On the Performance of the AAA Systems in 3G Cellular Networks

Zaghloul, S.; Jukan, Admela

doi:10.1109/icc.2007.348

Cited by 3 publications

(5 citation statements)

References 8 publications

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“…which matches the result in [13], [14]. From (5), it is clear that there is a nonlinear relationship between the interim setting and the mean signaling load.…”

Section: Estimating the Aaa Signaling Loadsupporting

confidence: 86%

“…In some cases such as in roaming, the AAA system connected to the NAS may forward requests to the destination AAA system through few intermediate AAA proxies [13]. This configuration is referred to as the AAA proxy chain.…”

Section: Impact Of Roaming Users (Proxy Chains)mentioning

confidence: 99%

“…This is a practical assumption for operational networks. Following a similar approach as in [13], [14], the authentication rate 2 for service i denoted as i is related to the rates of accounting start and stop messages as…”

Section: Estimating the Aaa Signaling Loadmentioning

confidence: 99%

“…To account for statistical variability due to mobility, our method uses standard protocol attributes [3], [4] to categorize mobile service sessions into four distinct types relevant to their initiation and termination locations. The statistics of the four components are then used to estimate the load and loss by extending concepts of holding time, based on our past work [13], [14], [15]. Our optimization mechanism embraces the current AAA IETF standards, RADIUS, and its successor Diameter [1], [2] and does not require any modifications to the AAA protocols nor to the network access servers, and its implementation scope is limited to the AAA systems.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Accounting Policies for AAA Systems in Mobile Telecommunications Networks

Zaghloul

Jukan

2010

IEEE Trans. on Mobile Comput.

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Authentication, Authorization, and Accounting (AAA) deployments are expected to grow significantly in emerging mobile systems as they offer a plethora of services and mobile applications. In current systems, network access servers (NAS) periodically report the service usage of mobile users located within their coverage areas. The periodic reports are used by the billing systems to minimize the incurred capital losses if the serving NAS fails. While shorter reporting intervals are desired for lower losses, they can potentially result in undesirably high signaling load. Because it is prohibitively difficult to obtain optimal reporting intervals in mobile systems due to multitudes of services with different mobility profiles, current accounting standards offer no quantitative measures for selecting a proper reporting interval and AAA systems are typically designed via over provisioning. To address this issue, we propose an adaptive optimization mechanism in multiservice AAA systems which limits the potential loss without excessively generating unnecessary usage reports. Our optimization mechanism embraces the current AAA IETF standards RADIUS and its successor Diameter and does not require any modifications to the AAA protocols nor to the network access servers' implementation, and its implementation scope is limited to the AAA systems. The results demonstrate that our mechanism is robust under various operational conditions, easy to implement, and offers considerable potential for loss control compared to the current static approaches.

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“…which matches the result in [13], [14]. From (5), it is clear that there is a nonlinear relationship between the interim setting and the mean signaling load.…”

Section: Estimating the Aaa Signaling Loadsupporting

confidence: 86%

Section: Impact Of Roaming Users (Proxy Chains)mentioning

confidence: 99%

Section: Estimating the Aaa Signaling Loadmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Optimal Accounting Policies for AAA Systems in Mobile Telecommunications Networks

Zaghloul

Jukan

2010

IEEE Trans. on Mobile Comput.

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“…To the best of our knowledge, our study is the first to comprehensively analyze AAA signaling analytically, by taking into consideration protocol specifics, service session duration, mobility, and network size. The model presented in this paper is a major extension of our past work in [21], [22].…”

Section: Related Workmentioning

confidence: 97%

Signaling rate and performance for authentication, authorization, and accounting (AAA)) systems in all-IP cellular networks

Zaghloul

Jukan

2009

IEEE Trans. Wireless Commun.

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Authentication, Authorization, and Accounting (AAA) systems are one of the most significant architectural components of the current cellular networks and within the emerging IP Multimedia Subsystem (IMS) standard. Despite the operators' experience in AAA operations, very little is fundamentally known about the expected signaling rate towards the AAA system. In this paper, using stochastic and renewal theoretic techniques, we develop the first analytical model for the AAA signaling rate as a function of protocol parameters, users' access rates, session durations, and mobility. We provide model approximations and evaluate their accuracy under various operational conditions. Our results show that the AAA signaling rate is a monotonic non-linear function of the mobility rate and asymptotically converges to the AAA signaling rate in fixed networks. We also show that by adjusting the accounting interim and the authorization-lifetime intervals from half to full mean session duration, it is possible to define an AAA operational range for accounting messages that minimizes the signaling rate fluctuations due to likely perturbations in session and mobility statistics. The results also include the effect of the session dropping during handoffs and shows that is marginal in operational networks.

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