Traffic-aware optimization of heterogeneous access management

Bühler, Jörg; Wunder, Gerhard

doi:10.1109/tcomm.2010.06.090182

Cited by 25 publications

(23 citation statements)

References 20 publications

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“…It may be interesting, for example, to evaluate how much efficiency is lost with respect to the case of coordinated management. In [9], multiple access techniques are integrated; this is a strong research topic also in view of upcoming 5G cellular networks. In this case, the access selection may be done with or without coordination among the controllers allowing a comparison between the different performance evaluations obtained.…”

Section: Preliminariesmentioning

confidence: 99%

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Bayesian game analysis of a queueing system with multiple candidate servers

Guglielmi

Badia

2015

2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD)

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We combine queueing theory and game theory to evaluate the performance of a queueing system with multiple strategic candidate servers. The intent is to model a transmission system where packets can be sent via multiple options, each incurring a cost and controlled by a distributed management. Our purpose is to analyze the effects of the presence or the lack of both cooperation and communication between servers. The mathematical characterization of the uncertainty about the characteristics of the transmission alternatives available is captured through a Bayesian game formulation. In this setup, we compute both the Price of Anarchy, quantifying the inherent inefficiency arising from selfish management of each server, and the Price of Stability, which is the loss due to distributed system management, under different conditions of signaling exchange among the servers.

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Section: Preliminariesmentioning

confidence: 99%

“…For example, at the network layer it can be exploited for a distributed routing selection in multi-hop environments [8]. At the datalink layer, multiple access techniques can be coordinated similarly [9]. Finally, at the physical layer, this can be applied for devices powered by multiple energy sources [10].…”

Section: Introductionmentioning

confidence: 99%

Bayesian game analysis of a queueing system with multiple candidate servers

Guglielmi

Badia

2015

2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD)

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“…However, the channel heterogeneity among multiple spectrum bands is not considered. In [8] [9], radio resource management in heterogeneous networks have been studied and the problems are formulated as a Semi-Markov Decision Process (SMDP). However, since PUs' behavior is not considered and modeled, their proposed approaches cannot lead to an optimal solution for CR networks.…”

Section: Introductionmentioning

confidence: 99%

Optimal policy for joint spectrum resource management in multi-band cognitive radio networks

Suga

Guo

Tafazolli

2012

2012 IEEE 8th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)

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Cognitive Radio (CR) has been recognized as a promising solution to solve the current spectrum inefficiency problem. We consider a CR Base Station (CR-BS) has multiple spectrum bands over a wide frequency range and uses channel dependent data rates to communicate with the Secondary Users (SUs). To maximize the spectrum utilization while supporting the Quality of Service (QoS) of the SUs, various decisions needs to be made during the operational period of the CR system taking into account not only the behavior of Primary Users (PUs) and SUs but also the current utilization of each spectrum band. In this paper, we propose an optimal policy for joint spectrum resource management in multi-band CR networks, which consists of admission control, spectrum band selection, spectrum handover and eviction control. The problem is formulated as a Semi Markov Decision Process (SMDP) and the optimal decision for each system state is derived to reduce the SU blocking probability while keeping the SU dropping probability upper-bounded.Performance evaluation shows that the proposed policy outperforms other three policies in terms of both the SU blocking probability and the SU dropping probability.

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“…The greatest advantage of MDP-based optimal control policy is that each decision is made by taking into account both present and future outcomes. As a result, MDP has been adopted in numerous research dedicated to admission control schemes in bandwidthlimited wireless networks [10]- [16]. Ho et al [10], Choi et al [11] and Ni et al [12] investigated a MDP-based optimal call admission control policy with multiple traffic classes to maximize system utilization/revenue.…”

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confidence: 99%

“…Ho et al [10], Choi et al [11] and Ni et al [12] investigated a MDP-based optimal call admission control policy with multiple traffic classes to maximize system utilization/revenue. Yu et al [13], StevensNavarro et al [14], Chen et al [15] and Bühler et al [16] applied the MDP-based approach to integrated heterogeneous wireless networks to find an optimal call admission control mechanism. However, none of the quoted references dealt with the admission control for MSS.…”

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confidence: 99%

An Optimal Admission Control Protocol for Heterogeneous Multicast Streaming Services

Kim

Devanarayana

Alfa

et al. 2015

IEEE Trans. Commun.

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Abstract-We investigate optimal call admission control (CAC) policy for multicast streaming services (MSS) in 3rd generation (3G) and beyond wireless mobile networks. Several MSS sessions are supported simultaneously in a bandwidth-limited network. Active sessions are those that are currently serving some users, and inactive sessions are those that are currently not serving any users. An admission decision in MSS is required only when an inactive session is requested, unlike in unicasting. For this reason, if a user request for an inactive MSS session arrives, we should make an admission decision in anticipation of (i) the possible reward earned based on users served during a session active time generated by accepting it, and (ii) the influence of the session active time upon the future status of network bandwidth and admission decisions. Our objective is to determine when to admit or block a user asking an inactive MSS session to achieve the optimality in rewards. We formulate this problem as a semi-Markov decision process (SMDP), and a value iteration algorithm is used to obtain an optimal stationary deterministic policy. We also derive the user blocking probability of the optimal policy by analyzing an embedded Markov chain induced by it.

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Traffic-aware optimization of heterogeneous access management

Cited by 25 publications

References 20 publications

Bayesian game analysis of a queueing system with multiple candidate servers

Bayesian game analysis of a queueing system with multiple candidate servers

Optimal policy for joint spectrum resource management in multi-band cognitive radio networks

An Optimal Admission Control Protocol for Heterogeneous Multicast Streaming Services

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