.

An example with dynamic roaming

Dynamic roaming enables users to access several networks and not only the one or the ones of the home operator. From the end-user perspective this is similar to emergency calls (112) or when traveling abroad (international roaming). In these cases the user can usually access all networks in a country. The user needs to be identified before access to the network is allowed. One solution is to use the identity provided by an mobile operator (the home network operator). Dynamic roaming consider cases where the home operator does not have any previous agreement with the operator of the visited network. Therefore an agreement needs to be established before the user is able to connect.

3.5. DYNAMIC ROAMING 49

Figure 3.9: Distribution of activities and roles for two examples of dynamic roaming. Different actors are involved doing different types of activities

Two types of roaming are shown in Figure 3.9. In the first case a subscriber of the Red operator detects an offer from the Blue operator and selects this net- work. In the second case the green user connects to a local access network without any involvement of any mobile operator. The user may have a mobile operator subscription but in this case the identity is provided by some other trusted third party that has a business relation with the user. Typically this can be a credit card company (VISA, Mastercard) or a payment provider (Paypal, PayEx). The green user may detect offers from other access providers, in this case the blue operator, but chooses the local operator.

From a network composition perspective these two cases are identical. The decision making can be made by the network (the operator) or by the user (terminal) based on policies or user preferences. The home network operator identity is used to authenticate and authorize the user.

Compared to the network sharing cases we can see different actors performs different activities. In this example the different actors take the responsibility for different activity groups. The user can chose what network to access and what identity & payment solution to use. The business roles an actor will take and what activities to perform depends on the decisions made for each user session. The whole usage pattern isdynamicfor users as well as for the different providers.

Potential benefits of dynamic roaming

The Ambient Networks concepts challenge the traditional operator approach with

one subscriber - one operator - one network. As will be shown there are potential performance benefits, especially for the end-users, but at the same time the opera- tors will be faced with a more complex business situation. The investments made in both networks and customers may be more risky since the own user may use networks of other network providers.

Dynamic roaming will enable access to many networks operated by different types of network providers. The ability for users to connect toany network is a key element of the network composition. This will enable operators to co-operate in new ways and allow users to connect to a multitude of visited networks although the user is within coverage of the home network. This implies a number of potential benefits for different types of actors:

• End-userscan chose freely from many network and service providers and will experience an improved service availability

• Mobile Operatorswill get access to a larger market which implies a potential for increased revenues. The operators can offer better service coverage and availability to own customers and can also reduce investment costs and risks for deployment of own networks

• Greenfield operatorswill experience lower entry barriers, less investment and can start operation without nation wide networks

• Local network operators can more easily build up a customer base and enter the market

• Regulating authorities can more easily enforce national roaming in order to support market entrants and to manage actors with a dominant market po- sition

The discussion below is focused on the improved service availability due to the ability for end-users to access networks of many network operators. The improved service availability will increase the traffic, the potential for revenues and it will also result in more satisfied users. A typical multi-operator multi-network scenario is outlined in Figure 3.10 with three mobile operators, each with a number of different access networks (e.g. GSM at 900MHz, GSM at 1800 MHz and UMTS at 2100 MHz).

The end-users can access all networks and not only the networks of one operator. The benefits of dynamic roaming can be illustrated by comparing the performance of cases where all networks can be accessed to the case where just one network can be accessed. The performance will vary depending on the network load and the location of users. At location 1 shown in Figure 3.10 in total five networks have coverage. Users at location 2 are within coverage of two networks.

3.5. DYNAMIC ROAMING 51

Figure 3.10: Example of a multi-operator multi-network scenario. Wide cylinders represent wide area coverage networks and"high"cylinders represent networks with

"high"average capacity

The question is how to evaluate the differences in performance and how to express and interpret the value of the performance improvements.

Analysis of service availability

In the Ambient Networks project the impact of roaming was analyzed by comparing cases where the users (and terminals) could connect to one or several networks with partly overlapping coverage. A number of moving users were simulated in an area with multiple networks. At some locations the ongoing session was ended due to coverage problems or overload in the network. For the roaming case a handover to the other networks was initiated. For the case of a single-operator user attempts to connect to network was done at new locations.

Handovers are initiated when the signal strength to the serving base station is below a certain threshold. The handover mechanisms for a traditional single net- work (legacy) case consider signal strength and roaming agreements. The Ambient Network algorithms support multi-operator & multi-radio access operation and al- low use of the cells of the other operators. Two types of multi-operator handover strategies were analyzed, terminal centric and network centric algorithms. The al- gorithms were proposed, designed and tested by Pöyhönen and colleges at Nokia Siemens Networks [8] [9] [10].

Connectivity statistics

The evaluation of multi-operator and multi-radio handovers was done by simula- tions where statistics was collected for different types of handover algorithms taking into account the possibility to use other operator network. The results were typi- cally in the form of connection statistics where one example is shown in Figure 3.11. The possibility to use multiple networks not surprisingly results in an increase in the overall time that terminals were connected, and in a corresponding decrease of the total time intervals of disconnection.

Figure 3.11: Example of connection statistics for handover experiment in a multi- operator multi-network scenario. Legacy case represent single-operator case (i.e. no handover). Terminal and network centric algorithms means hand-over for the multi-operator case, from [8]

Impact of traffic and load

The simulation experiments were repeated for different levels of network load and number users. More served mobile nodes (MNs) represents higher network utiliza- tion and total traffic. The performance in terms of number of connected MNs is shown in Figure 3.12 for a scenario with 2 mobile operators with overlapping cov- erage areas. The specific numbers is a result of the working assumptions and the simulation setup, but the general behavior and impact of cooperation is clear. The network utilization increases and more mobile nodes can be served.

3.5. DYNAMIC ROAMING 53

Figure 3.12: Served mobile nodes (%) for different levels of network load, with and without operator cooperation (i.e. possibility to switch network or not), from [13]

Figure 3.12 shows the connectivity statistics (% served MNs) for different levels of network load (number of MNs). The network cooperation results in increases in the number of served MNs. For 100 MNs the improvement is approximately 20% and for 700 MNs the improvement is 73%.

User experience

With these these results on improved network utilization and traffic it was discussed how these kinds of results could be interpreted from an user perspective. The connection and disconnection numbers are linearly related to the connection time. But will this reflect the user experience in a correct way?

Users that are disconnected will probably be disappointed which will result in a negative user experience. The connectivity statistics alone does not reflect this potential disappointment. A user that not is connected contributes with a "zero"

to the statistics but the user experience is probably not zero. These thoughts were the starting point for development of a user oriented performance metrics called the User Satisfaction Index (USI). The USI is based on behavioral economics and takes into account users expectation [179] [180] [181].

This has implications for how users value service availability and quality, i.e. it is related to the value proposition. Such an analysis provides input to modeling of customer satisfaction. This type of modeling and analysis is described in a number of papers by Pöyhönen, Markendahl and Strandberg, see [11] [13] [14] [15].