**1. Introduction**

26 Will-be-set-by-IN-TECH

28 Telecommunications Networks – Current Status and Future Trends

R. Housley & B. Aboba (2007). *Guidance for Authentication, Authorization, and Accounting (AAA)*

R. M. Lopez, A. Dutta, Y. Ohba, H. Schulzrinne & A. F. Gomez Skarmeta (2007). *Network-Layer*

R. Marin, J. Bournelle, M. Maknavicius-Laurent, J.M. Combes & A. Gomez-Skarmeta

S. Pack & Y. Choi (2002). *Fast Inter-AP Handoff using Predictive-Authentication Scheme in a Public Wireless LAN*, *Proc. of IEEE Networks 2002 (Joint ICN 2002 and ICWLHN 2002)*. S. Winter, M. McCauley, S. Venaas & K. Wierenga (2010). *TLS encryption for RADIUS*. IETF

T. Aura & M. Roe (2005). *Reducing Reauthentication Delay in Wireless Networks*, *Proc. of 1st IEEE*

T. Clancy, M. Nakhjiri, V. Narayanan & L. Dondeti (2008). *Handover Key Management and*

Taniuchi, K., Ohba, Y., Fajardo, V., Das, S., Yuu-Heng, M. T. C., Dutta, A., Baker, D., Yajnik, M.

V. Narayanan & L. Dondeti (2008). *EAP Extensions for EAP Re-authentication Protocol (ERP)*.

Y. Ohba and A. Yegin (2010). *Pre-Authentication Support for the Protocol for Carrying*

Y. Ohba, Q. Wu & G. Zorn (2010). *Extensible Authentication Protocol (EAP) Early Authentication*

Z. Cao, H. Deng, Y. Wang, Q. Wu & G. Zorn (2011). *EAP Re-authentication Protocol*

*Extensions for Authenticated Anticipatory Keying (ERP/AAK)*. IETF Internet Draft,

*2006*, Vancouver, British Columbia, Canada, pp. 183–188.

*Assisted Mechanism to Optimize Authentication Delay during Handoff in 802.11 Networks*, *Proc. of the 5th Annual International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, ACM Mobiquitous 2007*, ACM, Philadelphia, USA.

(2006). *Improved EAP keying framework for a secure mobility access service*, *Proc. of International Wireless Communications & Mobile Computing Conference 2006, IWCMC*

*Security and Privacy for Emerging Areas in Communication Networks, SECURECOMM*

& Famolari, D. (2009). *IEEE 802.21: Media independent handover: Features, applicability,*

*Key Management*. IETF RFC 4962.

*2005*, IEEE, Athens, Greece, pp. 139–148.

*Problem Statement*. IETF RFC 5836.

raft-ietf-hokey-erp-aak-06.

*Re-authentication Problem Statement*. IETF RFC 5169. T. Dierks & C. Allen (1999). *The TLS Protocol Version 1.0*. IETF RFC 2246.

*and realization*, *IEEE Communications Magazine* 47(1): 112 –120.

*Authentication for Network Access (PANA)*. IETF RFC 5873.

Internet-Draft.

IETF RFC 5296.

This chapter discusses the application of methodologies to plan and design IP Backbones and 3G access networks for today's Internet world. The recent trend of the multi-frequency band operations for mobile communication systems requires increasingly bandwidth capacity in terms of core and access. The network planning task needs mathematical models to forecast network capacity that match the service demands. As the nature of network usage changed, to explain and forecast the network growth, new methods are needed. In this chapter, we will discuss some strategies to optimize the bandwidth management of a real service provider IP/MPLS backbone and later we will propose a method for traffic engineering in a national IP backbone.

Currently, all telecommunications networks are using IP packets to transport several kind of services. The industry has called this integration as IMS (IP Multimedia Subsystem) in 3G technologies. One important challenge is how to implement this desirable integration with the lack of well known mathematical models to perform capacity planning and forecast the network needs in terms of growth and applications demands. In other way, the main question is how to deliver the required level of service for all kind of applications using the same structure but with different types of traffic and QoS (Quality of Service) requirements.

Due to the fact that many different services will use the same transport infrastructure, the Quality of Service can also be described as a result of traffic characterization because the traffic nature per service or at least per application shall be known. As demonstrated in some research papers (Leland et al., 1994; Carvalho et al., 2009), the Erlang model is not able to accurately describe the behavior of Ethernet and Internet traffic. Without the right model, scientific prediction becomes very difficult and therefore, the planning and forecasting tasks become almost impossible. The above research works verified that the Poisson traffic model is not able to explain the IP traffic dynamics and this implies that the capacity planning tasks for integrated services will need new methodologies. Some models have been used with superior performance to achieve these goals, the self-similar or monofractal model show acceptable results in several situations (Carvalho et al., 2007).

Several works show that the multifractal models are particularly promising for multimedia networks (Riedi et al., 2000; Abry, 2002; Fonseca, 2005; Deus, 2007). The traffic

IP and 3G Bandwidth Management Strategies Applied to Capacity Planning 31

Fig. 1. Telecommunications Industry Planning Process. Adapted from (De Deus, 2007; Evans

The processes of traffic characterization and modelling are very important points of a good network project. A precise traffic modelling may allow the understanding of a physical network problem as a mathematical problem whose solution may be simpler. For example, the use of traffic theory suggests that mathematical models can explain, at least for some confidence degrees, the relationship between traffic performance and network capacity (De

The next sections will provide an example on a 3G network using traffic samples to study the planning and project deployment phases. The network described in our study runs with more than 1 million attached 3G costumers with national coverage. In this network, we collected traffic in July 2009 in three different locations (Leblon, Barra da Tijuca and Centro) in Rio de Janeiro. In this way, the first step was to classify the traffic per application. The second step was to characterize the traffic using a procedure based on selfsimilarity (Clegg, 2005) or multifractal analysis (Carvalho et al., 2009). These results were

To manage the traffic demands, we deployed a traffic engineering concept that divides the traffic across the network through tunnels. The bandwidth was monitored and in the observed period, we collected metrics that were used as inputs to decide how to configure new parameters that may fit the incoming needs. An ILEC (incumbent local exchange

used as basis for proposing a method to manage the traffic in the network.

& Filsfils, 2007).

Deus, 2007; Fonseca, 2005).

engineering task is valuable to optimize the network resources such as links, routing and processing capacity. One important issue in the traffic engineering task is that the capacity planning forecasting may be for medium long periods (or more than one year), due the fact is not easy to increase long distance link capacities in small periods of time. This problem is much more valuable when the coverage area income is not proportional to the area, as in countries like Brazil, China, Russia in which large areas not necessarily economically attractive.
