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  • 1.
    Nordström, Ernst
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Carlström, Jakob
    Communication networks: a new reward model for MDP state aggregation with application to CAC and routing2005In: European transactions on telecommunications, ISSN 1124-318X, E-ISSN 2161-3915, Vol. 16, no 6, p. 495-508Article in journal (Refereed)
    Abstract [en]

    An optimal solution of the call admission control and routing problem in multi-service loss networks, in terms of average reward per time unit, is possible by modeling the network behavior as a Markov decision process (MDP). However, even after applying the standard link independence assumption, the solution of the corresponding set of link problems may involve considerable numerical computation. In this paper, we study an approximate MDP framework on the link level, where vector-valued MDP states are mapped into a set of aggregate scalar MDP states corresponding to link occupancies. In particular, we propose a new model of the expected reward for admitting a call on the network. Compared to Krishnan's and Hübner's method [11], our reward model more accurately reflects the bandwidth occupancy by different call categories. The exact and approximate link MDP frameworks are compared by simulations, and the results show that the proposed link reward model significantly improves the performance of Krishnan's and Hübner's method.

  • 2.
    Nordström, Ernst
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dziong, Zbigniew
    CAC and routing for multi-service networks with blocked wide-band calls delayed, part I: exact link MDP framework2006In: European transactions on telecommunications, ISSN 1124-318X, E-ISSN 2161-3915, Vol. 17, no 1, p. 21-36Article in journal (Refereed)
    Abstract [en]

    In this paper, we study the call admission control (CAC) and routing issue in multi-service networks. Two categories of calls are considered: a narrow-band (NB) with blocked calls cleared and a wide-band (WB) with blocked calls delayed. The objective function is formulated as reward maximisation with penalty for delay. The optimisation is subject to quality of service (QoS) constraints and, possibly, grade of service (GoS) constraints. A suboptimal solution is achieved by applying Markov decision process (MDP) theory together with a two-level approximation. First, the network is decomposed into a set of links assumed to have independent Markov and reward processes respectively. Second, the dimensions of the link Markov and reward processes are reduced by aggregation of the call classes into call categories. The CAC and routing policy is computed by the policy iteration algorithm from MDP theory. The numerical results show that the proposed CAC and routing method, based on the exact link MDP framework, is able to find an efficient trade-off between reward loss and average call set-up delay, outperforming conventional methods such as the least loaded routing (LLR).

  • 3.
    Nordström, Ernst
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dziong, Zbigniew
    CAC and routing for multi-service networks with blocked wide-band calls delayed, Part II: approximative link MDP framework2007In: European transactions on telecommunications, ISSN 1124-318X, E-ISSN 2161-3915, Vol. 18, no 1, p. 13-33Article in journal (Refereed)
    Abstract [en]

    In this paper, we study the call admission control (CAC) and routing issue in multi-service networks. Two categories of calls are considered: a narrow-band with blocked calls cleared and a wide-band with blocked calls delayed. The optimisation is subject to several quality of service (QoS) constraints, either on the packet or call level. The objective function is formulated as reward maximisation with penalty for delay. A suboptimal solution is achieved by applying Markov decision process (MDP) theory together with a three-level approximation. First, the network is decomposed into a set of links assumed to have independent Markov and reward processes respectively. Second, the dimensions of the link Markov and reward processes are reduced by aggregation of the call classes into call categories. Third, by applying decomposition of the link Markov process, the link MDP tasks are simplified considerably. The CAC and routing policy is computed by the policy iteration algorithm from MDP theory. The numerical results show that the proposed CAC and routing method, based on the approximate link MDP framework, is able to find an efficient trade-off between reward loss and average call set-up delay, outperforming conventional methods such as least loaded routing (LLR).

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